01538nas a2200169 4500008004200000245012100042210006900163520094900232100001801181700001701199700002501216700001801241700002201259700002201281700002001303856004501323 In Press d 00aDevelopment of a Computerized Adaptive Test for Anxiety Based on the Dutch–Flemish Version of the PROMIS Item Bank0 aDevelopment of a Computerized Adaptive Test for Anxiety Based on3 aWe used the Dutch–Flemish version of the USA PROMIS adult V1.0 item bank for Anxiety as input for developing a computerized adaptive test (CAT) to measure the entire latent anxiety continuum. First, psychometric analysis of a combined clinical and general population sample (N = 2,010) showed that the 29-item bank has psychometric properties that are required for a CAT administration. Second, a post hoc CAT simulation showed efficient and highly precise measurement, with an average number of 8.64 items for the clinical sample, and 9.48 items for the general population sample. Furthermore, the accuracy of our CAT version was highly similar to that of the full item bank administration, both in final score estimates and in distinguishing clinical subjects from persons without a mental health disorder. We discuss the future directions and limitations of CAT development with the Dutch–Flemish version of the PROMIS Anxiety item bank.1 aFlens, Gerard1 aSmits, Niels1 aTerwee, Caroline, B.1 aDekker, Joost1 aHuijbrechts, Irma1 aSpinhoven, Philip1 ade Beurs, Edwin uhttps://doi.org/10.1177/107319111774674200576nas a2200109 4500008004200000245016600042210006900208100002400277700002000301700001900321856012600340 In Press d 00aMeasurement efficiency for fixed-precision multidimensional computerized adaptive tests: Comparing health measurement and educational testing using example banks0 aMeasurement efficiency for fixedprecision multidimensional compu1 aPaap, Muirne, C. S.1 aBorn, Sebastian1 aBraeken, Johan uhttp://www.iacat.org/measurement-efficiency-fixed-precision-multidimensional-computerized-adaptive-tests-comparing-health00459nas a2200097 4500008004900000245009300049210006900142100001700211700001600228856011700244 In Press Engldsh 00aOptimizing cognitive ability measurement with multidimensional computer adaptive testing0 aOptimizing cognitive ability measurement with multidimensional c1 aMakransky, G1 aGlas, C A W uhttp://www.iacat.org/content/optimizing-cognitive-ability-measurement-multidimensional-computer-adaptive-testing01395nas a2200181 4500008004500000022001400045245008700059210006900146490000700215520080200222653003401024653002501058653001901083653001901102653001601121100002101137856005501158 2024 Engldsh  a2165-659200aThe Influence of Computerized Adaptive Testing on Psychometric Theory and Practice0 aInfluence of Computerized Adaptive Testing on Psychometric Theor0 v113 a

The major premise of this article is that part of the stimulus for the evolution of psychometric theory since the 1950s was the introduction of the concept of computerized adaptive testing (CAT) or its earlier non-CAT variations. The conceptual underpinnings of CAT that had the most influence on psychometric theory was the shift of emphasis from the test (or test score) as the focus of analysis to the test item (or item score). The change in focus allowed a change in the way that test results are conceived of as measurements. It also resolved the conflict among a number of ideas that were present in the early work on psychometric theory. Some of the conflicting ideas are summarized below to show how work on the development of CAT resolved some of those conflicts.

 

10acomputerized adaptive testing10aItem Response Theory10aparadigm shift10ascaling theory10atest design1 aReckase, Mark, D uhttps://jcatpub.net/index.php/jcat/issue/view/34/900541nas a2200169 4500008004500000245006600045210006600111300001000177490000700187653002100194653000800215653000800223653003000231653001300261100002000274856007700294 2023 Engldsh 00aExpanding the Meaning of Adaptive Testing to Enhance Validity0 aExpanding the Meaning of Adaptive Testing to Enhance Validity a22-310 v1010aAdaptive Testing10aCAT10aCBT10atest-taking disengagement10avalidity1 aWise, Steven, L uhttp://www.iacat.org/expanding-meaning-adaptive-testing-enhance-validity00670nas a2200193 4500008004500000022001400045245007100059210006700130490000700197653002100204653002900225653002500254653003900279653001600318100001400334700002200348700002400370856008200394 2023 Engldsh  a2165-659200aAn Extended Taxonomy of Variants of Computerized Adaptive Testing0 aExtended Taxonomy of Variants of Computerized Adaptive Testing0 v1010aAdaptive Testing10aevidence-centered design10aItem Response Theory10aknowledge-based model construction10amissingness1 aLevy, Roy1 aBehrens, John, T.1 aMislevy, Robert, J. uhttp://www.iacat.org/extended-taxonomy-variants-computerized-adaptive-testing00732nas a2200193 4500008004500000245009100045210006900136300001000205490000700215653003500222653003400257653002900291653002600320100001900346700002700365700002400392700002100416856010100437 2023 Engldsh 00aHow Do Trait Change Patterns Affect the Performance of Adaptive Measurement of Change?0 aHow Do Trait Change Patterns Affect the Performance of Adaptive  a32-580 v1010aadaptive measurement of change10acomputerized adaptive testing10alongitudinal measurement10atrait change patterns1 aTai, Ming, Him1 aCooperman, Allison, W.1 aDeWeese, Joseph, N.1 aWeiss, David, J. uhttp://www.iacat.org/how-do-trait-change-patterns-affect-performance-adaptive-measurement-change00537nas a2200181 4500008004500000022001400045245004000059210004000099260001200139300000800151490000600159653003300165653003000198653002000228653002700248100002200275856005800297 2022 Engldsh  a2165-659200aImproving Precision of CAT Measures0 aImproving Precision of CAT Measures c10/2022 a1-70 v910a: dichotomously scored items10aoption probability theory10ascoring methods10asubjective probability1 aBarnard, John, J. uhttp://www.iacat.org/improving-precision-cat-measures00480nas a2200133 4500008003900000245007300039210006700112490000600179653003400185653001300219653003500232100002600267856005300293 2022 d00aThe (non)Impact of Misfitting Items in Computerized Adaptive Testing0 anonImpact of Misfitting Items in Computerized Adaptive Testing0 v910acomputerized adaptive testing10aitem fit10athree-parameter logistic model1 aDeMars, Christine, E. uhttps://jcatpub.net/index.php/jcat/issue/view/2601308nas a2200133 4500008003900000245003900039210003500078300001000113490000700123520095700130100001901087700002301106856004501129 2020 d00aA Blocked-CAT Procedure for CD-CAT0 aBlockedCAT Procedure for CDCAT a49-640 v443 aThis article introduces a blocked-design procedure for cognitive diagnosis computerized adaptive testing (CD-CAT), which allows examinees to review items and change their answers during test administration. Four blocking versions of the new procedure were proposed. In addition, the impact of several factors, namely, item quality, generating model, block size, and test length, on the classification rates was investigated. Three popular item selection indices in CD-CAT were used and their efficiency compared using the new procedure. An additional study was carried out to examine the potential benefit of item review. The results showed that the new procedure is promising in that allowing item review resulted only in a small loss in attribute classification accuracy under some conditions. Moreover, using a blocked-design CD-CAT is beneficial to the extent that it alleviates the negative impact of test anxiety on examinees’ true performance.1 aKaplan, Mehmet1 ade la Torre, Jimmy uhttps://doi.org/10.1177/014662161983550002729nas a2200145 4500008003900000245012200039210006900161490000700230520216000237100003002397700002702427700002802454700002502482856007602507 2020 d00aComputerized adaptive testing to screen children for emotional and behavioral problems by preventive child healthcare0 aComputerized adaptive testing to screen children for emotional a0 v203 a

Background

Questionnaires to detect emotional and behavioral problems (EBP) in Preventive Child Healthcare (PCH) should be short which potentially affects validity and reliability. Simulation studies have shown that Computerized Adaptive Testing (CAT) could overcome these weaknesses. We studied the applicability (using the measures participation rate, satisfaction, and efficiency) and the validity of CAT in routine PCH practice.

Methods

We analyzed data on 461 children aged 10–11 years (response 41%), who were assessed during routine well-child examinations by PCH professionals. Before the visit, parents completed the CAT and the Child Behavior Checklist (CBCL). Satisfaction was measured by parent- and PCH professional-report. Efficiency of the CAT procedure was measured as number of items needed to assess whether a child has serious problems or not. Its validity was assessed using the CBCL as the criterion.

Results

Parents and PCH professionals rated the CAT on average as good. The procedure required at average 16 items to assess whether a child has serious problems or not. Agreement of scores on the CAT scales with corresponding CBCL scales was high (range of Spearman correlations 0.59–0.72). Area Under Curves (AUC) were high (range: 0.95–0.97) for the Psycat total, externalizing, and hyperactivity scales using corresponding CBCL scale scores as criterion. For the Psycat internalizing scale the AUC was somewhat lower but still high (0.86).

Conclusions

CAT is a valid procedure for the identification of emotional and behavioral problems in children aged 10–11 years. It may support the efficient and accurate identification of children with overall, and potentially also specific, emotional and behavioral problems in routine PCH.

1 aTheunissen, Meninou, H.C.1 ade Wolff, Marianne, S.1 aDeurloo, Jacqueline, A.1 aVogels, Anton, G. C. uhttps://bmcpediatr.biomedcentral.com/articles/10.1186/s12887-020-2018-101973nas a2200145 4500008003900000245012800039210006900167300001200236490000700248520147000255100002001725700001801745700001901763856004501782 2020 d00aA Dynamic Stratification Method for Improving Trait Estimation in Computerized Adaptive Testing Under Item Exposure Control0 aDynamic Stratification Method for Improving Trait Estimation in  a182-1960 v443 aWhen computerized adaptive testing (CAT) is under stringent item exposure control, the precision of trait estimation will substantially decrease. A new item selection method, the dynamic Stratification method based on Dominance Curves (SDC), which is aimed at improving trait estimation, is proposed to mitigate this problem. The objective function of the SDC in item selection is to maximize the sum of test information for all examinees rather than maximizing item information for individual examinees at a single-item administration, as in conventional CAT. To achieve this objective, the SDC uses dominance curves to stratify an item pool into strata with the number being equal to the test length to precisely and accurately increase the quality of the administered items as the test progresses, reducing the likelihood that a high-discrimination item will be administered to an examinee whose ability is not close to the item difficulty. Furthermore, the SDC incorporates a dynamic process for on-the-fly item–stratum adjustment to optimize the use of quality items. Simulation studies were conducted to investigate the performance of the SDC in CAT under item exposure control at different levels of severity. According to the results, the SDC can efficiently improve trait estimation in CAT through greater precision and more accurate trait estimation than those generated by other methods (e.g., the maximum Fisher information method) in most conditions.1 aChen, Jyun-Hong1 aChao, Hsiu-Yi1 aChen, Shu-Ying uhttps://doi.org/10.1177/014662161984382001462nas a2200121 4500008003900000245009900039210006900138300001100207490000700218520105100225100001901276856004501295 2020 d00aFramework for Developing Multistage Testing With Intersectional Routing for Short-Length Tests0 aFramework for Developing Multistage Testing With Intersectional  a87-1020 v443 aMultistage testing (MST) has many practical advantages over typical item-level computerized adaptive testing (CAT), but there is a substantial tradeoff when using MST because of its reduced level of adaptability. In typical MST, the first stage almost always performs as a routing stage in which all test takers see a linear test form. If multiple test sections measure different but moderately or highly correlated traits, then a score estimate for one section might be capable of adaptively selecting item modules for following sections without having to administer routing stages repeatedly for each section. In this article, a new framework for developing MST with intersectional routing (ISR) was proposed and evaluated under several research conditions with different MST structures, section score distributions and relationships, and types of regression models for ISR. The overall findings of the study suggested that MST with ISR approach could improve measurement efficiency and test optimality especially with tests with short lengths.1 aHan, Kyung, T. uhttps://doi.org/10.1177/014662161983722602111nas a2200193 4500008003900000245007100039210006900110300000900179490000700188520153100195653000701726653003201733653001701765653002301782100001501805700001501820700001901835856006301854 2020 d00aItem Calibration Methods With Multiple Subscale Multistage Testing0 aItem Calibration Methods With Multiple Subscale Multistage Testi a3-280 v573 aAbstract Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait (θ) estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to calibrate items using the incomplete data from MST design. Further complication arises when there are multiple correlated subscales per test, and when items from different subscales need to be calibrated according to their respective score reporting metric. The current calibration-per-subscale method produced biased item parameters, and there is no available method for resolving the challenge. Deriving from the missing data principle, we showed when calibrating all items together the Rubin's ignorability assumption is satisfied such that the traditional single-group calibration is sufficient. When calibrating items per subscale, we proposed a simple modification to the current calibration-per-subscale method that helps reinstate the missing-at-random assumption and therefore corrects for the estimation bias that is otherwise existent. Three mainstream calibration methods are discussed in the context of MST, they are the marginal maximum likelihood estimation, the expectation maximization method, and the fixed parameter calibration. An extensive simulation study is conducted and a real data example from NAEP is analyzed to provide convincing empirical evidence.10aEM10amarginal maximum likelihood10amissing data10amultistage testing1 aWang, Chun1 aChen, Ping1 aJiang, Shengyu uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1224101507nas a2200157 4500008003900000245011800039210006900157300001200226490000700238520096800245100001901213700002001232700002101252700001301273856006301286 2020 d00aItem Selection and Exposure Control Methods for Computerized Adaptive Testing with Multidimensional Ranking Items0 aItem Selection and Exposure Control Methods for Computerized Ada a343-3690 v573 aAbstract The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across items). To address these issues, we introduce subpool partition strategies for item selection and within-person statement exposure control procedures. Simulations showed that the multinomial method reduces computation time while maintaining measurement precision. Both the freeze and revised Sympson-Hetter online (RSHO) methods controlled the statement exposure rate; RSHO sacrificed some measurement precision but increased pool use. Furthermore, preventing a statement's repetition on consecutive items neither hindered the effectiveness of the freeze or RSHO method nor reduced measurement precision.1 aChen, Chia-Wen1 aWang, Wen-Chung1 aChiu, Ming, Ming1 aRo, Sage uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1225201806nas a2200145 4500008003900000245012400039210006900163300001000232490000700242520130500249100001801554700002401572700001901596856004501615 2020 d00aMultidimensional Test Assembly Using Mixed-Integer Linear Programming: An Application of Kullback–Leibler Information0 aMultidimensional Test Assembly Using MixedInteger Linear Program a17-320 v443 aMany educational testing programs require different test forms with minimal or no item overlap. At the same time, the test forms should be parallel in terms of their statistical and content-related properties. A well-established method to assemble parallel test forms is to apply combinatorial optimization using mixed-integer linear programming (MILP). Using this approach, in the unidimensional case, Fisher information (FI) is commonly used as the statistical target to obtain parallelism. In the multidimensional case, however, FI is a multidimensional matrix, which complicates its use as a statistical target. Previous research addressing this problem focused on item selection criteria for multidimensional computerized adaptive testing (MCAT). Yet these selection criteria are not directly transferable to the assembly of linear parallel test forms. To bridge this gap the authors derive different statistical targets, based on either FI or the Kullback–Leibler (KL) divergence, that can be applied in MILP models to assemble multidimensional parallel test forms. Using simulated item pools and an item pool based on empirical items, the proposed statistical targets are compared and evaluated. Promising results with respect to the KL-based statistical targets are presented and discussed.1 aDebeer, Dries1 avan Rijn, Peter, W.1 aAli, Usama, S. uhttps://doi.org/10.1177/014662161982758601760nas a2200145 4500008003900000245008000039210006900119300000900188490000700197520132100204100001601525700001501541700001301556856004501569 2020 d00aNew Efficient and Practicable Adaptive Designs for Calibrating Items Online0 aNew Efficient and Practicable Adaptive Designs for Calibrating I a3-160 v443 aWhen calibrating new items online, it is practicable to first compare all new items according to some criterion and then assign the most suitable one to the current examinee who reaches a seeding location. The modified D-optimal design proposed by van der Linden and Ren (denoted as D-VR design) works within this practicable framework with the aim of directly optimizing the estimation of item parameters. However, the optimal design point for a given new item should be obtained by comparing all examinees in a static examinee pool. Thus, D-VR design still has room for improvement in calibration efficiency from the view of traditional optimal design. To this end, this article incorporates the idea of traditional optimal design into D-VR design and proposes a new online calibration design criterion, namely, excellence degree (ED) criterion. Four different schemes are developed to measure the information provided by the current examinee when implementing this new criterion, and four new ED designs equipped with them are put forward accordingly. Simulation studies were conducted under a variety of conditions to compare the D-VR design and the four proposed ED designs in terms of calibration efficiency. Results showed that the four ED designs outperformed D-VR design in almost all simulation conditions.1 aHe, Yinhong1 aChen, Ping1 aLi, Yong uhttps://doi.org/10.1177/014662161882485401382nas a2200133 4500008003900000245010400039210006900143300001200212490000700224520093300231100001701164700002201181856004501203 2020 d00aThe Optimal Item Pool Design in Multistage Computerized Adaptive Tests With the p-Optimality Method0 aOptimal Item Pool Design in Multistage Computerized Adaptive Tes a955-9740 v803 aThe present study extended the p-optimality method to the multistage computerized adaptive test (MST) context in developing optimal item pools to support different MST panel designs under different test configurations. Using the Rasch model, simulated optimal item pools were generated with and without practical constraints of exposure control. A total number of 72 simulated optimal item pools were generated and evaluated by an overall sample and conditional sample using various statistical measures. Results showed that the optimal item pools built with the p-optimality method provide sufficient measurement accuracy under all simulated MST panel designs. Exposure control affected the item pool size, but not the item distributions and item pool characteristics. This study demonstrated that the p-optimality method can adapt to MST item pool design, facilitate the MST assembly process, and improve its scoring accuracy.1 aYang, Lihong1 aReckase, Mark, D. uhttps://doi.org/10.1177/001316441990129202064nas a2200157 4500008003900000245009100039210006900130300001200199490000700211520157600218100001501794700001901809700001401828700001901842856004501861 2020 d00aStratified Item Selection Methods in Cognitive Diagnosis Computerized Adaptive Testing0 aStratified Item Selection Methods in Cognitive Diagnosis Compute a346-3610 v443 aCognitive diagnostic computerized adaptive testing (CD-CAT) aims to obtain more useful diagnostic information by taking advantages of computerized adaptive testing (CAT). Cognitive diagnosis models (CDMs) have been developed to classify examinees into the correct proficiency classes so as to get more efficient remediation, whereas CAT tailors optimal items to the examinee’s mastery profile. The item selection method is the key factor of the CD-CAT procedure. In recent years, a large number of parametric/nonparametric item selection methods have been proposed. In this article, the authors proposed a series of stratified item selection methods in CD-CAT, which are combined with posterior-weighted Kullback–Leibler (PWKL), nonparametric item selection (NPS), and weighted nonparametric item selection (WNPS) methods, and named S-PWKL, S-NPS, and S-WNPS, respectively. Two different types of stratification indices were used: original versus novel. The performances of the proposed item selection methods were evaluated via simulation studies and compared with the PWKL, NPS, and WNPS methods without stratification. Manipulated conditions included calibration sample size, item quality, number of attributes, number of strata, and data generation models. Results indicated that the S-WNPS and S-NPS methods performed similarly, and both outperformed the S-PWKL method. And item selection methods with novel stratification indices performed slightly better than the ones with original stratification indices, and those without stratification performed the worst.1 aYang, Jing1 aChang, Hua-Hua1 aTao, Jian1 aShi, Ningzhong uhttps://doi.org/10.1177/014662161989378300452nas a2200133 4500008004500000022001400045245007200059210006900131300000900200490000600209100002300215700002000238856006000258 2020 Engldsh  a2165-659200aThree Measures of Test Adaptation Based on Optimal Test Information0 aThree Measures of Test Adaptation Based on Optimal Test Informat a1-190 v81 aKingsbury, Gage, G1 aWise, Steven, L uhttp://iacat.org/jcat/index.php/jcat/article/view/80/3700452nas a2200133 4500008004500000022001400045245007200059210006900131300000900200490000600209100002300215700002000238856006000258 2020 Engldsh  a2165-659200aThree Measures of Test Adaptation Based on Optimal Test Information0 aThree Measures of Test Adaptation Based on Optimal Test Informat a1-190 v81 aKingsbury, Gage, G1 aWise, Steven, L uhttp://iacat.org/jcat/index.php/jcat/article/view/80/3701989nas a2200133 4500008003900000245006800039210006800107300001000175490000700185520158200192100001701774700001901791856004501810 2019 d00aAdaptive Testing With a Hierarchical Item Response Theory Model0 aAdaptive Testing With a Hierarchical Item Response Theory Model a51-670 v433 aThe hierarchical item response theory (H-IRT) model is very flexible and allows a general factor and subfactors within an overall structure of two or more levels. When an H-IRT model with a large number of dimensions is used for an adaptive test, the computational burden associated with interim scoring and selection of subsequent items is heavy. An alternative approach for any high-dimension adaptive test is to reduce dimensionality for interim scoring and item selection and then revert to full dimensionality for final score reporting, thereby significantly reducing the computational burden. This study compared the accuracy and efficiency of final scoring for multidimensional, local multidimensional, and unidimensional item selection and interim scoring methods, using both simulated and real item pools. The simulation study was conducted under 10 conditions (i.e., five test lengths and two H-IRT models) with a simulated sample of 10,000 students. The study with the real item pool was conducted using item parameters from an actual 45-item adaptive test with a simulated sample of 10,000 students. Results indicate that the theta estimations provided by the local multidimensional and unidimensional item selection and interim scoring methods were relatively as accurate as the theta estimation provided by the multidimensional item selection and interim scoring method, especially during the real item pool study. In addition, the multidimensional method required the longest computation time and the unidimensional method required the shortest computation time.1 aWang, Wenhao1 aKingston, Neal uhttps://doi.org/10.1177/014662161876571401626nas a2200145 4500008003900000245008600039210006900125300001200194490000700206520117400213100001701387700001801404700001301422856004501435 2019 d00aApplication of Dimension Reduction to CAT Item Selection Under the Bifactor Model0 aApplication of Dimension Reduction to CAT Item Selection Under t a419-4340 v433 aMultidimensional computerized adaptive testing (MCAT) based on the bifactor model is suitable for tests with multidimensional bifactor measurement structures. Several item selection methods that proved to be more advantageous than the maximum Fisher information method are not practical for bifactor MCAT due to time-consuming computations resulting from high dimensionality. To make them applicable in bifactor MCAT, dimension reduction is applied to four item selection methods, which are the posterior-weighted Fisher D-optimality (PDO) and three non-Fisher information-based methods—posterior expected Kullback–Leibler information (PKL), continuous entropy (CE), and mutual information (MI). They were compared with the Bayesian D-optimality (BDO) method in terms of estimation precision. When both the general and group factors are the measurement objectives, BDO, PDO, CE, and MI perform equally well and better than PKL. When the group factors represent nuisance dimensions, MI and CE perform the best in estimating the general factor, followed by the BDO, PDO, and PKL. How the bifactor pattern and test length affect estimation accuracy was also discussed.1 aMao, Xiuzhen1 aZhang, Jiahui1 aXin, Tao uhttps://doi.org/10.1177/014662161881308601943nas a2200145 4500008003900000245007700039210006900116300001200185490000700197520148100204100002101685700002301706700002301729856004501752 2019 d00aComputerized Adaptive Testing for Cognitively Based Multiple-Choice Data0 aComputerized Adaptive Testing for Cognitively Based MultipleChoi a388-4010 v433 aCognitive diagnosis models (CDMs) are latent class models that hold great promise for providing diagnostic information about student knowledge profiles. The increasing use of computers in classrooms enhances the advantages of CDMs for more efficient diagnostic testing by using adaptive algorithms, referred to as cognitive diagnosis computerized adaptive testing (CD-CAT). When multiple-choice items are involved, CD-CAT can be further improved by using polytomous scoring (i.e., considering the specific options students choose), instead of dichotomous scoring (i.e., marking answers as either right or wrong). In this study, the authors propose and evaluate the performance of the Jensen–Shannon divergence (JSD) index as an item selection method for the multiple-choice deterministic inputs, noisy “and” gate (MC-DINA) model. Attribute classification accuracy and item usage are evaluated under different conditions of item quality and test termination rule. The proposed approach is compared with the random selection method and an approximate approach based on dichotomized responses. The results show that under the MC-DINA model, JSD improves the attribute classification accuracy significantly by considering the information from distractors, even with a very short test length. This result has important implications in practical classroom settings as it can allow for dramatically reduced testing times, thus resulting in more targeted learning opportunities.1 aYigit, Hulya, D.1 aSorrel, Miguel, A.1 ade la Torre, Jimmy uhttps://doi.org/10.1177/014662161879866501598nas a2200157 4500008003900000245012200039210006900161300001200230490000700242520104300249100002401292700001601316700002001332700002501352856006301377 2019 d00aComputerized Adaptive Testing in Early Education: Exploring the Impact of Item Position Effects on Ability Estimation0 aComputerized Adaptive Testing in Early Education Exploring the I a437-4510 v563 aAbstract Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in early education, an area of testing that has received relatively limited psychometric attention. In an initial study, multilevel item response models fit to data from an early literacy measure revealed statistically significant increases in difficulty for items appearing later in a 20-item form. The estimated linear change in logits for an increase of 1 in position was .024, resulting in a predicted change of .46 logits for a shift from the beginning to the end of the form. A subsequent simulation study examined impacts of item position effects on person ability estimation within computerized adaptive testing. Implications and recommendations for practice are discussed.1 aAlbano, Anthony, D.1 aCai, Liuhan1 aLease, Erin, M.1 aMcConnell, Scott, R. uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1221501777nas a2200145 4500008003900000245005500039210005400094300001300148490000700161520135000168100001901518700002601537700002301563856004501586 2019 d00aDeveloping Multistage Tests Using D-Scoring Method0 aDeveloping Multistage Tests Using DScoring Method a988-10080 v793 aThe D-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number correct score computation and relaxed requirements for model sample sizes. Because of its unique combination of those merits, the D-scoring method has seen quick adoption in the educational and psychological measurement field. Because item-level difficulty information is available with the D-scoring method and item difficulties are reflected in test scores, it conceptually makes sense to use the D-scoring method with adaptive test designs such as multistage testing (MST). In this study, we developed and compared several versions of the MST mechanism using the D-scoring approach and also proposed and implemented a new framework for conducting MST simulation under the D-scoring method. Our findings suggest that the score recovery performance under MST with D-scoring was promising, as it retained score comparability across different MST paths. We found that MST using the D-scoring method can achieve improvements in measurement precision and efficiency over linear-based tests that use D-scoring method.1 aHan, Kyung, T.1 aDimitrov, Dimiter, M.1 aAl-Mashary, Faisal uhttps://doi.org/10.1177/001316441984142801445nas a2200157 4500008003900000245010600039210006900145300001200214490000700226520090200233100002301135700002501158700002601183700001501209856006301224 2019 d00aEfficiency of Targeted Multistage Calibration Designs Under Practical Constraints: A Simulation Study0 aEfficiency of Targeted Multistage Calibration Designs Under Prac a121-1460 v563 aAbstract Calibration of an item bank for computer adaptive testing requires substantial resources. In this study, we investigated whether the efficiency of calibration under the Rasch model could be enhanced by improving the match between item difficulty and student ability. We introduced targeted multistage calibration designs, a design type that considers ability-related background variables and performance for assigning students to suitable items. Furthermore, we investigated whether uncertainty about item difficulty could impair the assembling of efficient designs. The results indicated that targeted multistage calibration designs were more efficient than ordinary targeted designs under optimal conditions. Limited knowledge about item difficulty reduced the efficiency of one of the two investigated targeted multistage calibration designs, whereas targeted designs were more robust.1 aBerger, Stéphanie1 aVerschoor, Angela, J1 aEggen, Theo, J. H. M.1 aMoser, Urs uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1220300579nas a2200169 4500008004500000245007100045210006900116300000900185490000600194653003100200653002000231653005100251100001800302700001400320700001500334856006000349 2019 Engldsh 00aHow Adaptive Is an Adaptive Test: Are All Adaptive Tests Adaptive?0 aHow Adaptive Is an Adaptive Test Are All Adaptive Tests Adaptive a1-140 v710acomputerized adaptive test10amultistage test10astatistical indicators of amount of adaptation1 aReckase, Mark1 aJu, Unhee1 aKim, Sewon uhttp://iacat.org/jcat/index.php/jcat/article/view/69/3401544nas a2200145 4500008003900000245009800039210006900137300001200206490000700218520104000225100002901265700002501294700003401319856004501353 2019 d00aImputation Methods to Deal With Missing Responses in Computerized Adaptive Multistage Testing0 aImputation Methods to Deal With Missing Responses in Computerize a495-5110 v793 aRouting examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated multiple missing data methods in computerized adaptive multistage testing, including two imputation techniques, the use of full information maximum likelihood and the use of scoring missing data as incorrect. These methods were examined under the missing completely at random, missing at random, and missing not at random frameworks, as well as other testing conditions. Comparisons were made to baseline conditions where no missing data were present. The results showed that imputation and the full information maximum likelihood methods outperformed incorrect scoring methods in terms of average bias, average root mean square error, and correlation between estimated and true thetas.1 aCetin-Berber, Dee, Duygu1 aSari, Halil, Ibrahim1 aHuggins-Manley, Anne, Corinne uhttps://doi.org/10.1177/001316441880553202022nas a2200193 4500008003900000245010500039210006900144300001200213490000700225520140200232100002301634700001901657700001801676700002101694700002201715700002801737700001801765856004501783 2019 d00aAn Investigation of Exposure Control Methods With Variable-Length CAT Using the Partial Credit Model0 aInvestigation of Exposure Control Methods With VariableLength CA a624-6380 v433 aThe purpose of this simulation study was to investigate the effect of several different item exposure control procedures in computerized adaptive testing (CAT) with variable-length stopping rules using the partial credit model. Previous simulation studies on CAT exposure control methods with polytomous items rarely considered variable-length tests. The four exposure control techniques examined were the randomesque with a group of three items, randomesque with a group of six items, progressive-restricted standard error (PR-SE), and no exposure control. The two variable-length stopping rules included were the SE and predicted standard error reduction (PSER), along with three item pools of varied sizes (43, 86, and 172 items). Descriptive statistics on number of nonconvergent cases, measurement precision, testing burden, item overlap, item exposure, and pool utilization were calculated. Results revealed that the PSER stopping rule administered fewer items on average while maintaining measurement precision similar to the SE stopping rule across the different item pool sizes and exposure controls. The PR-SE exposure control procedure surpassed the randomesque methods by further reducing test overlap, maintaining maximum exposure rates at the target rate or lower, and utilizing all items from the pool with a minimal increase in number of items administered and nonconvergent cases.1 aLeroux, Audrey, J.1 aWaid-Ebbs, Kay1 aWen, Pey-Shan1 aHelmer, Drew, A.1 aGraham, David, P.1 aO’Connor, Maureen, K.1 aRay, Kathleen uhttps://doi.org/10.1177/014662161882485601341nas a2200133 4500008003900000245010900039210006900148300001200217490000700229520088900236100001801125700001901143856004501162 2019 d00aItem Selection Criteria With Practical Constraints in Cognitive Diagnostic Computerized Adaptive Testing0 aItem Selection Criteria With Practical Constraints in Cognitive  a335-3570 v793 aFor item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP\_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP\_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.1 aLin, Chuan-Ju1 aChang, Hua-Hua uhttps://doi.org/10.1177/001316441879063401729nas a2200145 4500008003900000245016600039210006900205300001000274490000700284520118400291100002401475700002001499700001901519856004501538 2019 d00aMeasurement Efficiency for Fixed-Precision Multidimensional Computerized Adaptive Tests: Comparing Health Measurement and Educational Testing Using Example Banks0 aMeasurement Efficiency for FixedPrecision Multidimensional Compu a68-830 v433 aIt is currently not entirely clear to what degree the research on multidimensional computerized adaptive testing (CAT) conducted in the field of educational testing can be generalized to fields such as health assessment, where CAT design factors differ considerably from those typically used in educational testing. In this study, the impact of a number of important design factors on CAT performance is systematically evaluated, using realistic example item banks for two main scenarios: health assessment (polytomous items, small to medium item bank sizes, high discrimination parameters) and educational testing (dichotomous items, large item banks, small- to medium-sized discrimination parameters). Measurement efficiency is evaluated for both between-item multidimensional CATs and separate unidimensional CATs for each latent dimension. In this study, we focus on fixed-precision (variable-length) CATs because it is both feasible and desirable in health settings, but so far most research regarding CAT has focused on fixed-length testing. This study shows that the benefits associated with fixed-precision multidimensional CAT hold under a wide variety of circumstances.1 aPaap, Muirne, C. S.1 aBorn, Sebastian1 aBraeken, Johan uhttps://doi.org/10.1177/014662161876571901810nas a2200133 4500008003900000245010200039210006900141300001200210490000700222520136300229100001901592700002001611856004501631 2019 d00aMultidimensional Computerized Adaptive Testing Using Non-Compensatory Item Response Theory Models0 aMultidimensional Computerized Adaptive Testing Using NonCompensa a464-4800 v433 aCurrent use of multidimensional computerized adaptive testing (MCAT) has been developed in conjunction with compensatory multidimensional item response theory (MIRT) models rather than with non-compensatory ones. In recognition of the usefulness of MCAT and the complications associated with non-compensatory data, this study aimed to develop MCAT algorithms using non-compensatory MIRT models and to evaluate their performance. For the purpose of the study, three item selection methods were adapted and compared, namely, the Fisher information method, the mutual information method, and the Kullback–Leibler information method. The results of a series of simulations showed that the Fisher information and mutual information methods performed similarly, and both outperformed the Kullback–Leibler information method. In addition, it was found that the more stringent the termination criterion and the higher the correlation between the latent traits, the higher the resulting measurement precision and test reliability. Test reliability was very similar across the dimensions, regardless of the correlation between the latent traits and termination criterion. On average, the difficulties of the administered items were found to be at a lower level than the examinees’ abilities, which shed light on item bank construction for non-compensatory items.1 aHsu, Chia-Ling1 aWang, Wen-Chung uhttps://doi.org/10.1177/014662161880028001915nas a2200145 4500008003900000245007200039210006900111300001200180490000700192520146600199100002001665700001801685700002101703856004501724 2019 d00aNonparametric CAT for CD in Educational Settings With Small Samples0 aNonparametric CAT for CD in Educational Settings With Small Samp a543-5610 v433 aCognitive diagnostic computerized adaptive testing (CD-CAT) has been suggested by researchers as a diagnostic tool for assessment and evaluation. Although model-based CD-CAT is relatively well researched in the context of large-scale assessment systems, this type of system has not received the same degree of research and development in small-scale settings, such as at the course-based level, where this system would be the most useful. The main obstacle is that the statistical estimation techniques that are successfully applied within the context of a large-scale assessment require large samples to guarantee reliable calibration of the item parameters and an accurate estimation of the examinees’ proficiency class membership. Such samples are simply not obtainable in course-based settings. Therefore, the nonparametric item selection (NPS) method that does not require any parameter calibration, and thus, can be used in small educational programs is proposed in the study. The proposed nonparametric CD-CAT uses the nonparametric classification (NPC) method to estimate an examinee’s attribute profile and based on the examinee’s item responses, the item that can best discriminate the estimated attribute profile and the other attribute profiles is then selected. The simulation results show that the NPS method outperformed the compared parametric CD-CAT algorithms and the differences were substantial when the calibration samples were small.1 aChang, Yuan-Pei1 aChiu, Chia-Yi1 aTsai, Rung-Ching uhttps://doi.org/10.1177/014662161881311301927nas a2200157 4500008003900000245010900039210006900148300001200217490000700229520138500236100002201621700002001643700002201663700002101685856006301706 2019 d00aRouting Strategies and Optimizing Design for Multistage Testing in International Large-Scale Assessments0 aRouting Strategies and Optimizing Design for Multistage Testing  a192-2130 v563 aAbstract This study investigates the effect of several design and administration choices on item exposure and person/item parameter recovery under a multistage test (MST) design. In a simulation study, we examine whether number-correct (NC) or item response theory (IRT) methods are differentially effective at routing students to the correct next stage(s) and whether routing choices (optimal versus suboptimal routing) have an impact on achievement precision. Additionally, we examine the impact of testlet length on both person and item recovery. Overall, our results suggest that no single approach works best across the studied conditions. With respect to the mean person parameter recovery, IRT scoring (via either Fisher information or preliminary EAP estimates) outperformed classical NC methods, although differences in bias and root mean squared error were generally small. Item exposure rates were found to be more evenly distributed when suboptimal routing methods were used, and item recovery (both difficulty and discrimination) was most precisely observed for items with moderate difficulties. Based on the results of the simulation study, we draw conclusions and discuss implications for practice in the context of international large-scale assessments that recently introduced adaptive assessment in the form of MST. Future research directions are also discussed.1 aSvetina, Dubravka1 aLiaw, Yuan-Ling1 aRutkowski, Leslie1 aRutkowski, David uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1220601609nas a2200205 4500008004500000022001400045245005000059210004900109300001000158490000600168520099300174653003501167653003401202653002301236653001901259653002701278100002301305700001501328856006001343 2019 Engldsh  a2165-659200aTime-Efficient Adaptive Measurement of Change0 aTimeEfficient Adaptive Measurement of Change a15-340 v73 a

The adaptive measurement of change (AMC) refers to the use of computerized adaptive testing (CAT) at multiple occasions to efficiently assess a respondent’s improvement, decline, or sameness from occasion to occasion. Whereas previous AMC research focused on administering the most informative item to a respondent at each stage of testing, the current research proposes the use of Fisher information per time unit as an item selection procedure for AMC. The latter procedure incorporates not only the amount of information provided by a given item but also the expected amount of time required to complete it. In a simulation study, the use of Fisher information per time unit item selection resulted in a lower false positive rate in the majority of conditions studied, and a higher true positive rate in all conditions studied, compared to item selection via Fisher information without accounting for the expected time taken. Future directions of research are suggested.

10aadaptive measurement of change10acomputerized adaptive testing10aFisher information10aitem selection10aresponse-time modeling1 aFinkelman, Matthew1 aWang, Chun uhttp://iacat.org/jcat/index.php/jcat/article/view/73/3500419nas a2200133 4500008004500000245005400045210005400099300001000153490000600163100001800169700001700187700001700204856006400221 2018 Engldsh 00aAdaptive Item Selection Under Matroid Constraints0 aAdaptive Item Selection Under Matroid Constraints a15-360 v61 aBengs, Daniel1 aBrefeld, Ulf1 aKröhne, Ulf uhttp://www.iacat.org/jcat/index.php/jcat/article/view/64/3201434nas a2200133 4500008003900000245010800039210006900147300001200216490000700228520097100235100001201206700001901218856006301237 2018 d00aA Comparison of Constraint Programming and Mixed-Integer Programming for Automated Test-Form Generation0 aComparison of Constraint Programming and MixedInteger Programmin a435-4560 v553 aAbstract The final step of the typical process of developing educational and psychological tests is to place the selected test items in a formatted form. The step involves the grouping and ordering of the items to meet a variety of formatting constraints. As this activity tends to be time-intensive, the use of mixed-integer programming (MIP) has been proposed to automate it. The goal of this article is to show how constraint programming (CP) can be used as an alternative to automate test-form generation problems with a large variety of formatting constraints, and how it compares with MIP-based form generation as for its models, solutions, and running times. Two empirical examples are presented: (i) automated generation of a computerized fixed-form; and (ii) automated generation of shadow tests for multistage testing. Both examples show that CP works well with feasible solutions and running times likely to be better than that for MIP-based applications.1 aLi, Jie1 aLinden, Wim, J uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1218701188nas a2200133 4500008003900000245006600039210006500105300001200170490000700182520079400189100001300983700001300996856004501009 2018 d00aConstructing Shadow Tests in Variable-Length Adaptive Testing0 aConstructing Shadow Tests in VariableLength Adaptive Testing a538-5520 v423 aImposing content constraints is very important in most operational computerized adaptive testing (CAT) programs in educational measurement. Shadow test approach to CAT (Shadow CAT) offers an elegant solution to imposing statistical and nonstatistical constraints by projecting future consequences of item selection. The original form of Shadow CAT presumes fixed test lengths. The goal of the current study was to extend Shadow CAT to tests under variable-length termination conditions and evaluate its performance relative to other content balancing approaches. The study demonstrated the feasibility of constructing Shadow CAT with variable test lengths and in operational CAT programs. The results indicated the superiority of the approach compared with other content balancing methods.1 aDiao, Qi1 aRen, Hao uhttps://doi.org/10.1177/014662161775373601267nas a2200157 4500008003900000245009900039210006900138300001200207490000700219520076400226100001800990700001501008700001801023700002301041856004501064 2018 d00aA Continuous a-Stratification Index for Item Exposure Control in Computerized Adaptive Testing0 aContinuous aStratification Index for Item Exposure Control in Co a523-5370 v423 aThe method of a-stratification aims to reduce item overexposure in computerized adaptive testing, as items that are administered at very high rates may threaten the validity of test scores. In existing methods of a-stratification, the item bank is partitioned into a fixed number of nonoverlapping strata according to the items’a, or discrimination, parameters. This article introduces a continuous a-stratification index which incorporates exposure control into the item selection index itself and thus eliminates the need for fixed discrete strata. The new continuous a-stratification index is compared with existing stratification methods via simulation studies in terms of ability estimation bias, mean squared error, and control of item exposure rates.1 aHuebner, Alan1 aWang, Chun1 aDaly, Bridget1 aPinkelman, Colleen uhttps://doi.org/10.1177/014662161875828901674nas a2200157 4500008003900000245014600039210006900185300001200254490000700266520111500273100001801388700001701406700001301423700001701436856006301453 2018 d00aEvaluation of a New Method for Providing Full Review Opportunities in Computerized Adaptive Testing—Computerized Adaptive Testing With Salt0 aEvaluation of a New Method for Providing Full Review Opportuniti a582-5940 v553 aAbstract Allowing item review in computerized adaptive testing (CAT) is getting more attention in the educational measurement field as more and more testing programs adopt CAT. The research literature has shown that allowing item review in an educational test could result in more accurate estimates of examinees’ abilities. The practice of item review in CAT, however, is hindered by the potential danger of test-manipulation strategies. To provide review opportunities to examinees while minimizing the effect of test-manipulation strategies, researchers have proposed different algorithms to implement CAT with restricted revision options. In this article, we propose and evaluate a new method that implements CAT without any restriction on item review. In particular, we evaluate the new method in terms of the accuracy on ability estimates and the robustness against test-manipulation strategies. This study shows that the newly proposed method is promising in a win-win situation: examinees have full freedom to review and change answers, and the impacts of test-manipulation strategies are undermined.1 aCui, Zhongmin1 aLiu, Chunyan1 aHe, Yong1 aChen, Hanwei uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1219300515nas a2200133 4500008003900000245012900039210006900168300000900237490000600246100001800252700002700270700002400297856006000321 2018 d00aFactors Affecting the Classification Accuracy and Average Length of a Variable-Length Cognitive Diagnostic Computerized Test0 aFactors Affecting the Classification Accuracy and Average Length a1-140 v61 aHuebner, Alan1 aFinkelman, Matthew, D.1 aWeissman, Alexander uhttp://iacat.org/jcat/index.php/jcat/article/view/55/3000336nas a2200097 4500008004500000245006000045210005900105490000700164100002100171856004600192 2018 Engldsh 00aFrom Simulation to Implementation: Two CAT Case Studies0 aFrom Simulation to Implementation Two CAT Case Studies0 v231 aBarnard, John, J uhttp://pareonline.net/getvn.asp?v=23&n=1401066nas a2200121 4500008003900000245006100039210005900100300001200159490000700171520070300178100001800881856004500899 2018 d00aA Hybrid Strategy to Construct Multistage Adaptive Tests0 aHybrid Strategy to Construct Multistage Adaptive Tests a630-6430 v423 aHow to effectively construct multistage adaptive test (MST) panels is a topic that has spurred recent advances. The most commonly used approaches for MST assembly use one of two strategies: bottom-up and top-down. The bottom-up approach splits the whole test into several modules, and each module is built first, then all modules are compiled to obtain the whole test, while the top-down approach follows the opposite direction. Both methods have their pros and cons, and sometimes neither is convenient for practitioners. This study provides an innovative hybrid strategy to build optimal MST panels efficiently most of the time. Empirical data and results by using this strategy will be provided.1 aXiong, Xinhui uhttps://doi.org/10.1177/014662161876273900444nas a2200145 4500008004500000245005100045210005100096260001200147300001000159490000600169100002200175700001800197700002300215856006000238 2018 Engldsh 00aImplementing Three CATs Within Eighteen Months0 aImplementing Three CATs Within Eighteen Months c09/2018 a38-550 v61 aSpoden, Christian1 aFrey, Andreas1 aBernhardt, Raphael uhttp://iacat.org/jcat/index.php/jcat/article/view/70/3301331nas a2200121 4500008003900000245010900039210006900148300002100217520088900238100001801127700001901145856004501164 2018 d00aItem Selection Criteria With Practical Constraints in Cognitive Diagnostic Computerized Adaptive Testing0 aItem Selection Criteria With Practical Constraints in Cognitive  a00131644187906343 aFor item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP\_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP\_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.1 aLin, Chuan-Ju1 aChang, Hua-Hua uhttps://doi.org/10.1177/001316441879063401840nas a2200157 4500008003900000245010800039210006900147300001200216490000700228520134100235100001501576700001601591700001301607700001701620856004501637 2018 d00aItem Selection Methods in Multidimensional Computerized Adaptive Testing With Polytomously Scored Items0 aItem Selection Methods in Multidimensional Computerized Adaptive a677-6940 v423 aMultidimensional computerized adaptive testing (MCAT) has been developed over the past decades, and most of them can only deal with dichotomously scored items. However, polytomously scored items have been broadly used in a variety of tests for their advantages of providing more information and testing complicated abilities and skills. The purpose of this study is to discuss the item selection algorithms used in MCAT with polytomously scored items (PMCAT). Several promising item selection algorithms used in MCAT are extended to PMCAT, and two new item selection methods are proposed to improve the existing selection strategies. Two simulation studies are conducted to demonstrate the feasibility of the extended and proposed methods. The simulation results show that most of the extended item selection methods for PMCAT are feasible and the new proposed item selection methods perform well. Combined with the security of the pool, when two dimensions are considered (Study 1), the proposed modified continuous entropy method (MCEM) is the ideal of all in that it gains the lowest item exposure rate and has a relatively high accuracy. As for high dimensions (Study 2), results show that mutual information (MUI) and MCEM keep relatively high estimation accuracy, and the item exposure rates decrease as the correlation increases.1 aTu, Dongbo1 aHan, Yuting1 aCai, Yan1 aGao, Xuliang uhttps://doi.org/10.1177/014662161876274801532nas a2200169 4500008003900000245007100039210006900110300001200179490000700191520103000198100001601228700001801244700001801262700001801280700001901298856004501317 2018 d00aLatent Class Analysis of Recurrent Events in Problem-Solving Items0 aLatent Class Analysis of Recurrent Events in ProblemSolving Item a478-4980 v423 aComputer-based assessment of complex problem-solving abilities is becoming more and more popular. In such an assessment, the entire problem-solving process of an examinee is recorded, providing detailed information about the individual, such as behavioral patterns, speed, and learning trajectory. The problem-solving processes are recorded in a computer log file which is a time-stamped documentation of events related to task completion. As opposed to cross-sectional response data from traditional tests, process data in log files are massive and irregularly structured, calling for effective exploratory data analysis methods. Motivated by a specific complex problem-solving item “Climate Control” in the 2012 Programme for International Student Assessment, the authors propose a latent class analysis approach to analyzing the events occurred in the problem-solving processes. The exploratory latent class analysis yields meaningful latent classes. Simulation studies are conducted to evaluate the proposed approach.1 aXu, Haochen1 aFang, Guanhua1 aChen, Yunxiao1 aLiu, Jingchen1 aYing, Zhiliang uhttps://doi.org/10.1177/014662161774832500564nas a2200145 4500008003900000245008100039210006900120100002400189700002200213700001600235700001900251700002300270700002500293856010000318 2018 d00aMeasuring patient-reported outcomes adaptively: Multidimensionality matters!0 aMeasuring patientreported outcomes adaptively Multidimensionalit1 aPaap, Muirne, C. S.1 aKroeze, Karel, A.1 aGlas, C A W1 aTerwee, C., B.1 avan der Palen, Job1 aVeldkamp, Bernard, P uhttp://www.iacat.org/measuring-patient-reported-outcomes-adaptively-multidimensionality-matters01848nas a2200145 4500008003900000245011000039210006900149300001200218490000700230520135600237100001801593700001301611700001501624856006301639 2018 d00aOn-the-Fly Constraint-Controlled Assembly Methods for Multistage Adaptive Testing for Cognitive Diagnosis0 aOntheFly ConstraintControlled Assembly Methods for Multistage Ad a595-6130 v553 aAbstract This study applied the mode of on-the-fly assembled multistage adaptive testing to cognitive diagnosis (CD-OMST). Several and several module assembly methods for CD-OMST were proposed and compared in terms of measurement precision, test security, and constrain management. The module assembly methods in the study included the maximum priority index method (MPI), the revised maximum priority index (RMPI), the weighted deviation model (WDM), and the two revised Monte Carlo methods (R1-MC, R2-MC). Simulation results showed that on the whole the CD-OMST performs well in that it not only has acceptable attribute pattern correct classification rates but also satisfies both statistical and nonstatistical constraints; the RMPI method was generally better than the MPI method, the R2-MC method was generally better than the R1-MC method, and the two revised Monte Carlo methods performed best in terms of test security and constraint management, whereas the RMPI and WDM methods worked best in terms of measurement precision. The study is not only expected to provide information about how to combine MST and CD using an on-the-fly method and how do these assembled methods in CD-OMST perform relative to each other but also offer guidance for practitioners to assemble modules in CD-OMST with both statistical and nonstatistical constraints.1 aLiu, Shuchang1 aCai, Yan1 aTu, Dongbo uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1219400949nas a2200169 4500008003900000022001400039245011500053210006900168260000800237300001600245490000700261520040300268100001700671700002400688700002100712856004600733 2018 d a1573-264900aSome recommendations for developing multidimensional computerized adaptive tests for patient-reported outcomes0 aSome recommendations for developing multidimensional computerize cApr a1055–10630 v273 aMultidimensional item response theory and computerized adaptive testing (CAT) are increasingly used in mental health, quality of life (QoL), and patient-reported outcome measurement. Although multidimensional assessment techniques hold promises, they are more challenging in their application than unidimensional ones. The authors comment on minimal standards when developing multidimensional CATs.1 aSmits, Niels1 aPaap, Muirne, C. S.1 aBöhnke, Jan, R. uhttps://doi.org/10.1007/s11136-018-1821-801396nas a2200133 4500008003900000245007900039210006900118300001200187490000700199520096200206100001401168700001701182856006301199 2018 d00aA Top-Down Approach to Designing the Computerized Adaptive Multistage Test0 aTopDown Approach to Designing the Computerized Adaptive Multista a243-2630 v553 aAbstract The top-down approach to designing a multistage test is relatively understudied in the literature and underused in research and practice. This study introduced a route-based top-down design approach that directly sets design parameters at the test level and utilizes the advanced automated test assembly algorithm seeking global optimality. The design process in this approach consists of five sub-processes: (1) route mapping, (2) setting objectives, (3) setting constraints, (4) routing error control, and (5) test assembly. Results from a simulation study confirmed that the assembly, measurement and routing results of the top-down design eclipsed those of the bottom-up design. Additionally, the top-down design approach provided unique insights into design decisions that could be used to refine the test. Regardless of these advantages, it is recommended applying both top-down and bottom-up approaches in a complementary manner in practice.1 aLuo, Xiao1 aKim, Doyoung uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1217401501nas a2200133 4500008003900000245010600039210006900145300001000214490000700224520105500231100002001286700001601306856004501322 2018 d00aUsing Automatic Item Generation to Create Solutions and Rationales for Computerized Formative Testing0 aUsing Automatic Item Generation to Create Solutions and Rational a42-570 v423 aComputerized testing provides many benefits to support formative assessment. However, the advent of computerized formative testing has also raised formidable new challenges, particularly in the area of item development. Large numbers of diverse, high-quality test items are required because items are continuously administered to students. Hence, hundreds of items are needed to develop the banks necessary for computerized formative testing. One promising approach that may be used to address this test development challenge is automatic item generation. Automatic item generation is a relatively new but rapidly evolving research area where cognitive and psychometric modeling practices are used to produce items with the aid of computer technology. The purpose of this study is to describe a new method for generating both the items and the rationales required to solve the items to produce the required feedback for computerized formative testing. The method for rationale generation is demonstrated and evaluated in the medical education domain.1 aGierl, Mark, J.1 aLai, Hollis uhttps://doi.org/10.1177/014662161772678801986nas a2200133 4500008003900000245006600039210006400105300001200169490000700181520157400188100002501762700002001787856004501807 2018 d00aWhat Information Works Best?: A Comparison of Routing Methods0 aWhat Information Works Best A Comparison of Routing Methods a499-5150 v423 aThere are many item selection methods proposed for computerized adaptive testing (CAT) applications. However, not all of them have been used in computerized multistage testing (ca-MST). This study uses some item selection methods as a routing method in ca-MST framework. These are maximum Fisher information (MFI), maximum likelihood weighted information (MLWI), maximum posterior weighted information (MPWI), Kullback–Leibler (KL), and posterior Kullback–Leibler (KLP). The main purpose of this study is to examine the performance of these methods when they are used as a routing method in ca-MST applications. These five information methods under four ca-MST panel designs and two test lengths (30 items and 60 items) were tested using the parameters of a real item bank. Results were evaluated with overall findings (mean bias, root mean square error, correlation between true and estimated thetas, and module exposure rates) and conditional findings (conditional absolute bias, standard error of measurement, and root mean square error). It was found that test length affected the outcomes much more than other study conditions. Under 30-item conditions, 1-3 designs outperformed other panel designs. Under 60-item conditions, 1-3-3 designs were better than other panel designs. Each routing method performed well under particular conditions; there was no clear best method in the studied conditions. The recommendations for routing methods in any particular condition were provided for researchers and practitioners as well as the limitations of these results.1 aSari, Halil, Ibrahim1 aRaborn, Anthony uhttps://doi.org/10.1177/014662161775299001969nas a2200145 4500008004100000245008700041210006900128260005500197520137700252653003201629653001801661653002401679100001701703856010301720 2017 eng d00aAdapting Linear Models for Optimal Test Design to More Complex Test Specifications0 aAdapting Linear Models for Optimal Test Design to More Complex T aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Combinatorial optimization (CO) has proven to be a very helpful approach for addressing test assembly issues and for providing solutions. Furthermore, CO has been applied for several test designs, including: (1) for the development of linear test forms; (2) for computerized adaptive testing and; (3) for multistage testing. In his seminal work, van der Linden (2006) laid out the basis for using linear models for simultaneously assembling exams and item pools in a variety of conditions: (1) for single tests and multiple tests; (2) with item sets, etc. However, for some testing programs, the number and complexity of test specifications can grow rapidly. Consequently, the mathematical representation of the test assembly problem goes beyond most approaches reported either in van der Linden’s book or in the majority of other publications related to test assembly. In this presentation, we extend van der Linden’s framework by including the concept of blocks for test specifications. We modify the usual mathematical notation of a test assembly problem by including this concept and we show how it can be applied to various test designs. Finally, we will demonstrate an implementation of this approach in a stand-alone software, called the ATASolver.

Session Video

10aComplex Test Specifications10aLinear Models10aOptimal Test Design1 aMorin, Maxim uhttp://www.iacat.org/adapting-linear-models-optimal-test-design-more-complex-test-specifications-005518nas a2200193 4500008004100000245009000041210006900131260005500200520480200255653002305057653001905080653002105099653002605120100002205146700002005168700001605188700001905204856010105223 2017 eng d00aAdaptive Item and Feedback Selection in Personalized Learning with a Network Approach0 aAdaptive Item and Feedback Selection in Personalized Learning wi aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Personalized learning is a term used to describe educational systems that adapt student-specific curriculum sequencing, pacing, and presentation based on their unique backgrounds, knowledge, preferences, interests, and learning goals. (Chen, 2008; Netcoh, 2016). The technological approach to personalized learning provides data-driven models to incorporate these adaptations automatically. Examples of applications include online learning systems, educational games, and revision-aid systems. In this study we introduce Bayesian networks as a methodology to implement an adaptive framework within a personalized learning environment. Existing ideas from Computerized Adaptive Testing (CAT) with Item Response Theory (IRT), where choices about content provision are based on maximizing information, are related to the goals of personalized learning environments. Personalized learning entails other goals besides efficient ability estimation by maximizing information, such as an adaptive configuration of preferences and feedback to the student. These considerations will be discussed and their application in networks will be illustrated.

Adaptivity in Personalized Learning.In standard CAT’s there is a focus on selecting items that provide maximum information about the ability of an individual at a certain point in time (Van der Linden & Glas, 2000). When learning is the main goal of testing, alternative adaptive item selection methods were explored by Eggen (2012). The adaptive choices made in personalized learning applications require additional adaptivity with respect to the following aspects; the moment of feedback, the kind of feedback, and the possibility for students to actively influence the learning process.

Bayesian Networks and Personalized Learning.Personalized learning aims at constructing a framework to incorporate all the aspects mentioned above. Therefore, the goal of this framework is not only to focus on retrieving ability estimates by choosing items on maximum information, but also to construct a framework that allows for these other factors to play a role. Plajner and Vomlel (2016) have already applied Bayesian Networks to adaptive testing, selecting items with help of entropy reduction. Almond et al. (2015) provide a reference work on Bayesian Networks in Educational Assessment. Both acknowledge the potential of the method in terms of features such as modularity options to build finer-grained models. IRT does not allow to model sub-skills very easily and to gather information on fine-grained level, due to its dependency on the assumption of generally one underlying trait. The local independence assumption in IRT implies being interested in mainly the student’s overall ability on the subject of interest. When the goal is to improve student’s learning, we are not just interested in efficiently coming to their test score on a global subject. One wants a model that is able to map educational problems and talents in detail over the whole educational program, while allowing for dependency between items. The moment in time can influence topics to be better mastered than others, and this is exactly what we can to get out of a model. The possibility to model flexible structures, estimate abilities on a very detailed level for sub-skills and to easily incorporate other variables such as feedback in Bayesian Networks makes it a very promising method for making adaptive choices in personalized learning. It is shown in this research how item and feedback selection can be performed with help of the promising Bayesian Networks. A student involvement possibility is also introduced and evaluated.

References

Almond, R. G., Mislevy, R. J., Steinberg, L. S., Yan, D., & Williamson, D. M. (2015). Bayesian Networks in Educational Assessment. Test. New York: Springer Science+Business Media. http://doi.org/10.1007/978-0-387-98138-3

Eggen, T.J.H.M. (2012) Computerized Adaptive Testing Item Selection in Computerized Adaptive Learning Systems. In: Eggen. TJHM & Veldkamp, BP.. (Eds). Psychometrics in Practice at RCEC. Enschede: RCEC

Netcoh, S. (2016, March). “What Do You Mean by ‘Personalized Learning?’. Croscutting Conversations in Education – Research, Reflections & Practice. Blogpost.

Plajner, M., & Vomlel, J. (2016). Student Skill Models in Adaptive Testing. In Proceedings of the Eighth International Conference on Probabilistic Graphical Models (pp. 403-414).

Van der Linden, W. J., & Glas, C. A. (2000). Computerized adaptive testing: Theory and practice. Dordrecht: Kluwer Academic Publishers.

Session Video

10afeedback selection10aitem selection10anetwork approach10apersonalized learning1 avan Buuren, Nikky1 aStraat, Hendrik1 aEggen, Theo1 aFox, Jean-Paul uhttp://www.iacat.org/adaptive-item-and-feedback-selection-personalized-learning-network-approach01675nas a2200145 4500008004100000245004800041210004800089260005500137520120400192653000801396653002101404653001401425100002401439856006601463 2017 eng d00aAdaptivity in a Diagnostic Educational Test0 aAdaptivity in a Diagnostic Educational Test aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

During the past five years a diagnostic educational test for three subjects (writing Dutch, writing English and math) has been developed in the Netherlands. The test informs students and their teachers about the students’ strengths and weaknesses in such a manner that the learning process can be adjusted to their personal needs. It is a computer-based assessment for students in five different educational tracks midway secondary education that can yield diagnoses of many sub-skills. One of the main challenges at the outset of the development was to devise a way to deliver many diagnoses within a reasonably testing time. The answer to this challenge was to make the DET adaptive.

In this presentation we will discuss first how the adaptivity is shaped towards the purpose of the Diagnostic Educational Test. The adaptive design, particularly working with item blocks, will be discussed as well as the implemented adaptive rules. We will also show a simulation of different adaptive paths of students and some empirical information on the paths students took through the test

Session Video

10aCAT10aDiagnostic tests10aEducation1 aSchouwstra, Sanneke uhttp://www.iacat.org/adaptivity-diagnostic-educational-test-002709nas a2200157 4500008004100000245007100041210006900112260005500181520213800236653000802374653002002382653001402402100002002416700002602436856008902462 2017 eng d00aAnalysis of CAT Precision Depending on Parameters of the Item Pool0 aAnalysis of CAT Precision Depending on Parameters of the Item Po aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The purpose of this research project is to analyze the measurement precision of a latent variable depending on parameters of the item pool. The influence of the following factors is analyzed:

Factor A – range of variation of items in the pool. This factor varies on three levels with the following ranges in logits: a1 – [-3.0; +3.0], a2 - [-4.0; +4.0], a3 - [-5.0; +5.0].

Factor B – number of items in the pool. The factor varies on six levels with the following number of items for every factor: b1 - 128, b2 - 256, b3 – 512, b4 - 1024, b5 – 2048, b6 – 4096. The items are evenly distributed in each of the variation ranges.

Factor C – examinees’ proficiency varies at 30 levels (c1, c2, …, c30), which are evenly distributed in the range [-3.0; +3.0] logit.

The investigation was based on a simulation experiment within the framework of the theory of latent variables.

Response Y is the precision of measurement of examinees’ proficiency, which is calculated as the difference between the true levels of examinees’ proficiency and estimates obtained by means of adaptive testing. Three factor ANOVA was used for data processing.

The following results were obtained:

1. Factor A is significant. Ceteris paribus, the greater the range of variation of items in the pool, the higher the estimation precision is.

2. Factor B is significant. Ceteris paribus, the greater the number of items in the pool, the higher the estimation precision is.

3. Factor C is statistically insignificant at level α = .05. It means that the precision of estimation of examinees’ proficiency is the same within the range of their variation.

4. The only significant interaction among all interactions is AB. The significance of this interaction is explained by the fact that increasing the number of items in the pool decreases the effect of the range of variation of items in the pool. 

Session Video

10aCAT10aItem parameters10aPrecision1 aMaslak, Anatoly1 aPozdniakov, Stanislav uhttps://drive.google.com/file/d/1Bwe58kOQRgCSbB8x6OdZTDK4OIm3LQI3/view?usp=drive_web01999nas a2200133 4500008003900000245011600039210006900155300001200224490000700236520154300243100001901786700001501805856004501820 2017 d00aApplication of Binary Searching for Item Exposure Control in Cognitive Diagnostic Computerized Adaptive Testing0 aApplication of Binary Searching for Item Exposure Control in Cog a561-5760 v413 aCognitive diagnosis has emerged as a new generation of testing theory for educational assessment after the item response theory (IRT). One distinct feature of cognitive diagnostic models (CDMs) is that they assume the latent trait to be discrete instead of continuous as in IRT. From this perspective, cognitive diagnosis bears a close resemblance to searching problems in computer science and, similarly, item selection problem in cognitive diagnostic computerized adaptive testing (CD-CAT) can be considered as a dynamic searching problem. Previously, item selection algorithms in CD-CAT were developed from information indices in information science and attempted to achieve a balance among several objectives by assigning different weights. As a result, they suffered from low efficiency from a tug-of-war competition among multiple goals in item selection and, at the same time, put an undue responsibility of assigning the weights for these goals by trial and error on users. Based on the searching problem perspective on CD-CAT, this article adapts the binary searching algorithm, one of the most well-known searching algorithms in searching problems, to item selection in CD-CAT. The two new methods, the stratified dynamic binary searching (SDBS) algorithm for fixed-length CD-CAT and the dynamic binary searching (DBS) algorithm for variable-length CD-CAT, can achieve multiple goals without any of the aforementioned issues. The simulation studies indicate their performances are comparable or superior to the previous methods.1 aZheng, Chanjin1 aWang, Chun uhttps://doi.org/10.1177/014662161770750901537nas a2200181 4500008003900000245006700039210006500106300001200171490000700183520099700190100002001187700001801207700002101225700002201246700002201268700002001290856004501310 2017 d00aATS-PD: An Adaptive Testing System for Psychological Disorders0 aATSPD An Adaptive Testing System for Psychological Disorders a792-8150 v773 aThe clinical assessment of mental disorders can be a time-consuming and error-prone procedure, consisting of a sequence of diagnostic hypothesis formulation and testing aimed at restricting the set of plausible diagnoses for the patient. In this article, we propose a novel computerized system for the adaptive testing of psychological disorders. The proposed system combines a mathematical representation of psychological disorders, known as the “formal psychological assessment,” with an algorithm designed for the adaptive assessment of an individual’s knowledge. The assessment algorithm is extended and adapted to the new application domain. Testing the system on a real sample of 4,324 healthy individuals, screened for obsessive-compulsive disorder, we demonstrate the system’s ability to support clinical testing, both by identifying the correct critical areas for each individual and by reducing the number of posed questions with respect to a standard written questionnaire.1 aDonadello, Ivan1 aSpoto, Andrea1 aSambo, Francesco1 aBadaloni, Silvana1 aGranziol, Umberto1 aVidotto, Giulio uhttps://doi.org/10.1177/001316441665218802100nas a2200181 4500008004100000245004600041210004600087260005500133520153800188653002501726653000801751100002801759700001901787700001301806700002001819700001301839856006601852 2017 eng d00aBayesian Perspectives on Adaptive Testing0 aBayesian Perspectives on Adaptive Testing aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Although adaptive testing is usually treated from the perspective of maximum-likelihood parameter estimation and maximum-informaton item selection, a Bayesian pespective is more natural, statistically efficient, and computationally tractable. This observation not only holds for the core process of ability estimation but includes such processes as item calibration, and real-time monitoring of item security as well. Key elements of the approach are parametric modeling of each relevant process, updating of the parameter estimates after the arrival of each new response, and optimal design of the next step.

The purpose of the symposium is to illustrates the role of Bayesian statistics in this approach. The first presentation discusses a basic Bayesian algorithm for the sequential update of any parameter in adaptive testing and illustrates the idea of Bayesian optimal design for the two processes of ability estimation and online item calibration. The second presentation generalizes the ideas to the case of 62 IACAT 2017 ABSTRACTS BOOKLET adaptive testing with polytomous items. The third presentation uses the fundamental Bayesian idea of sampling from updated posterior predictive distributions (“multiple imputations”) to deal with the problem of scoring incomplete adaptive tests.

Session Video 1

Session Video 2

 

10aBayesian Perspective10aCAT1 avan der Linden, Wim, J.1 aJiang, Bingnan1 aRen, Hao1 aChoi, Seung, W.1 aDiao, Qi uhttp://www.iacat.org/bayesian-perspectives-adaptive-testing-003113nas a2200145 4500008004100000245004900041210004500090260005500135520264100190653002802831653000802859653002102867100001702888856006202905 2017 eng d00aIs CAT Suitable for Automated Speaking Test?0 aCAT Suitable for Automated Speaking Test aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

We have developed automated scoring system of Japanese speaking proficiency, namely SJ-CAT (Speaking Japanese Computerized Adaptive Test), which is operational for last few months. One of the unique features of the test is an adaptive test base on polytomous IRT.

SJ-CAT consists of two sections; Section 1 has sentence reading aloud tasks and a multiple choicereading tasks and Section 2 has sentence generation tasks and an open answer tasks. In reading aloud tasks, a test taker reads a phoneme-balanced sentence on the screen after listening to a model reading. In a multiple choice-reading task, a test taker sees a picture and reads aloud one sentence among three sentences on the screen, which describe the scene most appropriately. In a sentence generation task, a test taker sees a picture or watches a video clip and describes the scene with his/her own words for about ten seconds. In an open answer tasks, the test taker expresses one’s support for or opposition to e.g., a nuclear power generation with reasons for about 30 seconds.

In the course of the development of the test, we found many unexpected and unique characteristics of speaking CAT, which are not found in usual CATs with multiple choices. In this presentation, we will discuss some of such factors that are not previously noticed in our previous project of developing dichotomous J-CAT (Japanese Computerized Adaptive Test), which consists of vocabulary, grammar, reading, and listening. Firstly, we will claim that distribution of item difficulty parameters depends on the types of items. An item pool with unrestricted types of items such as open questions is difficult to achieve ideal distributions, either normal distribution or uniform distribution. Secondly, contrary to our expectations, open questions are not necessarily more difficult to operate in automated scoring system than more restricted questions such as sentence reading, as long as if one can set up suitable algorithm for open question scoring. Thirdly, we will show that the speed of convergence of standard deviation of posterior distribution, or standard error of theta parameter in polytomous IRT used for SJCAT is faster than dichotomous IRT used in J-CAT. Fourthly, we will discuss problems in equation of items in SJ-CAT, and suggest introducing deep learning with reinforcement learning instead of equation. And finally, we will discuss the issues of operation of SJ-CAT on the web, including speed of scoring, operation costs, security among others.

Session Video

10aAutomated Speaking Test10aCAT10alanguage testing1 aImai, Shingo uhttp://www.iacat.org/cat-suitable-automated-speaking-test05044nas a2200145 4500008004100000245008900041210006900130260005500199520447200254653000804726653002904734100001804763700001504781856010204796 2017 eng d00aComparison of Pretest Item Calibration Methods in a Computerized Adaptive Test (CAT)0 aComparison of Pretest Item Calibration Methods in a Computerized aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Calibration methods for pretest items in a computerized adaptive test (CAT) are not a new area of research inquiry. After decades of research on CAT, the fixed item parameter calibration (FIPC) method has been widely accepted and used by practitioners to address two CAT calibration issues: (a) a restricted ability range each item is exposed to, and (b) a sparse response data matrix. In FIPC, the parameters of the operational items are fixed at their original values, and multiple expectation maximization (EM) cycles are used to estimate parameters of the pretest items with prior ability distribution being updated multiple times (Ban, Hanson, Wang, Yi, & Harris, 2001; Kang & Peterson, 2009; Pommerich & Segall, 2003).

Another calibration method is the fixed person parameter calibration (FPPC) method proposed by Stocking (1988) as “Method A.” Under this approach, candidates’ ability estimates are fixed in the calibration of pretest items and they define the scale on which the parameter estimates are reported. The logic of FPPC is suitable for CAT applications because the person parameters are estimated based on operational items and available for pretest item calibration. In Stocking (1988), the FPPC was evaluated using the LOGIST computer program developed by Wood, Wingersky, and Lord (1976). He reported that “Method A” produced larger root mean square errors (RMSEs) in the middle ability range than “Method B,” which required the use of anchor items (administered non-adaptively) and linking steps to attempt to correct for the potential scale drift due to the use of imperfect ability estimates.

Since then, new commercial software tools such as BILOG-MG and flexMIRT (Cai, 2013) have been developed to handle the FPPC method with different implementations (e.g., the MH-RM algorithm with flexMIRT). The performance of the FPPC method with those new software tools, however, has rarely been researched in the literature.

In our study, we evaluated the performance of two pretest item calibration methods using flexMIRT, the new software tool. The FIPC and FPPC are compared under various CAT settings. Each simulated exam contains 75% operational items and 25% pretest items, and real item parameters are used to generate the CAT data. This study also addresses the lack of guidelines in existing CAT item calibration literature regarding population ability shift and exam length (more accurate theta estimates are expected in longer exams). Thus, this study also investigates the following four factors and their impact on parameter estimation accuracy, including: (1) candidate population changes (3 ability distributions); (2) exam length (20: 15 OP + 5 PT, 40: 30 OP + 10 PT, and 60: 45 OP + 15 PT); (3) data model fit (3PL and 3PL with fixed C), and (4) pretest item calibration sample sizes (300, 500, and 1000). This study’s findings will fill the gap in this area of research and thus provide new information on which practitioners can base their decisions when selecting a pretest calibration method for their exams.

References

Ban, J. C., Hanson, B. A., Wang, T., Yi, Q., & Harris, D. J. (2001). A comparative study of online pretest item—Calibration/scaling methods in computerized adaptive testing. Journal of Educational Measurement, 38(3), 191–212.

Cai, L. (2013). flexMIRT® Flexible Multilevel Multidimensional Item Analysis and Test Scoring (Version 2) [Computer software]. Chapel Hill, NC: Vector Psychometric Group.

Kang, T., & Petersen, N. S. (2009). Linking item parameters to a base scale (Research Report No. 2009– 2). Iowa City, IA: ACT.

Pommerich, M., & Segall, D.O. (2003, April). Calibrating CAT pools and online pretest items using marginal maximum likelihood methods. Paper presented at the annual meeting of the National Council on Measurement in Education, Chicago, IL.

Stocking, M. L. (1988). Scale drift in online calibration (Research Report No. 88–28). Princeton, NJ: Educational Testing Service.

Wood, R. L., Wingersky, M. S., & Lord, F. M. (1976). LOGIST: A computer program for estimating examinee ability and item characteristic curve parameters (RM76-6) [Computer program]. Princeton, NJ: Educational Testing Service.

Session Video

10aCAT10aPretest Item Calibration1 aMeng, Huijuan1 aHan, Chris uhttp://www.iacat.org/comparison-pretest-item-calibration-methods-computerized-adaptive-test-cat-001722nas a2200133 4500008004100000245009200041210006900133260005500202520120200257653000801459653001601467100001801483856008701501 2017 eng d00aA Comparison of Three Empirical Reliability Estimates for Computerized Adaptive Testing0 aComparison of Three Empirical Reliability Estimates for Computer aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Reliability estimates in Computerized Adaptive Testing (CAT) are derived from estimated thetas and standard error of estimated thetas. In practical, the observed standard error (OSE) of estimated thetas can be estimated by test information function for each examinee with respect to Item response theory (IRT). Unlike classical test theory (CTT), OSEs in IRT are conditional values given each estimated thetas so that those values should be marginalized to consider test reliability. Arithmetic mean, Harmonic mean, and Jensen equality were applied to marginalize OSEs to estimate CAT reliability. Based on different marginalization method, three empirical CAT reliabilities were compared with true reliabilities. Results showed that three empirical CAT reliabilities were underestimated compared to true reliability in short test length (< 40), whereas the magnitude of CAT reliabilities was followed by Jensen equality, Harmonic mean, and Arithmetic mean in long test length (> 40). Specifically, Jensen equality overestimated true reliability across all conditions in long test length (>50).

Session Video 

10aCAT10aReliability1 aSeo, Dong, Gi uhttps://drive.google.com/file/d/1gXgH-epPIWJiE0LxMHGiCAxZZAwy4dAH/view?usp=sharing02166nas a2200157 4500008003900000245007600039210006900115300001200184490000700196520167900203100002001882700001801902700001801920700002501938856004501963 2017 d00aIs a Computerized Adaptive Test More Motivating Than a Fixed-Item Test?0 aComputerized Adaptive Test More Motivating Than a FixedItem Test a495-5110 v413 aComputer adaptive tests provide important measurement advantages over traditional fixed-item tests, but research on the psychological reactions of test takers to adaptive tests is lacking. In particular, it has been suggested that test-taker engagement, and possibly test performance as a consequence, could benefit from the control that adaptive tests have on the number of test items examinees answer correctly. However, previous research on this issue found little support for this possibility. This study expands on previous research by examining this issue in the context of a mathematical ability assessment and by considering the possible effect of immediate feedback of response correctness on test engagement, test anxiety, time on task, and test performance. Middle school students completed a mathematics assessment under one of three test type conditions (fixed, adaptive, or easier adaptive) and either with or without immediate feedback about the correctness of responses. Results showed little evidence for test type effects. The easier adaptive test resulted in higher engagement and lower anxiety than either the adaptive or fixed-item tests; however, no significant differences in performance were found across test types, although performance was significantly higher across all test types when students received immediate feedback. In addition, these effects were not related to ability level, as measured by the state assessment achievement levels. The possibility that test experiences in adaptive tests may not in practice be significantly different than in fixed-item tests is raised and discussed to explain the results of this and previous studies.1 aLing, Guangming1 aAttali, Yigal1 aFinn, Bridgid1 aStone, Elizabeth, A. uhttps://doi.org/10.1177/014662161770755604446nas a2200157 4500008004100000245009700041210006900138260005500207520381800262653001104080653002804091100002004119700001804139700002104157856011004178 2017 eng d00aComputerized Adaptive Testing for Cognitive Diagnosis in Classroom: A Nonparametric Approach0 aComputerized Adaptive Testing for Cognitive Diagnosis in Classro aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

In the past decade, CDMs of educational test performance have received increasing attention among educational researchers (for details, see Fu & Li, 2007, and Rupp, Templin, & Henson, 2010). CDMs of educational test performance decompose the ability domain of a given test into specific skills, called attributes, each of which an examinee may or may not have mastered. The resulting attribute profile documents the individual’s strengths and weaknesses within the ability domain. The Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) has been suggested by researchers as a diagnostic tool for assessment and evaluation (e.g., Cheng & Chang, 2007; Cheng, 2009; Liu, You, Wang, Ding, & Chang, 2013; Tatsuoka & Tatsuoka, 1997). While model-based CD-CAT is relatively well-researched in the context of large-scale assessments, this type of system has not received the same degree of development in small-scale settings, where it would be most useful. The main challenge is that the statistical estimation techniques successfully applied to the parametric CD-CAT require large samples to guarantee the reliable calibration of item parameters and accurate estimation of examinees’ attribute profiles. In response to the challenge, a nonparametric approach that does not require any parameter calibration, and thus can be used in small educational programs, is proposed. The proposed nonparametric CD-CAT relies on the same principle as the regular CAT algorithm, but uses the nonparametric classification method (Chiu & Douglas, 2013) to assess and update the student’s ability state while the test proceeds. Based on a student’s initial responses, 2 a neighborhood of candidate proficiency classes is identified, and items not characteristic of the chosen proficiency classes are precluded from being chosen next. The response to the next item then allows for an update of the skill profile, and the set of possible proficiency classes is further narrowed. In this manner, the nonparametric CD-CAT cycles through item administration and update stages until the most likely proficiency class has been pinpointed. The simulation results show that the proposed method outperformed the compared parametric CD-CAT algorithms and the differences were significant when the item parameter calibration was not optimal.

References

Cheng, Y. (2009). When cognitive diagnosis meets computerized adaptive testing: CD-CAT. Psychometrika, 74, 619-632.

Cheng, Y., & Chang, H. (2007). The modified maximum global discrimination index method for cognitive diagnostic CAT. In D. Weiss (Ed.) Proceedings of the 2007 GMAC Computerized Adaptive Testing Conference.

Chiu, C.-Y., & Douglas, J. A. (2013). A nonparametric approach to cognitive diagnosis by proximity to ideal response patterns. Journal of Classification, 30, 225-250.

Fu, J., & Li, Y. (2007). An integrative review of cognitively diagnostic psychometric models. Paper presented at the Annual Meeting of the National Council on Measurement in Education. Chicago, Illinois.

Liu, H., You, X., Wang, W., Ding, S., & Chang, H. (2013). The development of computerized adaptive testing with cognitive diagnosis for an English achievement test in China. Journal of Classification, 30, 152-172.

Rupp, A. A., & Templin, J. L., & Henson, R. A. (2010). Diagnostic Measurement. Theory, Methods, and Applications. New York: Guilford.

Tatsuoka, K.K., & Tatsuoka, M.M. (1997), Computerized cognitive diagnostic adaptive testing: Effect on remedial instruction as empirical validation. Journal of Educational Measurement, 34, 3–20.

Session Video

10aCD-CAT10anon-parametric approach1 aChang, Yuan-Pei1 aChiu, Chia-Yi1 aTsai, Rung-Ching uhttp://www.iacat.org/computerized-adaptive-testing-cognitive-diagnosis-classroom-nonparametric-approach-001506nas a2200133 4500008004100000245006000041210005900101260005500160520103000215653001501245653002001260100002101280856007101301 2017 eng d00aConcerto 5 Open Source CAT Platform: From Code to Nodes0 aConcerto 5 Open Source CAT Platform From Code to Nodes aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Concerto 5 is the newest version of the Concerto open source R-based Computer-Adaptive Testing platform, which is currently used in educational testing and in clinical trials. In our quest to make CAT accessible to all, the latest version uses flowchart nodes to connect different elements of a test, so that CAT test creation is an intuitive high-level process that does not require writing code.

A test creator might connect an Info Page node, to a Consent Page node, to a CAT node, to a Feedback node. And after uploading their items, their test is done.

This talk will show the new flowchart interface, and demonstrate the creation of a CAT test from scratch in less than 10 minutes.

Concerto 5 also includes a new Polytomous CAT node, so CATs with Likert items can be easily created in the flowchart interface. This node is currently used in depression and anxiety tests in a clinical trial.

Session Video

10aConcerto 510aOpen Source CAT1 aStillwell, David uhttps://drive.google.com/open?id=11eu1KKILQEoK5c-CYO1P1AiJgiQxX0E003452nas a2200157 4500008004100000245008400041210006900125260005500194520283600249653001203085653002503097653002803122100002303150700002003173856010103193 2017 eng d00aConsiderations in Performance Evaluations of Computerized Formative Assessments0 aConsiderations in Performance Evaluations of Computerized Format aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Computerized adaptive instruments have been widely established and used in the context of summative assessments for purposes including licensure, admissions and proficiency testing. The benefits of examinee tailored examinations, which can provide estimates of performance that are more reliable and valid, have in recent years attracted a greater audience (i.e. patient oriented outcomes, test prep, etc.). Formative assessment, which are most widely understood in their implementation as diagnostic tools, have recently started to expand to lesser known areas of computerized testing such as in implementations of instructional designs aiming to maximize examinee learning through targeted practice.

Using a CAT instrument within the framework of evaluating repetitious examinee performances (in such settings as a Quiz Bank practices for example) poses unique challenges not germane to summative assessments. The scale on which item parameters (and subsequently examinee performance estimates such as Maximum Likelihood Estimates) are determined usually do not take change over time under consideration. While vertical scaling features resolve the learning acquisition problem, most content practice engines do not make use of explicit practice windows which could be vertically aligned. Alternatively, the Multidimensional (MIRT)- and Hierarchical Item Response Theory (HIRT) models allow for the specification of random effects associated with change over time in examinees’ skills, but are often complex and require content and usage resources not often observed.

The research submitted for consideration simulated examinees’ repeated variable length Quiz Bank practice in algebra using a 500 1-PL operational item pool. The stability simulations sought to determine with which rolling item interval size ability estimates would provide the most informative insight into the examinees’ learning progression over time. Estimates were evaluated in terms of reduction in estimate uncertainty, bias and RMSD with the true and total item based ability estimates. It was found that rolling item intervals between 20-25 items provided the best reduction of uncertainty around the estimate without compromising the ability to provide informed performance estimates to students. However, while asymptotically intervals of 20-25 items tended to provide adequate estimates of performance, changes over shorter periods of time assessed with shorter quizzes could not be detected as those changes would be suppressed in lieu of the performance based on the full interval considered. Implications for infrastructure (such as recommendation engines, etc.), product and scale development are discussed.

Session video

10aalgebra10aFormative Assessment10aPerformance Evaluations1 aChajewski, Michael1 aHarnisher, John uhttp://www.iacat.org/considerations-performance-evaluations-computerized-formative-assessments-001967nas a2200133 4500008004100000245008000041210006900121260005500190520145700245653002001702653002101722100001901743856007101762 2017 eng d00aConstruction of Gratitude Scale Using Polytomous Item Response Theory Model0 aConstruction of Gratitude Scale Using Polytomous Item Response T aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Various studies have shown that gratitude is essential to increase the happiness and quality of life of every individual. Unfortunately, research on gratitude still received little attention, and there is no standardized measurement for it. Gratitude measurement scale was developed overseas, and has not adapted to the Indonesian culture context. Moreover, the scale development is generally performed with classical theory approach, which has some drawbacks. This research will develop a gratitude scale using polytomous Item Response Theory model (IRT) by applying the Partial Credit Model (PCM).

The pilot study results showed that the gratitude scale (with 44 items) is a reliable measure (α = 0.944) and valid (meet both convergent and discriminant validity requirements). The pilot study results also showed that the gratitude scale satisfies unidimensionality assumptions.

The test results using the PCM model showed that the gratitude scale had a fit model. Of 44 items, there was one item that does not fit, so it was eliminated. Second test results for the remaining 43 items showed that they fit the model, and all items were fit to measure gratitude. Analysis using Differential Item Functioning (DIF) showed four items have a response bias based on gender. Thus, there are 39 items remaining in the scale.

Session Video 

10aGratitude Scale10apolytomous items1 aArbiyah, Nurul uhttps://drive.google.com/open?id=1pHhO4cq2-wh24ht3nBAoXNHv7234_mjH02607nas a2200133 4500008004100000245004800041210004700089260005500136520214600191653002002337653002402357100002102381856007102402 2017 eng d00aDeveloping a CAT: An Integrated Perspective0 aDeveloping a CAT An Integrated Perspective aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Most resources on computerized adaptive testing (CAT) tend to focus on psychometric aspects such as mathematical formulae for item selection or ability estimation. However, development of a CAT assessment requires a holistic view of project management, financials, content development, product launch and branding, and more. This presentation will develop such a holistic view, which serves several purposes, including providing a framework for validity, estimating costs and ROI, and making better decisions regarding the psychometric aspects.

Thompson and Weiss (2011) presented a 5-step model for developing computerized adaptive tests (CATs). This model will be presented and discussed as the core of this holistic framework, then applied to real-life examples. While most CAT research focuses on developing new quantitative algorithms, this presentation is instead intended to help researchers evaluate and select algorithms that are most appropriate for their needs. It is therefore ideal for practitioners that are familiar with the basics of item response theory and CAT, and wish to explore how they might apply these methodologies to improve their assessments.

Steps include:

1. Feasibility, applicability, and planning studies

2. Develop item bank content or utilize existing bank

3. Pretest and calibrate item bank

4. Determine specifications for final CAT

5. Publish live CAT.

So, for example, Step 1 will contain simulation studies which estimate item bank requirements, which then can be used to determine costs of content development, which in turn can be integrated into an estimated project cost timeline. Such information is vital in determining if the CAT should even be developed in the first place.

References

Thompson, N. A., & Weiss, D. J. (2011). A Framework for the Development of Computerized Adaptive Tests. Practical Assessment, Research & Evaluation, 16(1). Retrieved from http://pareonline.net/getvn.asp?v=16&n=1.

Session Video

10aCAT Development10aintegrated approach1 aThompson, Nathan uhttps://drive.google.com/open?id=1Jv8bpH2zkw5TqSMi03e5JJJ98QtXf-Cv01568nas a2200181 4500008003900000245011800039210006900157300001100226490000700237520097700244100001801221700001701239700002501256700001801281700002201299700002001321856004501341 2017 d00aDevelopment of a Computer Adaptive Test for Depression Based on the Dutch-Flemish Version of the PROMIS Item Bank0 aDevelopment of a Computer Adaptive Test for Depression Based on  a79-1050 v403 aWe developed a Dutch-Flemish version of the patient-reported outcomes measurement information system (PROMIS) adult V1.0 item bank for depression as input for computerized adaptive testing (CAT). As item bank, we used the Dutch-Flemish translation of the original PROMIS item bank (28 items) and additionally translated 28 U.S. depression items that failed to make the final U.S. item bank. Through psychometric analysis of a combined clinical and general population sample (N = 2,010), 8 added items were removed. With the final item bank, we performed several CAT simulations to assess the efficiency of the extended (48 items) and the original item bank (28 items), using various stopping rules. Both item banks resulted in highly efficient and precise measurement of depression and showed high similarity between the CAT simulation scores and the full item bank scores. We discuss the implications of using each item bank and stopping rule for further CAT development.1 aFlens, Gerard1 aSmits, Niels1 aTerwee, Caroline, B.1 aDekker, Joost1 aHuijbrechts, Irma1 ade Beurs, Edwin uhttps://doi.org/10.1177/016327871668416803031nas a2200169 4500008004100000245004800041210004300089260005500132520252300187653001002710653001802720100001902738700001702757700001402774700001602788856005702804 2017 eng d00aThe Development of a Web-Based CAT in China0 aDevelopment of a WebBased CAT in China aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Cognitive ability assessment has been widely used as the recruitment tool in hiring potential employees. Traditional cognitive ability tests have been encountering threats from item-exposures and long time for answering. Especially in China, campus recruitment thinks highly of short answering time and anti-cheating. Beisen, as the biggest native online assessment software provider, developed a web-based CAT for cognitive ability which assessing verbal, quantitative, logical and spatial ability in order to decrease answering times, improve assessment accuracy and reduce threats from cheating and faking in online ability test. The web-based test provides convenient testing for examinees who can access easily to the test via internet just by login the test website at any time and any place through any Internet-enabled devices (e.g., laptops, IPADs, and smart phones).

We designed the CAT following strategies of establishing item bank, setting starting point, item selection, scoring and terminating. Additionally, we pay close attention to administrating the test via web. For the CAT procedures, we employed online calibration for establishing a stable and expanding item bank, and integrated maximum Fisher information, α-stratified strategy and randomization for item selection and coping with item exposures. Fixed-length and variable-length strategies were combined in terminating the test. For fulfilling the fluid web-based testing, we employed cloud computing techniques and designed each computing process subtly. Distributed computation was used to process scoring which executes EAP and item selecting at high speed. Caching all items to the servers in advance helps shortening the process of loading items to examinees’ terminal equipment. Horizontally scalable cloud servers function coping with great concurrency. The massive computation in item selecting was conversed to searching items from an information matrix table.

We examined the average accuracy, bank usage and computing performance in the condition of laboratory and real testing. According to a test for almost 28000 examinees, we found that bank usage is averagely 50%, and that 80% tests terminate at test information of 10 and averagely at 9.6. In context of great concurrency, the testing is unhindered and the process of scoring and item selection only takes averagely 0.23s for each examiner.

Session Video

10aChina10aWeb-Based CAT1 aLiang, Chongli1 aWang, Danjun1 aZhou, Dan1 aZhan, Peida uhttp://www.iacat.org/development-web-based-cat-china01179nas a2200157 4500008003900000245008400039210006900123300001200192490000700204520068700211100002000898700001600918700001800934700002200952856004700974 2017 d00aThe Development of MST Test Information for the Prediction of Test Performances0 aDevelopment of MST Test Information for the Prediction of Test P a570-5860 v773 aThe current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the validity of the proposed method in both measurement precision and classification accuracy. The results indicate that the MST test information effectively predicted the performance of MST. In addition, the results of the current study highlighted the relationship among the test construction, MST design factors, and MST performance.1 aPark, Ryoungsun1 aKim, Jiseon1 aChung, Hyewon1 aDodd, Barbara, G. uhttp://dx.doi.org/10.1177/001316441666296003946nas a2200181 4500008004100000245009300041210006900134260005500203520329800258653001203556653002403568653002603592653002503618100001403643700002103657700001503678856007103693 2017 eng d00aDIF-CAT: Doubly Adaptive CAT Using Subgroup Information to Improve Measurement Precision0 aDIFCAT Doubly Adaptive CAT Using Subgroup Information to Improve aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Differential item functioning (DIF) is usually regarded as a test fairness issue in high-stakes tests. In low-stakes tests, it is more of an accuracy problem. However, in low-stakes tests, the same method, deleting items that demonstrate significant DIF, is still employed to treat DIF items. When political concerns are not important, such as in low-stakes tests and instruments that are not used to make decisions about people, deleting items might not be optimal. Computerized adaptive testing (CAT) is more and more frequently used in low-stakes tests. The DIF-CAT method evaluated in this research is designed to cope with DIF in a CAT environment. Using this method, item parameters are separately estimated for the focal group and the reference group in a DIF study, then CATs are administered based on different sets of item parameters for the focal and reference groups.

To evaluate the performance of the DIF-CAT procedure, it was compared in a simulation study to (1) deleting all the DIF items in a CAT bank and (2) ignoring DIF. A 300-item flat item bank and a 300-item peaked item bank were simulated using the three-parameter logistic IRT model with D = 1,7. 40% of the items in each bank showed DIF. The DIF size was b and/or a = 0.5 while original b ranged from -3 to 3 and a ranged from 0.3 to 2.1. Three types of DIF were considered: (1) uniform DIF caused by differences in b, non-uniform DIF caused by differences in a, and non-uniform DIF caused by differences in both a and b. 500 normally distributed simulees in each of reference and focal groups were used in item parameter re-calibration. In the Delete DIF method, only DIF-free items were calibrated. In the Ignore DIF method, all the items were calibrated using all simulees without differentiating the groups. In the DIF-CAT method, the DIF-free items were used as anchor items to estimate the item parameters for the focal and reference groups and the item parameters from recalibration were used. All simulees used the same item parameters in the Delete method and the Ignore method. CATs for simulees within the two groups used group-specific item parameters in the DIF-CAT method. In the CAT stage, 100 simulees were generated for each of the reference and focal groups, at each of six discrete q levels ranging from -2.5 to 2.5. CAT test length was fixed at 40 items. Bias, average absolute difference, RMSE, standard error of θ estimates, and person fit, were used to compare the performance of the DIF methods. DIF item usage was also recorded for the Ignore method and the DIF-CAT method.

Generally, the DIF-CAT method outperformed both the Delete method and the Ignore method in dealing with DIF items in CAT. The Delete method, which is the most frequently used method for handling DIF, performed the worst of the three methods in a CAT environment, as reflected in multiple indices of measurement precision. Even the Ignore method, which simply left DIF items in the item bank, provided θ estimates of higher precision than the Delete method. This poor performance of the Delete method was probably due to reduction in size of the item bank available for each CAT.

Session Video

10aDIF-CAT10aDoubly Adaptive CAT10aMeasurement Precision10asubgroup information1 aWang, Joy1 aWeiss, David, J.1 aWang, Chun uhttps://drive.google.com/open?id=1Gu4FR06qM5EZNp_Ns0Kt3HzBqWAv3LPy01541nas a2200157 4500008003900000022001400039245009700053210006900150300001400219490000700233520104800240100001901288700001601307700001901323856004101342 2017 d a1745-398400aDual-Objective Item Selection Criteria in Cognitive Diagnostic Computerized Adaptive Testing0 aDualObjective Item Selection Criteria in Cognitive Diagnostic Co a165–1830 v543 aThe development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery status and overall test performance. The new procedure is based on the Jensen-Shannon (JS) divergence, a symmetrized version of the Kullback-Leibler divergence. We show that the JS divergence resolves the noncomparability problem of the dual information index and has close relationships with Shannon entropy, mutual information, and Fisher information. The performance of the JS divergence is evaluated in simulation studies in comparison with the methods available in the literature. Results suggest that the JS divergence achieves parallel or more precise recovery of latent trait variables compared to the existing methods and maintains practical advantages in computation and item pool usage.1 aKang, Hyeon-Ah1 aZhang, Susu1 aChang, Hua-Hua uhttp://dx.doi.org/10.1111/jedm.1213906631nas a2200157 4500008004100000245011400041210006900155260005500224520601700279653001106296653004106307653001906348100001706367700001806384856007106402 2017 eng d00aEfficiency of Item Selection in CD-CAT Based on Conjunctive Bayesian Network Modeling Hierarchical attributes0 aEfficiency of Item Selection in CDCAT Based on Conjunctive Bayes aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Cognitive diagnosis models (CDM) aim to diagnosis examinee’s mastery status of multiple fine-grained skills. As new development for cognitive diagnosis methods emerges, much attention is given to cognitive diagnostic computerized adaptive testing (CD-CAT) as well. The topics such as item selection methods, item exposure control strategies, and online calibration methods, which have been wellstudied for traditional item response theory (IRT) based CAT, are also investigated in the context of CD-CAT (e.g., Xu, Chang, & Douglas, 2003; Wang, Chang, & Huebner, 2011; Chen et al., 2012).

In CDM framework, some researchers suggest to model structural relationship between cognitive skills, or namely, attributes. Especially, attributes can be hierarchical, such that some attributes must be acquired before the subsequent ones are mastered. For example, in mathematics, addition must be mastered before multiplication, which gives a hierarchy model for addition skill and multiplication skill. Recently, new CDMs considering attribute hierarchies have been suggested including the Attribute Hierarchy Method (AHM; Leighton, Gierl, & Hunka, 2004) and the Hierarchical Diagnostic Classification Models (HDCM; Templin & Bradshaw, 2014).

Bayesian Networks (BN), the probabilistic graphical models representing the relationship of a set of random variables using a directed acyclic graph with conditional probability distributions, also provide an efficient framework for modeling the relationship between attributes (Culbertson, 2016). Among various BNs, conjunctive Bayesian network (CBN; Beerenwinkel, Eriksson, & Sturmfels, 2007) is a special kind of BN, which assumes partial ordering between occurrences of events and conjunctive constraints between them.

In this study, we propose using CBN for modeling attribute hierarchies and discuss the advantage of CBN for CDM. We then explore the impact of the CBN modeling on the efficiency of item selection methods for CD-CAT when the attributes are truly hierarchical. To this end, two simulation studies, one for fixed-length CAT and another for variable-length CAT, are conducted. For each studies, two attribute hierarchy structures with 5 and 8 attributes are assumed. Among the various item selection methods developed for CD-CAT, six algorithms are considered: posterior-weighted Kullback-Leibler index (PWKL; Cheng, 2009), the modified PWKL index (MPWKL; Kaplan, de la Torre, Barrada, 2015), Shannon entropy (SHE; Tatsuoka, 2002), mutual information (MI; Wang, 2013), posterior-weighted CDM discrimination index (PWCDI; Zheng & Chang, 2016) and posterior-weighted attribute-level CDM discrimination index (PWACDI; Zheng & Chang, 2016). The impact of Q-matrix structure, item quality, and test termination rules on the efficiency of item selection algorithms is also investigated. Evaluation measures include the attribute classification accuracy (fixed-length experiment) and test length of CDCAT until stopping (variable-length experiment).

The results of the study indicate that the efficiency of item selection is improved by directly modeling the attribute hierarchies using CBN. The test length until achieving diagnosis probability threshold was reduced to 50-70% for CBN based CAT compared to the CD-CAT assuming independence of attributes. The magnitude of improvement is greater when the cognitive model of the test includes more attributes and when the test length is shorter. We conclude by discussing how Q-matrix structure, item quality, and test termination rules affect the efficiency.

References

Beerenwinkel, N., Eriksson, N., & Sturmfels, B. (2007). Conjunctive bayesian networks. Bernoulli, 893- 909.

Chen, P., Xin, T., Wang, C., & Chang, H. H. (2012). Online calibration methods for the DINA model with independent attributes in CD-CAT. Psychometrika, 77(2), 201-222.

Cheng, Y. (2009). When cognitive diagnosis meets computerized adaptive testing: CD-CAT. Psychometrika, 74(4), 619-632.

Culbertson, M. J. (2016). Bayesian networks in educational assessment: the state of the field. Applied Psychological Measurement, 40(1), 3-21.

Kaplan, M., de la Torre, J., & Barrada, J. R. (2015). New item selection methods for cognitive diagnosis computerized adaptive testing. Applied Psychological Measurement, 39(3), 167-188.

Leighton, J. P., Gierl, M. J., & Hunka, S. M. (2004). The attribute hierarchy method for cognitive assessment: a variation on Tatsuoka's rule‐space approach. Journal of Educational Measurement, 41(3), 205-237.

Tatsuoka, C. (2002). Data analytic methods for latent partially ordered classification models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 51(3), 337-350.

Templin, J., & Bradshaw, L. (2014). Hierarchical diagnostic classification models: A family of models for estimating and testing attribute hierarchies. Psychometrika, 79(2), 317-339. Wang, C. (2013). Mutual information item selection method in cognitive diagnostic computerized adaptive testing with short test length. Educational and Psychological Measurement, 73(6), 1017-1035.

Wang, C., Chang, H. H., & Huebner, A. (2011). Restrictive stochastic item selection methods in cognitive diagnostic computerized adaptive testing. Journal of Educational Measurement, 48(3), 255-273.

Xu, X., Chang, H., & Douglas, J. (2003, April). A simulation study to compare CAT strategies for cognitive diagnosis. Paper presented at the annual meeting of National Council on Measurement in Education, Chicago.

Zheng, C., & Chang, H. H. (2016). High-efficiency response distribution–based item selection algorithms for short-length cognitive diagnostic computerized adaptive testing. Applied Psychological Measurement, 40(8), 608-624.

Session Video

10aCD-CAT10aConjuctive Bayesian Network Modeling10aitem selection1 aHan, Soo-Yun1 aYoo, Yun, Joo uhttps://drive.google.com/open?id=1RbO2gd4aULqsSgRi_VZudNN_edX82NeD03162nas a2200181 4500008004100000245010600041210006900147260005500216520249300271653000802764653001502772653002702787100002202814700002602836700001602862700001502878856008702893 2017 eng d00aEfficiency of Targeted Multistage Calibration Designs under Practical Constraints: A Simulation Study0 aEfficiency of Targeted Multistage Calibration Designs under Prac aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Calibration of an item bank for computer adaptive testing requires substantial resources. In this study, we focused on two related research questions. First, we investigated whether the efficiency of item calibration under the Rasch model could be enhanced by calibration designs that optimize the match between item difficulty and student ability (Berger, 1991). Therefore, we introduced targeted multistage calibration designs, a design type that refers to a combination of traditional targeted calibration designs and multistage designs. As such, targeted multistage calibration designs consider ability-related background variables (e.g., grade in school), as well as performance (i.e., outcome of a preceding test stage) for assigning students to suitable items.

Second, we explored how limited a priori knowledge about item difficulty affects the efficiency of both targeted calibration designs and targeted multistage calibration designs. When arranging items within a given calibration design, test developers need to know the item difficulties to locate items optimally within the design. However, usually, no empirical information about item difficulty is available before item calibration. Owing to missing empirical data, test developers might fail to assign all items to the most suitable location within a calibration design.

Both research questions were addressed in a simulation study in which we varied the calibration design, as well as the accuracy of item distribution across the different booklets or modules within each design (i.e., number of misplaced items). The results indicated that targeted multistage calibration designs were more efficient than ordinary targeted designs under optimal conditions. Especially, targeted multistage calibration designs provided more accurate estimates for very easy and 52 IACAT 2017 ABSTRACTS BOOKLET very difficult items. Limited knowledge about item difficulty during test construction impaired the efficiency of all designs. The loss of efficiency was considerably large for one of the two investigated targeted multistage calibration designs, whereas targeted designs were more robust.

References

Berger, M. P. F. (1991). On the efficiency of IRT models when applied to different sampling designs. Applied Psychological Measurement, 15(3), 293–306. doi:10.1177/014662169101500310

Session Video

10aCAT10aEfficiency10aMultistage Calibration1 aBerger, Stephanie1 aVerschoor, Angela, J.1 aEggen, Theo1 aMoser, Urs uhttps://drive.google.com/file/d/1ko2LuiARKqsjL_6aupO4Pj9zgk6p_xhd/view?usp=sharing02300nas a2200133 4500008004100000245006100041210005800102260005500160520182900215653000902044653002302053100001302076856007702089 2017 eng d00aAn Empirical Simulation Study Using mstR for MST Designs0 aEmpirical Simulation Study Using mstR for MST Designs aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Unlike other systems of adaptive testing, multistage testing (MST) provides many benefits of adaptive testing and linear testing, and has become the most sought-after form for computerized testing in educational assessment recently. It is greatly fit for testing educational achievement and can be adapted to practical educational surveys testing. However, there are many practical considerations for MST design for operational implementations including costs and benefits. As a practitioner, we need to start with various simulations to evaluate the various MST designs and their performances before the implementations. A recently developed statistical tool mstR, an open source R package, was released to support the researchers and practitioners to aid their MST simulations for implementations.

Conventional MST design has three stages of module (i.e., 1-2-3 design) structure. Alternatively, the composition of modules diverges from one design to another (e.g., 1-3 design). For advance planning of equivalence studies, this paper utilizes both 1-2-3 design and 1-3 design for the MST structures. In order to study the broad structure of these values, this paper evaluates the different MST designs through simulations using the R package mstR. The empirical simulation study provides an introductory overview of mstR and describes what mstR offers using different MST structures from 2PL item bank. Further comparisons will show the advantages of the different MST designs (e.g., 1-2-3 design and 1-3 design) for different practical implementations.

As an open-source statistical environment R, mstR provides a great simulation tool and allows psychologists, social scientists, and educational measurement scientists to apply it to innovative future assessments in the operational use of MST.

10amstR10amultistage testing1 aLee, Soo uhttp://www.iacat.org/empirical-simulation-study-using-mstr-mst-designs-002133nas a2200169 4500008004100000245006700041210006500108260005500173520156400228653000801792653000801800653002001808653002301828100002101851700002001872856007101892 2017 eng d00aEvaluation of Parameter Recovery, Drift, and DIF with CAT Data0 aEvaluation of Parameter Recovery Drift and DIF with CAT Data aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Parameter drift and differential item functioning (DIF) analyses are frequent components of a test maintenance plan. That is, after a test form(s) is published, organizations will often calibrate postpublishing data at a later date to evaluate whether the performance of the items or the test has changed over time. For example, if item content is leaked, the items might gradually become easier over time, and item statistics or parameters can reflect this.

When tests are published under a computerized adaptive testing (CAT) paradigm, they are nearly always calibrated with item response theory (IRT). IRT calibrations assume that range restriction is not an issue – that is, each item is administered to a range of examinee ability. CAT data violates this assumption. However, some organizations still wish to evaluate continuing performance of the items from a DIF or drift paradigm.

This presentation will evaluate just how inaccurate DIF and drift analyses might be on CAT data, using a Monte Carlo parameter recovery methodology. Known item parameters will be used to generate both linear and CAT data sets, which are then calibrated for DIF and drift. In addition, we will implement Randomesque item exposure constraints in some CAT conditions, as this randomization directly alleviates the range restriction problem somewhat, but it is an empirical question as to whether this improves the parameter recovery calibrations.

Session Video

10aCAT10aDIF10aParameter Drift10aParameter Recovery1 aThompson, Nathan1 aStoeger, Jordan uhttps://drive.google.com/open?id=1F7HCZWD28Q97sCKFIJB0Yps0H66NPeKq03807nas a2200145 4500008004100000245008500041210006900126260005500195520326300250653002503513653001503538653001203553100002503565856007103590 2017 eng d00aFastCAT – Customizing CAT Administration Rules to Increase Response Efficiency0 aFastCAT Customizing CAT Administration Rules to Increase Respons aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

A typical pre-requisite for CAT administration is the existence of an underlying item bank completely covering the range of the trait being measured. When a bank fails to cover the full range of the trait, examinees who are close to the floor or ceiling will often never achieve a standard error cut-off and examinees will be forced to answer items increasingly less relevant to their trait level. This scenario is fairly typical for many patients responding to patient reported outcome measures (PROMS). For IACAT 2017 ABSTRACTS BOOKLET 65 example, in the assessment of physical functioning, many item banks ceiling at about the 50%ile. For most healthy patients, after a few items the only items remaining in the bank will represent decreasing ability (even though the patient has already indicated that they are at or above the mean for the population). Another example would be for a patient with no pain taking a Pain CAT. They will probably answer “Never” pain for every succeeding item out to the maximum test length. For this project we sought to reduce patient burden, while maintaining test accuracy, through the reduction of CAT length using novel stopping rules.

We studied CAT administration assessment histories for patients who were administered Patient Reported Outcomes Measurement Information System (PROMIS) CATs. In the PROMIS 1 Wave 2 Back Pain/Depression Study, CATs were administered to N=417 cases assessed across 11 PROMIS domains. Original CAT administration rules were: start with a pre-identified item of moderate difficulty; administer a minimum four items per case; stop when an estimated theta’s SE declines to < 0.3 OR a maximum 12 items are administered.

Original CAT. 12,622 CAT administrations were analyzed. CATs ranged in number of items administered from 4 to 12 items; 72.5% were 4-item CATs. The second and third most frequently occurring CATs were 5-item (n=1102; 8.7%) and 12-item CATs (n=964; 7.6%). 64,062 items total were administered, averaging 5.1 items per CAT. Customized CAT. Three new CAT stopping rules were introduced, each with potential to increase item-presentation efficiency and maintain required score precision: Stop if a case responds to the first two items administered using an “extreme” response category (towards the ceiling or floor for the in item bank, or at ); administer a minimum two items per case; stop if the change in SE estimate (previous to current item administration) is positive but < 0.01.

The three new stopping rules reduced the total number of items administered by 25,643 to 38,419 items (40.0% reduction). After four items were administered, only n=1,824 CATs (14.5%) were still in assessment mode (vs. n=3,477 (27.5%) in the original CATs). On average, cases completed 3.0 items per CAT (vs. 5.1).

Each new rule addressed specific inefficiencies in the original CAT administration process: Cases not having or possessing a low/clinically unimportant level of the assessed domain; allow the SE <0.3 stopping criterion to come into effect earlier in the CAT administration process; cases experiencing poor domain item bank measurement, (e.g., “floor,” “ceiling” cases).

10aAdministration Rules10aEfficiency10aFastCAT1 aGershon, Richard, C. uhttps://drive.google.com/open?id=1oPJV-x0p9hRmgJ7t6k-MCC1nAoBSFM1w01714nas a2200157 4500008004100000245007500041210006900116260005500185520116600240653000801406653002401414653001201438100002001450700001501470856007101485 2017 eng d00aFrom Blueprints to Systems: An Integrated Approach to Adaptive Testing0 aFrom Blueprints to Systems An Integrated Approach to Adaptive Te aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

For years, test blueprints have told test developers how many items and what types of items will be included in a test. Adaptive testing adopted this approach from paper testing, and it is reasonably useful. Unfortunately, 'how many items and what types of items' are not all the elements one should consider when choosing items for an adaptive test. To fill in gaps, practitioners have developed tools to allow an adaptive test to behave appropriately (i.e. examining exposure control, content balancing, item drift procedures, etc.). Each of these tools involves the use of a separate process external to the primary item selection process.

The use of these subsidiary processes makes item selection less optimal and makes it difficult to prioritize aspects of selection. This discussion describes systems-based adaptive testing. This approach uses metadata concerning items, test takers and test elements to select items. These elements are weighted by the stakeholders to shape an expanded blueprint designed for adaptive testing. 

Session Video

10aCAT10aintegrated approach10aKeynote1 aKingsbury, Gage1 aZara, Tony uhttps://drive.google.com/open?id=1CBaAfH4ES7XivmvrMjPeKyFCsFZOpQMJ03003nas a2200157 4500008004100000245007600041210006900117260005500186520243700241653002102678653002302699653002002722100001602742700001602758856007102774 2017 eng d00aGenerating Rationales to Support Formative Feedback in Adaptive Testing0 aGenerating Rationales to Support Formative Feedback in Adaptive  aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Computer adaptive testing offers many important benefits to support and promote life-long learning. Computers permit testing on-demand thereby allowing students to take the test at any time during instruction; items on computerized tests are scored immediately thereby providing students with instant feedback; computerized tests permit continuous administration thereby allowing students to have more choice about when they write their exams. But despite these important benefits, the advent of computer adaptive testing has also raised formidable challenges, particularly in the area of item development. Educators must have access to large numbers of diverse, high-quality test items to implement computerize adaptive testing because items are continuously administered to students. Hence, hundreds or even thousands of items are needed to develop the test item banks necessary for computer adaptive testing. Unfortunately, educational test items, as they are currently created, are time consuming and expensive to develop because each individual item is written, initially, by a content specialist and, then, reviewed, edited, and revised by groups of content specialists to ensure the items yield reliable and valid information. Hence, item development is one of the most important problems that must be solved before we can migrate to computer adaptive testing to support life-long learning because large numbers of high-quality, content-specific, test items are required.

One promising item development method that may be used to address this challenge is with automatic item generation. Automatic item generation is a relatively new but rapidly evolving research area where cognitive and psychometric modelling practices are used produce hundreds of new test items with the aid of computer technology. The purpose of our presentation is to describe a new methodology for generating both the items and the rationales required to solve each generated item in order to produce the feedback needed to support life-long learning. Our item generation methodology will first be described. To ensure our description is practical, the method will also be demonstrated using generated items from the health sciences to demonstrate how item generation can promote life-long learning for medical educators and practitioners.

 

Session Video

10aAdaptive Testing10aformative feedback10aItem generation1 aGierl, Mark1 aBulut, Okan uhttps://drive.google.com/open?id=1O5KDFtQlDLvhNoDr7X4JO4arpJkIHKUP01513nas a2200145 4500008004100000245003400041210003300075260005500108520107900163653002101242653001601263653001701279100002201296856004901318 2017 eng d00aGrow a Tiger out of Your CAT 0 aGrow a Tiger out of Your CAT aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The main focus in the community of test developers and researchers is on improving adaptive test procedures and methodologies. Yet, the transition from research projects to larger-scale operational CATs is facing its own challenges. Usually, these operational CATs find their origin in government tenders. “Scalability”, “Interoperability” and “Transparency” are three keywords often found in these documents. Scalability is concerned with parallel system architectures which are based upon stateless selection algorithms. Design capacities often range from 10,000 to well over 100,000 concurrent students. Interoperability is implemented in standards like QTI, standards that were not designed with adaptive testing in mind. Transparency is being realized by open source software: the adaptive test should not be a black box. These three requirements often complicate the development of an adaptive test, or sometimes even conflict.

Session Video

10ainteroparability10aScalability10atransparency1 aVerschoor, Angela uhttp://www.iacat.org/grow-tiger-out-your-cat01710nas a2200133 4500008003900000245008100039210006900120300001200189490000700201520128300208100002001491700001801511856004701529 2017 d00aHeuristic Constraint Management Methods in Multidimensional Adaptive Testing0 aHeuristic Constraint Management Methods in Multidimensional Adap a241-2620 v773 aAlthough multidimensional adaptive testing (MAT) has been proven to be highly advantageous with regard to measurement efficiency when several highly correlated dimensions are measured, there are few operational assessments that use MAT. This may be due to issues of constraint management, which is more complex in MAT than it is in unidimensional adaptive testing. Very few studies have examined the performance of existing constraint management methods (CMMs) in MAT. The present article focuses on the effectiveness of two promising heuristic CMMs in MAT for varying levels of imposed constraints and for various correlations between the measured dimensions. Through a simulation study, the multidimensional maximum priority index (MMPI) and multidimensional weighted penalty model (MWPM), as an extension of the weighted penalty model, are examined with regard to measurement precision and constraint violations. The results show that both CMMs are capable of addressing complex constraints in MAT. However, measurement precision losses were found to differ between the MMPI and MWPM. While the MMPI appears to be more suitable for use in assessment situations involving few to a moderate number of constraints, the MWPM should be used when numerous constraints are involved.1 aBorn, Sebastian1 aFrey, Andreas uhttp://dx.doi.org/10.1177/001316441664374401456nas a2200133 4500008004100000245007100041210006900112260005500181520096500236653002101201653000801222100002101230856007101251 2017 eng d00aHow Adaptive is an Adaptive Test: Are all Adaptive Tests Adaptive?0 aHow Adaptive is an Adaptive Test Are all Adaptive Tests Adaptive aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

There are many different kinds of adaptive tests but they all have the characteristic that some feature of the test is customized to the purpose of the test. In the time allotted, it is impossible to consider the adaptation of all of this types so this address will focus on the “classic” adaptive test that matches the difficulty of the test to the capabilities of the person being tested. This address will first present information on the maximum level of adaptation that can occur and then compare the amount of adaptation that typically occurs on an operational adaptive test to the maximum level of adaptation. An index is proposed to summarize the amount of adaptation and it is argued that this type of index should be reported for operational adaptive tests to show the amount of adaptation that typically occurs.

Click for Presentation Video 

10aAdaptive Testing10aCAT1 aReckase, Mark, D uhttps://drive.google.com/open?id=1Nj-zDCKk3DvHA4Jlp1qkb2XovmHeQfxu03184nas a2200157 4500008004100000245010000041210006900141260005500210520260800265653002002873653001602893653001102909100001902920700001602939856007102955 2017 eng d00aThe Implementation of Nationwide High Stakes Computerized (adaptive) Testing in the Netherlands0 aImplementation of Nationwide High Stakes Computerized adaptive T aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

In this presentation the challenges of implementation of (adaptive) digital testing in the Facet system in the Netherlands is discussed. In the Netherlands there is a long tradition of implementing adaptive testing in educational settings. Already since the late nineties of the last century adaptive testing was used mostly in low stakes testing. Several CATs were implemented in student monitoring systems for primary education and in the general subjects language and arithmetic in vocational education. The only nationwide implemented high stakes CAT is the WISCAT-pabo: an arithmetic test for students in the first year of primary school teacher colleges. The psychometric advantages of item based adaptive testing are obvious. For example efficiency and high measurement precision. But there are also some disadvantages such as the impossibility of reviewing items during and after the test. During the test the student is not in control of his own test; e.q . he can only navigate forward to the next item. This is one of the reasons other methods of testing, such as multistage-testing, with adaptivity not on the item level but on subtest level, has become more popular to use in high stakes testing.

A main challenge of computerized (adaptive) testing is the implementation of the item bank and the test workflow in a digital system. Since 2014 a nationwide new digital system (Facet) was introduced in the Netherlands, with connections to the digital systems of different parties based on international standards (LTI and QTI). The first nationwide tests in the Facet-system were flexible exams Dutch and arithmetic for vocational (and secondary) education, taken as item response theory-based equated linear multiple forms tests, which are administered during 5 periods in a year. Nowadays there are some implementations of different methods of (multistage) adaptive testing in the same Facet system (DTT en Acet).

In this conference, other presenters of Cito will elaborate on the psychometric characteristics of this other adaptive testing methods. In this contribution, the system architecture and interoperability of the Facet system will be explained. The emphasis is on the implementation and the problems to be solved by using this digital system in all phases of the (adaptive) testing process: item banking, test construction, designing, publication, test taking, analyzing and reporting to the student. An evaluation of the use of the system will be presented.

Session Video

10aHigh stakes CAT10aNetherlands10aWISCAT1 avan Boxel, Mia1 aEggen, Theo uhttps://drive.google.com/open?id=1Kn1PvgioUYaOJ5pykq-_XWnwDU15rRsf03610nas a2200169 4500008004100000245006900041210006600110260005500176520302300231653000803254653002403262653003303286100001503319700001803334700001703352856007103369 2017 eng d00aAn Imputation Approach to Handling Incomplete Computerized Tests0 aImputation Approach to Handling Incomplete Computerized Tests aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

As technology advances, computerized adaptive testing (CAT) is becoming increasingly popular as it allows tests to be tailored to an examinee’s ability.  Nevertheless, examinees might devise testing strategies to use CAT to their advantage.  For instance, if only the items that examinees answer count towards their score, then a higher theta score might be obtained by spending more time on items at the beginning of the test and skipping items at the end if time runs out. This type of gaming can be discouraged if examinees’ scores are lowered or “penalized” based on the amount of non-response.

The goal of this study was to devise a penalty function that would meet two criteria: 1) the greater the omit rate, the greater the penalty, and 2) examinees with the same ability and the same omit rate should receive the same penalty. To create the penalty, theta was calculated based on only the items the examinee responded to ( ).  Next, the expected number correct score (EXR) was obtained using  and the test characteristic curve. A penalized expected number correct score (E ) was obtained by multiplying EXR by the proportion of items the examinee responded to. Finally, the penalized theta ( ) was identified using the test characteristic curve. Based on   and the item parameters ( ) of an unanswered item, the likelihood of a correct response,  , is computed and employed to estimate the imputed score ( ) for the unanswered item.

Two datasets were used to generate tests with completion rates of 50%, 80%, and 90%.  The first dataset included real data where approximately 4,500 examinees responded to a 21 -item test which provided a baseline/truth. Sampling was done to achieve the three completion rate conditions. The second dataset consisted of simulated item scores for 50,000 simulees under a 1-2-4 multi-stage CAT design where each stage contained seven items. Imputed item scores for unanswered items were computed using a variety of values for G (and therefore T).  Three other approaches to handling unanswered items were also considered: all correct (i.e., T = 0), all incorrect (i.e., T = 1), and random scoring (i.e., T = 0.5).

The current study investigated the impact on theta estimates resulting from the proposed approach to handling unanswered items in a fixed-length CAT. In real testing situations, when examinees do not finish a test, it is hard to tell whether they tried diligently but ran out of time or whether they attempted to manipulate the scoring engine.  To handle unfinished tests with penalties, the proposed approach considers examinees’ abilities and incompletion rates. The results of this study provide direction for psychometric practitioners when considering penalties for omitted responses.

Session Video

10aCAT10aimputation approach10aincomplete computerized test1 aChen, Troy1 aHuang, Chi-Yu1 aLiu, Chunyan uhttps://drive.google.com/open?id=1vznZeO3nsZZK0k6_oyw5c9ZTP8uyGnXh01106nas a2200169 4500008003900000020001400039245010200053210006900155260001500224300001400239490000700253520057900260100001900839700001600858700001700874856004500891 2017 d a0146-621600aThe Information Product Methods: A Unified Approach to Dual-Purpose Computerized Adaptive Testing0 aInformation Product Methods A Unified Approach to DualPurpose Co c2018/06/01 a321 - 3240 v423 aThis article gives a brief summary of major approaches in dual-purpose computerized adaptive testing (CAT) in which the test is tailored interactively to both an examinee?s overall ability level, ?, and attribute mastery level, α. It also proposes an information product approach whose connections to the current methods are revealed. An updated comprehensive empirical study demonstrated that the information product approach not only can offer a unified framework to connect all other approaches but also can mitigate the weighting issue in the dual-information approach.1 aZheng, Chanjin1 aHe, Guanrui1 aGao, Chunlei uhttps://doi.org/10.1177/014662161773039203841nas a2200145 4500008004100000245014000041210006900181260005500250520324600305653000803551653001103559653002903570100002503599856007103624 2017 eng d00aIssues in Trait Range Coverage for Patient Reported Outcome Measure CATs - Extending the Ceiling for Above-average Physical Functioning0 aIssues in Trait Range Coverage for Patient Reported Outcome Meas aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The use of a measure which fails to cover the upper range of functioning may produce results which can lead to serious misinterpretation. Scores produced by such a measure may fail to recognize significant improvement, or may not be able to demonstrate functioning commensurate with an important milestone. Accurate measurement of this range is critical for the assessment of physically active adults, e.g., athletes recovering from injury and active military personnel who wish to return to active service. Alternatively, a PF measure with a low ceiling might fail to differentiate patients in rehabilitation who continue to improve, but for whom their score ceilings due to the measurement used.

The assessment of physical function (PF) has greatly benefited from modern psychometric theory and resulting scales, such as the Patient-Reported Outcomes Measurement Information System (PROMIS®) PF instruments. While PROMIS PF has extended the range of function upwards relative to older “legacy” instruments, few PROMIS PF items asses high levels of function. We report here on the development of higher functioning items for the PROMIS PF bank.

An expert panel representing orthopedics, sports/military medicine, and rehabilitation reviewed existing instruments and wrote new items. After internal review, cognitive interviews were conducted with 24 individuals of average and high levels of physical function. The remaining candidate items were administered along with 50 existing PROMIS anchor items to an internet panel screened for low, average, and high levels of physical function (N = 1,600), as well as members of Boston-area gyms (N= 344). The resulting data was subjected to standard psychometric analysis, along with multiple linking methods to place the new items on the existing PF metric. The new items were added to the full PF bank for simulated computerized adaptive testing (CAT).

Item response data was collected on 54 candidate items. Items that exhibited local dependence (LD) or differential item functioning (DIF) related to gender, age, race, education, or PF status. These items were removed from consideration. Of the 50 existing PROMIS PF items, 31 were free of DIF and LD and used as anchors. The parameters for the remaining new candidate items were estimated twice: freelyestimated and linked with coefficients and fixed-anchor calibration. Both methods were comparable and had appropriate fit. The new items were added to the full PF bank for simulated CATs. The resulting CAT was able to extend the ceiling with high precision to a T-score of 68, suggesting accurate measurement for 97% of the general population.

Extending the range of items by which PF is measured will substantially improve measurement quality, applicability, and efficiency. The bank has incorporated these extension items and is available for use in research and clinics for brief CAT administration (see www.healthmeasures.net). Future research projects should focus on recovery trajectories of the measure for individuals with above average function who are recovering from injury.

Session Video

10aCAT10aIssues10aPatient Reported Outcome1 aGershon, Richard, C. uhttps://drive.google.com/open?id=1ZC02F-dIyYovEjzpeuRdoXDiXMLFRuKb02154nas a2200145 4500008004100000245005100041210005100092260005500143520166100198653002301859653002001882100001901902700001301921856007401934 2017 eng d00aItem Parameter Drifting and Online Calibration0 aItem Parameter Drifting and Online Calibration aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Item calibration is a part of the most important topics in item response theory (IRT). Since many largescale testing programs have switched from paper and pencil (P&P) testing mode to computerized adaptive testing (CAT) mode, developing methods for efficiently calibrating new items have become vital. Among many proposed item calibration processes in CAT, online calibration is the most cost-effective. This presentation introduces an online (re)calibration design to detect item parameter drift for computerized adaptive testing (CAT) in both unidimensional and multidimensional environments. Specifically, for online calibration optimal design in unidimensional computerized adaptive testing model, a two-stage design is proposed by implementing a proportional density index algorithm. For a multidimensional computerized adaptive testing model, a four-quadrant online calibration pretest item selection design with proportional density index algorithm is proposed. Comparisons were made between different online calibration item selection strategies. Results showed that under unidimensional computerized adaptive testing, the proposed modified two-stage item selection criterion with the proportional density algorithm outperformed the other existing methods in terms of item parameter calibration and item parameter drift detection, and under multidimensional computerized adaptive testing, the online (re)calibration technique with the proposed four-quadrant item selection design with proportional density index outperformed other methods.

Session Video

10aonline calibration10aParameter Drift1 aChang, Hua-Hua1 aGuo, Rui uhttp://www.iacat.org/item-parameter-drifting-and-online-calibration-001393nas a2200169 4500008004100000245003600041210003600077260005500113520088800168653000801056653002101064100002101085700001201106700001601118700001801134856007101152 2017 eng d00aItem Pool Design and Evaluation0 aItem Pool Design and Evaluation aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Early work on CAT tended to use existing sets of items which came from fixed length test forms. These sets of items were selected to meet much different requirements than are needed for a CAT; decision making or covering a content domain. However, there was also some early work that suggested having items equally distributed over the range of proficiency that was of interest or concentrated at a decision point. There was also some work that showed that there was bias in proficiency estimates when an item pool was too easy or too hard. These early findings eventually led to work on item pool design and, more recently, on item pool evaluation. This presentation gives a brief overview of these topics to give some context for the following presentations in this symposium.

Session Video

10aCAT10aItem Pool Design1 aReckase, Mark, D1 aHe, Wei1 aXu, Jing-Ru1 aZhou, Xuechun uhttps://drive.google.com/open?id=1ZAsqm1yNZlliqxEHcyyqQ_vOSu20xxZs03463nas a2200145 4500008004100000245004500041210004500086260005500131520301500186653000803201653001803209653001603227100001403243856006003257 2017 eng d00aItem Response Time on Task Effect in CAT0 aItem Response Time on Task Effect in CAT aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Introduction. In addition to reduced test length and increased measurement efficiency, computerized adaptive testing (CAT) can provide new insights into the cognitive process of task completion that cannot be mined via conventional tests. Response time is a primary characteristic of the task completion procedure. It has the potential to inform us about underlying processes. In this study, the relationship between response time and response accuracy will be investigated.

Hypothesis. The present study argues that the relationship between response time on task and response accuracy, which may be positive, negative, or curvilinear, will depend on cognitive nature of task items, holding ability of the subjects and difficulty of the items constant. The interpretations regarding the associations are not uniform either.

Research question. Is there a homogeneous effect of response time on test outcome across Graduate

Proposed explanations. If the accuracy of cognitive test responses decreases with response time, then it is an indication that the underlying cognitive process is a degrading process such as knowledge retrieval. More accessible knowledge can be retrieved faster than less accessible knowledge. It is inherent to knowledge retrieval that the success rate declines with elapsing response time. For instance, in reading tasks, the time on task effect is negative and the more negative, the easier a task is. However, if the accuracy of cognitive test responses increases with response time, then the process is of an upgrading nature, with an increasing success rate as a function of response time. For example, problem-solving takes time, and fast responses are less likely to be well-founded responses. It is of course also possible that the relationship is curvilinear, as when an increasing success rate is followed by a decreasing success rate or vice versa.

Methodology. The data are from computer-based GRE quantitative and verbal tests and will be analyzed with generalized linear mixed models (GLMM) framework after controlling the effect of ability and item difficulty as possible confounding factors. A linear model means a linear combination of predictors determining the probability of person p for answering item i correctly. The models are equivalent with advanced IRT models that go beyond the regular modeling of test responses in terms of one or more latent variables and item parameters. The lme4 package for R will be utilized to conduct the statistical calculation.

Implications. The right amount of testing time in CAT is important—too much is wasteful and costly, too little impacts score validity. The study is expected to provide new perception on the relationship between response time and response accuracy, which in turn, contribute to a better understanding of time effects and relevant cognitive process in CA.

Session Video

10aCAT10aResponse time10aTask effect1 aShi, Yang uhttp://www.iacat.org/item-response-time-task-effect-cat01708nas a2200145 4500008004100000245006200041210006200103260005500165520122100220653000801441653001401449653003001463100002101493856004801514 2017 eng d00aItem Selection Strategies for Developing CAT in Indonesia0 aItem Selection Strategies for Developing CAT in Indonesia aNiigata JapanbNiiagata Seiryo Universityc08/20173 a

Recently, development of computerized testing in Indonesia is quiet promising for the future. Many government institutions used the technology for recruitment. Starting from Indonesian Army acknowledged the benefits of computerized adaptive testing (CAT) over conventional test administration, ones of the issues of selection the first item have taken place of attention. Due to CAT’s basic philosophy, several methods can be used to select the first item such as educational level, ability estimation from item simulation, or other methods. In this case, the question is remains how apply the methods most effective in the context of constrained adaptive testing. This paper reviews such strategies that appeared in the relevant literature. The focus of this paper is on studies that have been conducted in order to evaluate the effectiveness of item selection strategies for dichotomous scoring. In this paper, also discusses the strength and weaknesses of each strategy group using examples from simulation studies. No new research is presented but rather a compendium of models is reviewed in term of learning in the newcomer context, a wide view of first item selection strategies.

 

10aCAT10aIndonesia10aitem selection strategies1 aChandra, Istiani uhttps://www.youtube.com/watch?v=2KuFrRATq9Q00592nas a2200169 4500008003900000022001400039245011200053210006900165300001600234490000700250100002400257700002200281700002500303700002300328700002500351856004600376 2017 d a1573-264900aItem usage in a multidimensional computerized adaptive test (MCAT) measuring health-related quality of life0 aItem usage in a multidimensional computerized adaptive test MCAT a2909–29180 v261 aPaap, Muirne, C. S.1 aKroeze, Karel, A.1 aTerwee, Caroline, B.1 avan der Palen, Job1 aVeldkamp, Bernard, P uhttps://doi.org/10.1007/s11136-017-1624-303826nas a2200157 4500008004100000245008500041210006900126260005500195520325800250653000803508653002203516653002303538100001603561700002003577856007103597 2017 eng d00aA Large-Scale Progress Monitoring Application with Computerized Adaptive Testing0 aLargeScale Progress Monitoring Application with Computerized Ada aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Many conventional assessment tools are available to teachers in schools for monitoring student progress in a formative manner. The outcomes of these assessment tools are essential to teachers’ instructional modifications and schools’ data-driven educational strategies, such as using remedial activities and planning instructional interventions for students with learning difficulties. When measuring student progress toward instructional goals or outcomes, assessments should be not only considerably precise but also sensitive to individual change in learning. Unlike conventional paper-pencil assessments that are usually not appropriate for every student, computerized adaptive tests (CATs) are highly capable of estimating growth consistently with minimum and consistent error. Therefore, CATs can be used as a progress monitoring tool in measuring student growth.

This study focuses on an operational CAT assessment that has been used for measuring student growth in reading during the academic school year. The sample of this study consists of nearly 7 million students from the 1st grade to the 12th grade in the US. The students received a CAT-based reading assessment periodically during the school year. The purpose of these periodical assessments is to measure the growth in students’ reading achievement and identify the students who may need additional instructional support (e.g., academic interventions). Using real data, this study aims to address the following research questions: (1) How many CAT administrations are necessary to make psychometrically sound decisions about the need for instructional changes in the classroom or when to provide academic interventions?; (2) What is the ideal amount of time between CAT administrations to capture student growth for the purpose of producing meaningful decisions from assessment results?

To address these research questions, we first used the Theil-Sen estimator for robustly fitting a regression line to each student’s test scores obtained from a series of CAT administrations. Next, we used the conditional standard error of measurement (cSEM) from the CAT administrations to create an error band around the Theil-Sen slope (i.e., student growth rate). This process resulted in the normative slope values across all the grade levels. The optimal number of CAT administrations was established from grade-level regression results. The amount of time needed for progress monitoring was determined by calculating the amount of time required for a student to show growth beyond the median cSEM value for each grade level. The results showed that the normative slope values were the highest for lower grades and declined steadily as grade level increased. The results also suggested that the CAT-based reading assessment is most useful for grades 1 through 4, since most struggling readers requiring an intervention appear to be within this grade range. Because CAT yielded very similar cSEM values across administrations, the amount of error in the progress monitoring decisions did not seem to depend on the number of CAT administrations.

Session Video

10aCAT10aLarge-Scale tests10aProcess monitoring1 aBulut, Okan1 aCormier, Damien uhttps://drive.google.com/open?id=1uGbCKenRLnqTxImX1fZicR2c7GRV6Udc00666nas a2200193 4500008003900000022001400039245008000053210006900133300001000202490000600212653004000218653002600258653003300284653002600317653002100343100002200364700002600386856006000412 2017 d a2165-659200aLatent-Class-Based Item Selection for Computerized Adaptive Progress Tests0 aLatentClassBased Item Selection for Computerized Adaptive Progre a22-430 v510acomputerized adaptive progress test10aitem selection method10aKullback-Leibler information10aLatent class analysis10alog-odds scoring1 avan Buuren, Nikky1 aEggen, Theo, J. H. M. uhttp://iacat.org/jcat/index.php/jcat/article/view/62/2902108nas a2200169 4500008004100000245005200041210005100093260005500144520156900199653002101768653000801789653002301797100001501820700001901835700001301854856007101867 2017 eng d00aMHK-MST Design and the Related Simulation Study0 aMHKMST Design and the Related Simulation Study aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The MHK is a national standardized exam that tests and rates Chinese language proficiency. It assesses non-native Chinese minorities’ abilities in using the Chinese language in their daily, academic and professional lives; Computerized multistage adaptive testing (MST) is a combination of conventional paper-and-pencil (P&P) and item level computerized adaptive test (CAT), it is a kind of test forms based on computerized technology, take the item set as the scoring unit. It can be said that, MST estimate the Ability extreme value more accurate than conventional paper-and-pencil (P&P), also used the CAT auto-adapted characteristic to reduce the examination length and the score time of report. At present, MST has used in some large test, like Uniform CPA Examination and Graduate Record Examination(GRE). Therefore, it is necessary to develop the MST of application in China.

Based on consideration of the MHK characteristics and its future development, the researchers start with design of MHK-MST. This simulation study is conducted to validate the performance of the MHK -MST system. Real difficulty parameters of MHK items and the simulated ability parameters of the candidates are used to generate the original score matrix and the item modules are delivered to the candidates following the adaptive procedures set according to the path rules. This simulation study provides a sound basis for the implementation of MHK-MST.

Session Video

10alanguage testing10aMHK10amultistage testing1 aYuyu, Ling1 aChenglin, Zhou1 aJie, Ren uhttp://www.iacat.org/mhk-mst-design-and-related-simulation-study-003876nas a2200193 4500008004100000245007700041210006900118260005500187520320800242653000803450653002103458653001603479100002003495700001803515700002003533700003803553700002003591856007103611 2017 eng d00aMulti-stage Testing for a Multi-disciplined End-of primary-school Test 0 aMultistage Testing for a Multidisciplined Endof primaryschool Te aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The Dutch secondary education system consists of five levels: basic, lower, and middle vocational education, general secondary education, and pre-academic education. The individual decision for level of secondary education is based on a combination of the teacher’s judgment and an end-of-primaryschool placement test.

This placement test encompasses the measurement of reading, language, mathematics and writing; each skill consisting of one to four subdomains. The Dutch end-of-primaryschool test is currently administered in two linear 200-item paper-based versions. The two versions differ in difficulty so as to motivate both less able and more able students, and measure both groups of students precisely. The primary goal of the test is providing a placement advice for five levels of secondary education. The secondary goal is the assessment of six different fundamental reference levels defined on reading, language, and mathematics. Because of the high stakes advice of the test, the Dutch parliament has instructed to change the format to a multistage test. A major advantage of multistage testing is that the tailoring of the tests is more strongly related to the ability of the students than to the teacher’s judgment. A separate multistage test is under development for each of the three skills measured by the reference levels to increase the classification accuracy for secondary education placement and to optimally measure the performance on the reference-level-related skills.

This symposium consists of three presentations discussing the challenges in transitioning from a linear paper-based test to a computer-based multistage test within an existing curriculum and the specification of the multistage test to meet the measurement purposes. The transitioning to a multistage test has to improve both classification accuracy and measurement precision.

First, we describe the Dutch educational system and the role of the end-of-primary-school placement test within this system. Special attention will be paid to the advantages of multistage testing over both linear testing and computerized adaptive testing, and on practical implications related to the transitioning from a linear to a multistage test.

Second, we discuss routing and reporting on the new multi-stage test. Both topics have a major impact on the quality of the placement advice and the reference mastery decisions. Several methods for routing and reporting are compared.

Third, the linear test contains 200 items to cover a broad range of different skills and to obtain a precise measurement of those skills separately. Multistage testing creates opportunities to reduce the cognitive burden for the students while maintaining the same quality of placement advice and assessment of mastering of reference levels. This presentation focuses on optimal allocation of items to test modules, optimal number of stages and modules per stage and test length reduction.

Session Video 1

Session Video 2

10amst10aMultidisciplined10aproficiency1 aStraat, Hendrik1 aGroen, Maaike1 aZijlstra, Wobbe1 aKeizer-Mittelhaëuser, Marie-Anne1 aLamoré, Michel uhttps://drive.google.com/open?id=1C5ys178p_Wl9eemQuIsI56IxDTck2z8P02365nas a2200277 4500008004100000245007100041210006900112260005500181520152900236653000801765653001501773653002801788100001501816700002101831700001501852700001401867700001601881700001501897700001601912700001601928700001601944700001801960700001901978700001901997856007102016 2017 eng d00aNew Challenges (With Solutions) and Innovative Applications of CAT0 aNew Challenges With Solutions and Innovative Applications of CAT aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Over the past several decades, computerized adaptive testing (CAT) has profoundly changed the administration of large-scale aptitude tests, state-wide achievement tests, professional licensure exams, and health outcome measures. While many challenges of CAT have been successfully addressed due to the continual efforts of researchers in the field, there are still many remaining, longstanding challenges that have yet to be resolved. This symposium will begin with three presentations, each of which provides a sound solution to one of the unresolved challenges. They are (1) item calibration when responses are “missing not at random” from CAT administration; (2) online calibration of new items when person traits have non-ignorable measurement error; (3) establishing consistency and asymptotic normality of latent trait estimation when allowing item response revision in CAT. In addition, this symposium also features innovative applications of CAT. In particular, there is emerging interest in using cognitive diagnostic CAT to monitor and detect learning progress (4th presentation). Last but not least, the 5th presentation illustrates the power of multidimensional polytomous CAT that permits rapid identification of hospitalized patients’ rehabilitative care needs in health outcomes measurement. We believe this symposium covers a wide range of interesting and important topics in CAT.

Session Video

10aCAT10achallenges10ainnovative applications1 aWang, Chun1 aWeiss, David, J.1 aZhang, Xue1 aTao, Jian1 aHe, Yinhong1 aChen, Ping1 aWang, Shiyu1 aZhang, Susu1 aLin, Haiyan1 aGao, Xiaohong1 aChang, Hua-Hua1 aShang, Zhuoran uhttps://drive.google.com/open?id=1Wvgxw7in_QCq_F7kzID6zCZuVXWcFDPa02583nas a2200157 4500008004100000245011700041210006900158260005500227520193000282653001102212653001902223653002702242100001802269700001902287856011902306 2017 eng d00aA New Cognitive Diagnostic Computerized Adaptive Testing for Simultaneously Diagnosing Skills and Misconceptions0 aNew Cognitive Diagnostic Computerized Adaptive Testing for Simul aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

In education diagnoses, diagnosing misconceptions is important as well as diagnosing skills. However, traditional cognitive diagnostic computerized adaptive testing (CD-CAT) is usually developed to diagnose skills. This study aims to propose a new CD-CAT that can simultaneously diagnose skills and misconceptions. The proposed CD-CAT is based on a recently published new CDM, called the simultaneously identifying skills and misconceptions (SISM) model (Kuo, Chen, & de la Torre, in press). A new item selection algorithm is also proposed in the proposed CD-CAT for achieving high adaptive testing performance. In simulation studies, we compare our new item selection algorithm with three existing item selection methods, including the Kullback–Leibler (KL) and posterior-weighted KL (PWKL) proposed by Cheng (2009) and the modified PWKL (MPWKL) proposed by Kaplan, de la Torre, and Barrada (2015). The results show that our proposed CD-CAT can efficiently diagnose skills and misconceptions; the accuracy of our new item selection algorithm is close to the MPWKL but less computational burden; and our new item selection algorithm outperforms the KL and PWKL methods on diagnosing skills and misconceptions.

References

Cheng, Y. (2009). When cognitive diagnosis meets computerized adaptive testing: CD-CAT. Psychometrika, 74(4), 619–632. doi: 10.1007/s11336-009-9123-2

Kaplan, M., de la Torre, J., & Barrada, J. R. (2015). New item selection methods for cognitive diagnosis computerized adaptive testing. Applied Psychological Measurement, 39(3), 167–188. doi:10.1177/0146621614554650

Kuo, B.-C., Chen, C.-H., & de la Torre, J. (in press). A cognitive diagnosis model for identifying coexisting skills and misconceptions. Applied Psychological Measurement.

Session Video

10aCD-CAT10aMisconceptions10aSimultaneous diagnosis1 aKuo, Bor-Chen1 aChen, Chun-Hua uhttp://www.iacat.org/new-cognitive-diagnostic-computerized-adaptive-testing-simultaneously-diagnosing-skills-and-003808nas a2200169 4500008004100000245008600041210006900127260005500196520318900251653000903440653000803449653002503457100002503482700001703507700001703524856009703541 2017 eng d00aNew Results on Bias in Estimates due to Discontinue Rules in Intelligence Testing0 aNew Results on Bias in Estimates due to Discontinue Rules in Int aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The presentation provides new results on a form of adaptive testing that is used frequently in intelligence testing. In these tests, items are presented in order of increasing difficulty, and the presentation of items is adaptive in the sense that each subtest session is discontinued once a test taker produces a certain number of incorrect responses in sequence. The subsequent (not observed) responses are commonly scored as wrong for that subtest, even though the test taker has not seen these. Discontinuation rules allow a certain form of adaptiveness both in paper-based and computerbased testing, and help reducing testing time.

Two lines of research that are relevant are studies that directly assess the impact of discontinuation rules, and studies that more broadly look at the impact of scoring rules on test results with a large number of not administered or not reached items. He & Wolf (2012) compared different ability estimation methods for this type of discontinuation rule adaptation of test length in a simulation study. However, to our knowledge there has been no rigorous analytical study of the underlying distributional changes of the response variables under discontinuation rules. It is important to point out that the results obtained by He & Wolf (2012) agree with results presented by, for example, DeAyala, Plake & Impara (2001) as well as Rose, von Davier & Xu (2010) and Rose, von Davier & Nagengast (2016) in that ability estimates are biased most when scoring the not observed responses as wrong. Discontinuation rules combined with scoring the non-administered items as wrong is used operationally in several major intelligence tests, so more research is needed in order to improve this particular type of adaptiveness in the testing practice.

The presentation extends existing research on adaptiveness by discontinue-rules in intelligence tests in multiple ways: First, a rigorous analytical study of the distributional properties of discontinue-rule scored items is presented. Second, an extended simulation is presented that includes additional alternative scoring rules as well as bias-corrected ability estimators that may be suitable to improve results for discontinue-rule scored intelligence tests.

References: DeAyala, R. J., Plake, B. S., & Impara, J. C. (2001). The impact of omitted responses on the accuracy of ability estimation in item response theory. Journal of Educational Measurement, 38, 213-234.

He, W. & Wolfe, E. W. (2012). Treatment of Not-Administered Items on Individually Administered Intelligence Tests. Educational and Psychological Measurement, Vol 72, Issue 5, pp. 808 – 826. DOI: 10.1177/0013164412441937

Rose, N., von Davier, M., & Xu, X. (2010). Modeling non-ignorable missing data with item response theory (IRT; ETS RR-10-11). Princeton, NJ: Educational Testing Service.

Rose, N., von Davier, M., & Nagengast, B. (2016) Modeling omitted and not-reached items in irt models. Psychometrika. doi:10.1007/s11336-016-9544-7

Session Video

10aBias10aCAT10aIntelligence Testing1 avon Davier, Matthias1 aCho, Youngmi1 aPan, Tianshu uhttp://www.iacat.org/new-results-bias-estimates-due-discontinue-rules-intelligence-testing-001828nas a2200169 4500008003900000020001400039245009100053210006900144260001500213300001400228490000700242520131200249100001401561700001701575700002101592856004501613 2017 d a0146-621600aProjection-Based Stopping Rules for Computerized Adaptive Testing in Licensure Testing0 aProjectionBased Stopping Rules for Computerized Adaptive Testing c2018/06/01 a275 - 2900 v423 aThe confidence interval (CI) stopping rule is commonly used in licensure settings to make classification decisions with fewer items in computerized adaptive testing (CAT). However, it tends to be less efficient in the near-cut regions of the ? scale, as the CI often fails to be narrow enough for an early termination decision prior to reaching the maximum test length. To solve this problem, this study proposed the projection-based stopping rules that base the termination decisions on the algorithmically projected range of the final ? estimate at the hypothetical completion of the CAT. A simulation study and an empirical study were conducted to show the advantages of the projection-based rules over the CI rule, in which the projection-based rules reduced the test length without jeopardizing critical psychometric qualities of the test, such as the ? and classification precision. Operationally, these rules do not require additional regularization parameters, because the projection is simply a hypothetical extension of the current test within the existing CAT environment. Because these new rules are specifically designed to address the decreased efficiency in the near-cut regions as opposed to for the entire scale, the authors recommend using them in conjunction with the CI rule in practice.1 aLuo, Xiao1 aKim, Doyoung1 aDickison, Philip uhttps://doi.org/10.1177/014662161772679003772nas a2200145 4500008004100000245007300041210006900114260005500183520325500238653000803493653002203501653001803523100001403541856007103555 2017 eng d00aResponse Time and Response Accuracy in Computerized Adaptive Testing0 aResponse Time and Response Accuracy in Computerized Adaptive Tes aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Introduction. This study explores the relationship between response speed and response accuracy in Computerized Adaptive Testing (CAT). CAT provides a score as well as item response times, which can offer additional diagnostic information regarding behavioral processes of task completion that cannot be uncovered by paper-based instruments. The goal of this study is to investigate how the accuracy rate evolves as a function of response time. If the accuracy of cognitive test responses decreases with response time, then it is an indication that the underlying cognitive process is a degrading process such as knowledge retrieval. More accessible knowledge can be retrieved faster than less accessible knowledge. For instance, in reading tasks, the time on task effect is negative and the more negative, the easier a task is. However, if the accuracy of cognitive test responses increases with response time, then the process is of an upgrading nature, with an increasing success rate as a function of response time. For example, problem-solving takes time, and fast responses are less likely to be well-founded responses. It is of course also possible that the relationship is curvilinear, as when an increasing success rate is followed by a decreasing success rate or vice versa.

Hypothesis. The present study argues the relationship between response time on task and response accuracy can be positive, negative, or curvilinear, which depends on cognitive nature of task items holding ability of the subjects and difficulty of the items constant.

Methodology. Data from a subsection of GRE quantitative test were available. We will use generalized linear mixed models. A linear model means a linear combination of predictors determining the probability of person p for answering item i correctly. Modeling mixed effects means both random effects and fixed effects are included. Fixed effects refer to constants across test takers. The models are equivalent with advanced IRT models that go beyond the regular modeling of test responses in terms of one or more latent variables and item parameters. The lme4 package for R will be utilized to conduct the statistical calculation.

Research questions. 1. What is the relationship between response accuracy and response speed? 2. What is the correlation between response accuracy and type of response time (fast response vs slow response) after controlling ability of people?

Preliminary Findings. 1. There is a negative relationship between response time and response accuracy. The success rate declines with elapsing response time. 2. The correlation between the two response latent variables (fast and slow) is 1.0, indicating the time on task effects between respond time types are not different.

Implications. The right amount of testing time in CAT is important—too much is wasteful and costly, too little impacts score validity. The study is expected to provide new perception on the relationship between response time and response accuracy, which in turn, contribute to the best timing strategy in CAT—with or without time constraints.

Session Video

10aCAT10aresponse accuracy10aResponse time1 aShi, Yang uhttps://drive.google.com/open?id=1yYP01bzGrKvJnfLwepcAoQQ2F4TdSvZ200491nas a2200133 4500008003900000022001400039245010800053210006900161300000700230490000600237100002500243700002400268856006500292 2017 d a2504-284X00aRobust Automated Test Assembly for Testlet-Based Tests: An Illustration with Analytical Reasoning Items0 aRobust Automated Test Assembly for TestletBased Tests An Illustr a630 v21 aVeldkamp, Bernard, P1 aPaap, Muirne, C. S. uhttps://www.frontiersin.org/article/10.3389/feduc.2017.0006303598nas a2200169 4500008004100000245004300041210004100084260005500125520306600180653000803246653002303254653002303277100001703300700002003317700002003337856007103357 2017 eng d00aScripted On-the-fly Multistage Testing0 aScripted Onthefly Multistage Testing aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

On-the-fly multistage testing (OMST) was introduced recently as a promising alternative to preassembled MST. A decidedly appealing feature of both is the reviewability of items within the current stage. However, the fundamental difference is that, instead of routing to a preassembled module, OMST adaptively assembles a module at each stage according to an interim ability estimate. This produces more individualized forms with finer measurement precision, but imposing nonstatistical constraints and controlling item exposure become more cumbersome. One recommendation is to use the maximum priority index followed by a remediation step to satisfy content constraints, and the Sympson-Hetter method with a stratified item bank for exposure control.

However, these methods can be computationally expensive, thereby impeding practical implementation. Therefore, this study investigated the script method as a simpler solution to the challenge of strict content balancing and effective item exposure control in OMST. The script method was originally devised as an item selection algorithm for CAT and generally proceeds as follows: For a test with m items, there are m slots to be filled, and an item is selected according to pre-defined rules for each slot. For the first slot, randomly select an item from a designated content area (collection). For each subsequent slot, 1) Discard any enemies of items already administered in previous slots; 2) Draw a designated number of candidate items (selection length) from the designated collection according to the current ability estimate; 3) Randomly select one item from the set of candidates. There are two distinct features of the script method. First, a predetermined sequence of collections guarantees meeting content specifications. The specific ordering may be determined either randomly or deliberately by content experts. Second, steps 2 and 3 depict a method of exposure control, in which selection length balances item usage at the possible expense of ability estimation accuracy. The adaptation of the script method to OMST is straightforward. For the first module, randomly select each item from a designated collection. For each subsequent module, the process is the same as in scripted CAT (SCAT) except the same ability estimate is used for the selection of all items within the module. A series of simulations was conducted to evaluate the performance of scripted OMST (SOMST, with 3 or 4 evenly divided stages) relative to SCAT under various item exposure restrictions. In all conditions, reliability was maximized by programming an optimization algorithm that searches for the smallest possible selection length for each slot within the constraints. Preliminary results indicated that SOMST is certainly a capable design with performance comparable to that of SCAT. The encouraging findings and ease of implementation highly motivate the prospect of operational use for large-scale assessments.

Presentation Video

10aCAT10amultistage testing10aOn-the-fly testing1 aChoe, Edison1 aWilliams, Bruce1 aLee, Sung-Hyuck uhttps://drive.google.com/open?id=1wKuAstITLXo6BM4APf2mPsth1BymNl-y01840nas a2200145 4500008004100000245010900041210006900150260005500219520128100274100001501555700001401570700001901584700002001603856007101623 2017 eng d00aA Simulation Study to Compare Classification Method in Cognitive Diagnosis Computerized Adaptive Testing0 aSimulation Study to Compare Classification Method in Cognitive D aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) combines the strengths of both CAT and cognitive diagnosis. Cognitive diagnosis models that can be viewed as restricted latent class models have been developed to classify the examinees into the correct profile of skills that have been mastered and those that have not so as to get more efficient remediation. Chiu & Douglas (2013) introduces a nonparametric procedure that only requires specification of Q-matrix to classify by proximity to ideal response pattern. In this article, we compare nonparametric procedure with common profile estimation method like maximum a posterior (MAP) in CD-CAT. Simulation studies consider a variety of Q-matrix structure, the number of attributes, ways to generate attribute profiles, and item quality. Results indicate that nonparametric procedure consistently gets the higher pattern and attribute recovery rate in nearly all conditions.

References

Chiu, C.-Y., & Douglas, J. (2013). A nonparametric approach to cognitive diagnosis by proximity to ideal response patterns. Journal of Classification, 30, 225-250. doi: 10.1007/s00357-013-9132-9

Session Video

1 aYang, Jing1 aTao, Jian1 aChang, Hua-Hua1 aShi, Ning-Zhong uhttps://drive.google.com/open?id=1jCL3fPZLgzIdwvEk20D-FliZ15OTUtpr04649nas a2200145 4500008004100000245010200041210006900143260005500212520406800267653003004335653001604365653002204381100002904403856007104432 2017 eng d00aUsing Automated Item Generation in a Large-scale Medical Licensure Exam Program: Lessons Learned.0 aUsing Automated Item Generation in a Largescale Medical Licensur aNiigata, JapanbNiigata Seiryo Universityc08.20173 a

On-demand testing has become commonplace with most large-scale testing programs. Continuous testing is appealing for candidates in that it affords greater flexibility in scheduling a session at the desired location. Furthermore, the push for more comprehensive systems of assessment (e.g. CBAL) is predicated on the availability of more frequently administered tasks given the purposeful link between instruction and assessment in these frameworks. However, continuous testing models impose several challenges to programs, including overexposure of items. Robust item banks are therefore needed to support routine retirement and replenishment of items. In a traditional approach to developing items, content experts select a topic and then develop an item consisting of a stem, lead-in question, a correct answer and list of distractors. The item then undergoes review by a panel of experts to validate the content and identify any potential flaws. The process involved in developing quality MCQ items can be time-consuming as well as costly, with estimates as high as $1500-$2500 USD per item (Rudner, 2010). The Medical Council of Canada (MCC) has been exploring a novel item development process to supplement traditional approaches. Specifically, the use of automated item generation (AIG), which uses technology to generate test items from cognitive models, has been studied for over five years. Cognitive models are representations of the knowledge and skills that are required to solve any given problem. While developing a cognitive model for a medical scenario, for example, content experts are asked to deconstruct the (clinical) reasoning process involved via clearly stated variables and related elements. The latter information is then entered into a computer program that uses algorithms to generate MCQs. The MCC has been piloting AIG –based items for over five years with the MCC Qualifying Examination Part I (MCCQE I), a pre-requisite for licensure in Canada. The aim of this presentation is to provide an overview of the practical lessons learned in the use and operational rollout of AIG with the MCCQE I. Psychometrically, the quality of the items is at least equal, and in many instances superior, to that of traditionally written MCQs, based on difficulty, discrimination, and information. In fact, 96% of the AIG based items piloted in a recent administration were retained for future operational scoring based on pre-defined inclusion criteria. AIG also offers a framework for the systematic creation of plausible distractors, in that the content experts not only need to provide the clinical reasoning underlying a correct response but also the cognitive errors associated with each of the distractors (Lai et al. 2016). Consequently, AIG holds great promise in regard to improving and tailoring diagnostic feedback for remedial purposes (Pugh, De Champlain, Gierl, Lai, Touchie, 2016). Furthermore, our test development process has been greatly enhanced by the addition of AIG as it requires that item writers use metacognitive skills to describe how they solve problems. We are hopeful that sharing our experiences with attendees might not only help other testing organizations interested in adopting AIG, but also foster discussion which might benefit all participants.

References

Lai, H., Gierl, M.J., Touchie, C., Pugh, D., Boulais, A.P., & De Champlain, A.F. (2016). Using automatic item generation to improve the quality of MCQ distractors. Teaching and Learning in Medicine, 28, 166-173.

Pugh, D., De Champlain, A.F., Lai, H., Gierl, M., & Touchie, C. (2016). Using cognitive models to develop quality multiple choice questions. Medical Teacher, 38, 838-843.

Rudner, L. (2010). Implementing the Graduate Management Admission Test Computerized Adaptive Test. In W. van der Linden & C. Glass (Eds.), Elements of adaptive testing (pp. 151-165). New York, NY: Springer. 

Presentation Video

10aAutomated item generation10alarge scale10amedical licensure1 aDe Champlain, André, F. uhttps://drive.google.com/open?id=14N8hUc8qexAy5W_94TykEDABGVIJHG1h02152nas a2200157 4500008004100000245008800041210006900129260005400198520153900252653002901791653001101820100001901831700002001850700001801870856010601888 2017 eng d00aUsing Bayesian Decision Theory in Cognitive Diagnosis Computerized Adaptive Testing0 aUsing Bayesian Decision Theory in Cognitive Diagnosis Computeriz aNiigata JapanbNiigata Seiryo Universityc08/20173 a

Cognitive diagnosis computerized adaptive testing (CD-CAT) purports to provide each individual a profile about the strengths and weaknesses of attributes or skills with computerized adaptive testing. In the CD-CAT literature, researchers dedicated to evolving item selection algorithms to improve measurement efficiency, and most algorithms were developed based on information theory. By the discontinuous nature of the latent variables in CD-CAT, this study introduced an alternative for item selection, called the minimum expected cost (MEC) method, which was derived based on Bayesian decision theory. Using simulations, the MEC method was evaluated against the posterior weighted Kullback-Leibler (PWKL) information, the modified PWKL (MPWKL), and the mutual information (MI) methods by manipulating item bank quality, item selection algorithm, and termination rule. Results indicated that, regardless of item quality and termination criterion, the MEC, MPWKL, and MI methods performed very similarly and they all outperformed the PWKL method in classification accuracy and test efficiency, especially in short tests; the MEC method had more efficient item bank usage than the MPWKL and MI methods. Moreover, the MEC method could consider the costs of incorrect decisions and improve classification accuracy and test efficiency when a particular profile was of concern. All the results suggest the practicability of the MEC method in CD-CAT.

Session Video

10aBayesian Decision Theory10aCD-CAT1 aHsu, Chia-Ling1 aWang, Wen-Chung1 aChen, ShuYing uhttp://www.iacat.org/using-bayesian-decision-theory-cognitive-diagnosis-computerized-adaptive-testing04519nas a2200181 4500008004100000245010800041210006900149260005500218520381200273653000804085653002404093653002604117100001604143700001204159700001604171700002004187856013004207 2017 eng d00aUsing Computerized Adaptive Testing to Detect Students’ Misconceptions: Exploration of Item Selection0 aUsing Computerized Adaptive Testing to Detect Students Misconcep aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Owning misconceptions impedes learning, thus detecting misconceptions through assessments is crucial to facilitate teaching. However, most computerized adaptive testing (CAT) applications to diagnose examinees’ attribute profiles focus on whether examinees mastering correct concepts or not. In educational scenario, teachers and students have to figure out the misconceptions underlying incorrect answers after obtaining the scores from assessments and then correct the corresponding misconceptions. The Scaling Individuals and Classifying Misconceptions (SICM) models proposed by Bradshaw and Templin (2014) fill this gap. SICMs can identify a student’s misconceptions directly from the distractors of multiple-choice questions and report whether s/he own the misconceptions or not. Simultaneously, SICM models are able to estimate a continuous ability within the item response theory (IRT) framework to fulfill the needs of policy-driven assessment systems relying on scaling examinees’ ability. However, the advantage of providing estimations for two types of latent variables also causes complexity of model estimation. More items are required to achieve the same accuracies for both classification and estimation compared to dichotomous DCMs and to IRT, respectively. Thus, we aim to develop a CAT using the SICM models (SICM-CAT) to estimate students’ misconceptions and continuous abilities simultaneously using fewer items than a linear test.

To achieve this goal, in this study, our research questions mainly focus on establishing several item selection rules that target on providing both accurate classification results and continuous ability estimations using SICM-CAT. The first research question is which information criterion to be used. The Kullback–Leibler (KL) divergence is the first choice, as it can naturally combine the continuous and discrete latent variables. Based on this criterion, we propose an item selection index that can nicely integrate the two types of information. Based on this index, the items selected in real time could discriminate the examinee’s current misconception profile and ability estimates from other possible estimates to the most extent. The second research question is about how to adaptively balance the estimations of the misconception profile and the continuous latent ability. Mimic the idea of the Hybrid Design proposed by Wang et al. (2016), we propose a design framework which makes the item selection transition from the group-level to the item-level. We aim to explore several design questions, such as how to select the transiting point and which latent variable estimation should be targeted first.

Preliminary results indicated that the SICM-CAT based on the proposed item selection index could classify examinees into different latent classes and measure their latent abilities compared with the random selection method more accurately and reliably under all the simulation conditions. We plan to compare different CAT designs based on our proposed item selection rules with the best linear test as the next step. We expect that the SICM-CAT is able to use shorter test length while retaining the same accuracies and reliabilities.

References

Bradshaw, L., & Templin, J. (2014). Combining item response theory and diagnostic classification models: A psychometric model for scaling ability and diagnosing misconceptions. Psychometrika, 79(3), 403-425.

Wang, S., Lin, H., Chang, H. H., & Douglas, J. (2016). Hybrid computerized adaptive testing: from group sequential design to fully sequential design. Journal of Educational Measurement, 53(1), 45-62.

Session Video

10aCAT10aincorrect answering10aStudent Misconception1 aShen, Yawei1 aBao, Yu1 aWang, Shiyu1 aBradshaw, Laine uhttp://www.iacat.org/using-computerized-adaptive-testing-detect-students%E2%80%99-misconceptions-exploration-item-selection-002175nas a2200133 4500008004100000245006300041210006300104260005500167520168000222653002501902653002301927100002001950856007101970 2017 eng d00aUsing Determinantal Point Processes for Multistage Testing0 aUsing Determinantal Point Processes for Multistage Testing aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Multistage tests are a generalization of computerized adaptive tests (CATs), that allow to ask batches of questions before starting to adapt the process, instead of asking questions one by one. In order to be provided in real-world scenarios, they should be assembled on the fly, and recent models have been designed accordingly (Zheng & Chang, 2015). We will present a new algorithm for assembling multistage tests, based on a recent technique in machine learning called determinantal point processes. We will illustrate this technique on various student data that come from fraction subtraction items, or massive online open courses.

In multidimensional CATs, feature vectors are estimated for students and questions, and the probability that a student gets a question correct depends on how much their feature vector is correlated with the question feature vector. In other words, questions that are close in space lead to similar response patterns from the students. Therefore, in order to maximize the information of a batch of questions, the volume spanned by their feature vectors should be as large as possible. Determinantal point processes allow to sample efficiently batches of items from a bank that are diverse, i.e., that span a large volume: it is actually possible to draw k items among n with a O(nk3 ) complexity, which is convenient for large databases of 10,000s of items.

References

Zheng, Y., & Chang, H. H. (2015). On-the-fly assembled multistage adaptive testing. Applied Psychological Measurement, 39(2), 104-118.

Session Video

10aMultidimentional CAT10amultistage testing1 aVie, Jill-Jênn uhttps://drive.google.com/open?id=1GkJkKTEFWK3srDX8TL4ra_Xbsliemu1R01269nas a2200301 4500008003900000022001400039245021000053210006900263260000800332300001600340490000700356520033300363100001600696700001300712700001400725700001900739700001600758700001500774700001500789700001500804700002000819700001400839700001400853700001800867700001200885700002400897856004600921 2017 d a1573-264900aThe validation of a computer-adaptive test (CAT) for assessing health-related quality of life in children and adolescents in a clinical sample: study design, methods and first results of the Kids-CAT study0 avalidation of a computeradaptive test CAT for assessing healthre cMay a1105–11170 v263 aRecently, we developed a computer-adaptive test (CAT) for assessing health-related quality of life (HRQoL) in children and adolescents: the Kids-CAT. It measures five generic HRQoL dimensions. The aims of this article were (1) to present the study design and (2) to investigate its psychometric properties in a clinical setting.1 aBarthel, D.1 aOtto, C.1 aNolte, S.1 aMeyrose, A.-K.1 aFischer, F.1 aDevine, J.1 aWalter, O.1 aMierke, A.1 aFischer, K., I.1 aThyen, U.1 aKlein, M.1 aAnkermann, T.1 aRose, M1 aRavens-Sieberer, U. uhttps://doi.org/10.1007/s11136-016-1437-901177nas a2200121 4500008003900000245007200039210006900111300000900180490000700189520078000196100002800976856005101004 2016 d00aBayesian Networks in Educational Assessment: The State of the Field0 aBayesian Networks in Educational Assessment The State of the Fie a3-210 v403 aBayesian networks (BN) provide a convenient and intuitive framework for specifying complex joint probability distributions and are thus well suited for modeling content domains of educational assessments at a diagnostic level. BN have been used extensively in the artificial intelligence community as student models for intelligent tutoring systems (ITS) but have received less attention among psychometricians. This critical review outlines the existing research on BN in educational assessment, providing an introduction to the ITS literature for the psychometric community, and points out several promising research paths. The online appendix lists 40 assessment systems that serve as empirical examples of the use of BN for educational assessment in a variety of domains.1 aCulbertson, Michael, J. uhttp://apm.sagepub.com/content/40/1/3.abstract01793nas a2200121 4500008003900000245010500039210006900144300001200213490000700225520137100232100001501603856005301618 2016 d00aA Comparison of Constrained Item Selection Methods in Multidimensional Computerized Adaptive Testing0 aComparison of Constrained Item Selection Methods in Multidimensi a346-3600 v403 aThe construction of assessments in computerized adaptive testing (CAT) usually involves fulfilling a large number of statistical and non-statistical constraints to meet test specifications. To improve measurement precision and test validity, the multidimensional priority index (MPI) and the modified MPI (MMPI) can be used to monitor many constraints simultaneously under a between-item and a within-item multidimensional framework, respectively. As both item selection methods can be implemented easily and computed efficiently, they are important and useful for operational CATs; however, no thorough simulation study has compared the performance of these two item selection methods under two different item bank structures. The purpose of this study was to investigate the efficiency of the MMPI and the MPI item selection methods under the between-item and within-item multidimensional CAT through simulations. The MMPI and the MPI item selection methods yielded similar performance in measurement precision for both multidimensional pools and yielded similar performance in exposure control and constraint management for the between-item multidimensional pool. For the within-item multidimensional pool, the MPI method yielded slightly better performance in exposure control but yielded slightly worse performance in constraint management than the MMPI method.1 aSu, Ya-Hui uhttp://apm.sagepub.com/content/40/5/346.abstract01809nas a2200133 4500008003900000245010300039210006900142300001200211490000700223520134300230100002201573700002701595856005301622 2016 d00aOn Computing the Key Probability in the Stochastically Curtailed Sequential Probability Ratio Test0 aComputing the Key Probability in the Stochastically Curtailed Se a142-1560 v403 aThe Stochastically Curtailed Sequential Probability Ratio Test (SCSPRT) is a termination criterion for computerized classification tests (CCTs) that has been shown to be more efficient than the well-known Sequential Probability Ratio Test (SPRT). The performance of the SCSPRT depends on computing the probability that at a given stage in the test, an examinee’s current interim classification status will not change before the end of the test. Previous work discusses two methods of computing this probability, an exact method in which all potential responses to remaining items are considered and an approximation based on the central limit theorem (CLT) requiring less computation. Generally, the CLT method should be used early in the test when the number of remaining items is large, and the exact method is more appropriate at later stages of the test when few items remain. However, there is currently a dearth of information as to the performance of the SCSPRT when using the two methods. For the first time, the exact and CLT methods of computing the crucial probability are compared in a simulation study to explore whether there is any effect on the accuracy or efficiency of the CCT. The article is focused toward practitioners and researchers interested in using the SCSPRT as a termination criterion in an operational CCT.1 aHuebner, Alan, R.1 aFinkelman, Matthew, D. uhttp://apm.sagepub.com/content/40/2/142.abstract00925nas a2200133 4500008003900000022001400039245012600053210006900179300001600248490000700264520045700271100001700728856004600745 2016 d a1573-264900aOn the effect of adding clinical samples to validation studies of patient-reported outcome item banks: a simulation study0 aeffect of adding clinical samples to validation studies of patie a1635–16440 v253 aTo increase the precision of estimated item parameters of item response theory models for patient-reported outcomes, general population samples are often enriched with samples of clinical respondents. Calibration studies provide little information on how this sampling scheme is incorporated into model estimation. In a small simulation study the impact of ignoring the oversampling of clinical respondents on item and person parameters is illustrated.1 aSmits, Niels uhttps://doi.org/10.1007/s11136-015-1199-900723nas a2200205 4500008004500000022001500045245013200060210006900192300000900261490000600270653002100276653003000297653003000327653001600357653002300373100002100396700002000417700002000437856006000457 2016 Engldsh  a2165-6592 00aEffect of Imprecise Parameter Estimation on Ability Estimation in a Multistage Test in an Automatic Item Generation Context 0 aEffect of Imprecise Parameter Estimation on Ability Estimation i a1-180 v410aAdaptive Testing10aautomatic item generation10aerrors in item parameters10aitem clones10amultistage testing1 aColvin, Kimberly1 aKeller, Lisa, A1 aRobin, Frederic uhttp://iacat.org/jcat/index.php/jcat/article/view/59/2701678nas a2200145 4500008003900000245012000039210006900159300001200228490000700240520117900247100001501426700002001441700001801461856005301479 2016 d00aExploration of Item Selection in Dual-Purpose Cognitive Diagnostic Computerized Adaptive Testing: Based on the RRUM0 aExploration of Item Selection in DualPurpose Cognitive Diagnosti a625-6400 v403 aCognitive diagnostic computerized adaptive testing (CD-CAT) can be divided into two broad categories: (a) single-purpose tests, which are based on the subject’s knowledge state (KS) alone, and (b) dual-purpose tests, which are based on both the subject’s KS and traditional ability level ( ). This article seeks to identify the most efficient item selection method for the latter type of CD-CAT corresponding to various conditions and various evaluation criteria, respectively, based on the reduced reparameterized unified model (RRUM) and the two-parameter logistic model of item response theory (IRT-2PLM). The Shannon entropy (SHE) and Fisher information methods were combined to produce a new synthetic item selection index, that is, the “dapperness with information (DWI)” index, which concurrently considers both KS and within one step. The new method was compared with four other methods. The results showed that, in most conditions, the new method exhibited the best performance in terms of KS estimation and the second-best performance in terms of estimation. Item utilization uniformity and computing time are also considered for all the competing methods.1 aDai, Buyun1 aZhang, Minqiang1 aLi, Guangming uhttp://apm.sagepub.com/content/40/8/625.abstract02164nas a2200133 4500008003900000245014400039210007100183300001200254490000700266520166600273100001901939700001901958856005301977 2016 d00aHigh-Efficiency Response Distribution–Based Item Selection Algorithms for Short-Length Cognitive Diagnostic Computerized Adaptive Testing0 aHighEfficiency Response Distribution–Based Item Selection Algori a608-6240 v403 aCognitive diagnostic computerized adaptive testing (CD-CAT) purports to obtain useful diagnostic information with great efficiency brought by CAT technology. Most of the existing CD-CAT item selection algorithms are evaluated when test length is fixed and relatively long, but some applications of CD-CAT, such as in interim assessment, require to obtain the cognitive pattern with a short test. The mutual information (MI) algorithm proposed by Wang is the first endeavor to accommodate this need. To reduce the computational burden, Wang provided a simplified scheme, but at the price of scale/sign change in the original index. As a result, it is very difficult to combine it with some popular constraint management methods. The current study proposes two high-efficiency algorithms, posterior-weighted cognitive diagnostic model (CDM) discrimination index (PWCDI) and posterior-weighted attribute-level CDM discrimination index (PWACDI), by modifying the CDM discrimination index. They can be considered as an extension of the Kullback–Leibler (KL) and posterior-weighted KL (PWKL) methods. A pre-calculation strategy has also been developed to address the computational issue. Simulation studies indicate that the newly developed methods can produce results comparable with or better than the MI and PWKL in both short and long tests. The other major advantage is that the computational issue has been addressed more elegantly than MI. PWCDI and PWACDI can run as fast as PWKL. More importantly, they do not suffer from the problem of scale/sign change as MI and, thus, can be used with constraint management methods together in a straightforward manner.1 aZheng, Chanjin1 aChang, Hua-Hua uhttp://apm.sagepub.com/content/40/8/608.abstract01608nas a2200169 4500008003900000022001400039245009800053210006900151300001200220490000700232520108900239100001601328700001601344700001901360700001801379856004101397 2016 d a1745-398400aHybrid Computerized Adaptive Testing: From Group Sequential Design to Fully Sequential Design0 aHybrid Computerized Adaptive Testing From Group Sequential Desig a45–620 v533 aComputerized adaptive testing (CAT) and multistage testing (MST) have become two of the most popular modes in large-scale computer-based sequential testing.  Though most designs of CAT and MST exhibit strength and weakness in recent large-scale implementations, there is no simple answer to the question of which design is better because different modes may fit different practical situations. This article proposes a hybrid adaptive framework to combine both CAT and MST, inspired by an analysis of the history of CAT and MST. The proposed procedure is a design which transitions from a group sequential design to a fully sequential design. This allows for the robustness of MST in early stages, but also shares the advantages of CAT in later stages with fine tuning of the ability estimator once its neighborhood has been identified. Simulation results showed that hybrid designs following our proposed principles provided comparable or even better estimation accuracy and efficiency than standard CAT and MST designs, especially for examinees at the two ends of the ability range.1 aWang, Shiyu1 aLin, Haiyan1 aChang, Hua-Hua1 aDouglas, Jeff uhttp://dx.doi.org/10.1111/jedm.1210001586nas a2200133 4500008003900000022001400039245008800053210006900141300001400210490000700224520115500231100002501386856004101411 2016 d a1745-398400aOn the Issue of Item Selection in Computerized Adaptive Testing With Response Times0 aIssue of Item Selection in Computerized Adaptive Testing With Re a212–2280 v533 aMany standardized tests are now administered via computer rather than paper-and-pencil format. The computer-based delivery mode brings with it certain advantages. One advantage is the ability to adapt the difficulty level of the test to the ability level of the test taker in what has been termed computerized adaptive testing (CAT). A second advantage is the ability to record not only the test taker's response to each item (i.e., question), but also the amount of time the test taker spends considering and answering each item. Combining these two advantages, various methods were explored for utilizing response time data in selecting appropriate items for an individual test taker.Four strategies for incorporating response time data were evaluated, and the precision of the final test-taker score was assessed by comparing it to a benchmark value that did not take response time information into account. While differences in measurement precision and testing times were expected, results showed that the strategies did not differ much with respect to measurement precision but that there were differences with regard to the total testing time.1 aVeldkamp, Bernard, P uhttp://dx.doi.org/10.1111/jedm.1211001950nas a2200121 4500008003900000245011400039210006900153300001200222490000700234520151600241100001801757856005301775 2016 d00aMaximum Likelihood Score Estimation Method With Fences for Short-Length Tests and Computerized Adaptive Tests0 aMaximum Likelihood Score Estimation Method With Fences for Short a289-3010 v403 aA critical shortcoming of the maximum likelihood estimation (MLE) method for test score estimation is that it does not work with certain response patterns, including ones consisting only of all 0s or all 1s. This can be problematic in the early stages of computerized adaptive testing (CAT) administration and for tests short in length. To overcome this challenge, test practitioners often set lower and upper bounds of theta estimation and truncate the score estimation to be one of those bounds when the log likelihood function fails to yield a peak due to responses consisting only of 0s or 1s. Even so, this MLE with truncation (MLET) method still cannot handle response patterns in which all harder items are correct and all easy items are incorrect. Bayesian-based estimation methods such as the modal a posteriori (MAP) method or the expected a posteriori (EAP) method can be viable alternatives to MLE. The MAP or EAP methods, however, are known to result in estimates biased toward the center of a prior distribution, resulting in a shrunken score scale. This study introduces an alternative approach to MLE, called MLE with fences (MLEF). In MLEF, several imaginary “fence” items with fixed responses are introduced to form a workable log likelihood function even with abnormal response patterns. The findings of this study suggest that, unlike MLET, the MLEF can handle any response patterns and, unlike both MAP and EAP, results in score estimates that do not cause shrinkage of the theta scale.1 aHan, Kyung, T uhttp://apm.sagepub.com/content/40/4/289.abstract01299nas a2200145 4500008003900000022001400039245009100053210006900144300001300213490000700226520083800233100002101071700002001092856004101112 2016 d a1745-398400aModeling Student Test-Taking Motivation in the Context of an Adaptive Achievement Test0 aModeling Student TestTaking Motivation in the Context of an Adap a86–1050 v533 aThis study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior. Test taker behavior was found to be inconsistent with these models, with the exception of the effort-moderated model. Effort-moderated scoring was found to both yield scores that were more accurate than those found under traditional scoring, and exhibit improved person fit statistics. In addition, an effort-guided adaptive test was proposed and shown by a simulation study to alleviate item difficulty mistargeting caused by unmotivated test taking.1 aWise, Steven, L.1 aKingsbury, Gage uhttp://dx.doi.org/10.1111/jedm.1210201362nas a2200145 4500008003900000022001400039245005800053210005800111300001400169490000700183520095400190100001901144700001201163856004101175 2016 d a1745-398400aMonitoring Items in Real Time to Enhance CAT Security0 aMonitoring Items in Real Time to Enhance CAT Security a131–1510 v533 aAn IRT-based sequential procedure is developed to monitor items for enhancing test security. The procedure uses a series of statistical hypothesis tests to examine whether the statistical characteristics of each item under inspection have changed significantly during CAT administration. This procedure is compared with a previously developed CTT-based procedure through simulation studies. The results show that when the total number of examinees is fixed both procedures can control the rate of type I errors at any reasonable significance level by choosing an appropriate cutoff point and meanwhile maintain a low rate of type II errors. Further, the IRT-based method has a much lower type II error rate or more power than the CTT-based method when the number of compromised items is small (e.g., 5), which can be achieved if the IRT-based procedure can be applied in an active mode in the sense that flagged items can be replaced with new items.1 aZhang, Jinming1 aLi, Jie uhttp://dx.doi.org/10.1111/jedm.1210401549nas a2200145 4500008003900000245010400039210006900143300001200212490000700224520104200231100002601273700002601299700002501325856005301350 2016 d00aMultidimensional Computerized Adaptive Testing for Classifying Examinees With Within-Dimensionality0 aMultidimensional Computerized Adaptive Testing for Classifying E a387-4040 v403 aA classification method is presented for adaptive classification testing with a multidimensional item response theory (IRT) model in which items are intended to measure multiple traits, that is, within-dimensionality. The reference composite is used with the sequential probability ratio test (SPRT) to make decisions and decide whether testing can be stopped before reaching the maximum test length. Item-selection methods are provided that maximize the determinant of the information matrix at the cutoff point or at the projected ability estimate. A simulation study illustrates the efficiency and effectiveness of the classification method. Simulations were run with the new item-selection methods, random item selection, and maximization of the determinant of the information matrix at the ability estimate. The study also showed that the SPRT with multidimensional IRT has the same characteristics as the SPRT with unidimensional IRT and results in more accurate classifications than the latter when used for multidimensional data.1 avan Groen, Maaike, M.1 aEggen, Theo, J. H. M.1 aVeldkamp, Bernard, P uhttp://apm.sagepub.com/content/40/6/387.abstract01720nas a2200121 4500008003900000245008600039210006900125300001200194490000700206520131800213100001401531856005301545 2016 d00aOnline Calibration of Polytomous Items Under the Generalized Partial Credit Model0 aOnline Calibration of Polytomous Items Under the Generalized Par a434-4500 v403 aOnline calibration is a technology-enhanced architecture for item calibration in computerized adaptive tests (CATs). Many CATs are administered continuously over a long term and rely on large item banks. To ensure test validity, these item banks need to be frequently replenished with new items, and these new items need to be pretested before being used operationally. Online calibration dynamically embeds pretest items in operational tests and calibrates their parameters as response data are gradually obtained through the continuous test administration. This study extends existing formulas, procedures, and algorithms for dichotomous item response theory models to the generalized partial credit model, a popular model for items scored in more than two categories. A simulation study was conducted to investigate the developed algorithms and procedures under a variety of conditions, including two estimation algorithms, three pretest item selection methods, three seeding locations, two numbers of score categories, and three calibration sample sizes. Results demonstrated acceptable estimation accuracy of the two estimation algorithms in some of the simulated conditions. A variety of findings were also revealed for the interacted effects of included factors, and recommendations were made respectively.1 aZheng, Yi uhttp://apm.sagepub.com/content/40/6/434.abstract01483nas a2200157 4500008003900000245004600039210004600085300001200131490000700143520104600150100001901196700002601215700001201241700001901253856005301272 2016 d00aOptimal Reassembly of Shadow Tests in CAT0 aOptimal Reassembly of Shadow Tests in CAT a469-4850 v403 aEven in the age of abundant and fast computing resources, concurrency requirements for large-scale online testing programs still put an uninterrupted delivery of computer-adaptive tests at risk. In this study, to increase the concurrency for operational programs that use the shadow-test approach to adaptive testing, we explored various strategies aiming for reducing the number of reassembled shadow tests without compromising the measurement quality. Strategies requiring fixed intervals between reassemblies, a certain minimal change in the interim ability estimate since the last assembly before triggering a reassembly, and a hybrid of the two strategies yielded substantial reductions in the number of reassemblies without degradation in the measurement accuracy. The strategies effectively prevented unnecessary reassemblies due to adapting to the noise in the early test stages. They also highlighted the practicality of the shadow-test approach by minimizing the computational load involved in its use of mixed-integer programming.1 aChoi, Seung, W1 aMoellering, Karin, T.1 aLi, Jie1 aLinden, Wim, J uhttp://apm.sagepub.com/content/40/7/469.abstract01438nas a2200133 4500008003900000245013200039210006900171300001200240490000700252520095400259100001901213700001901232856005301251 2016 d00aParameter Drift Detection in Multidimensional Computerized Adaptive Testing Based on Informational Distance/Divergence Measures0 aParameter Drift Detection in Multidimensional Computerized Adapt a534-5500 v403 aAn informational distance/divergence-based approach is proposed to detect the presence of parameter drift in multidimensional computerized adaptive testing (MCAT). The study presents significance testing procedures for identifying changes in multidimensional item response functions (MIRFs) over time based on informational distance/divergence measures that capture the discrepancy between two probability functions. To approximate the MIRFs from the observed response data, the k-nearest neighbors algorithm is used with the random search method. A simulation study suggests that the distance/divergence-based drift measures perform effectively in identifying the instances of parameter drift in MCAT. They showed moderate power with small samples of 500 examinees and excellent power when the sample size was as large as 1,000. The proposed drift measures also adequately controlled for Type I error at the nominal level under the null hypothesis.1 aKang, Hyeon-Ah1 aChang, Hua-Hua uhttp://apm.sagepub.com/content/40/7/534.abstract01723nas a2200145 4500008003900000245015500039210006900194300001000263490000700273520118100280100001701461700002701478700002001505856005201525 2016 d00aStochastic Curtailment of Questionnaires for Three-Level Classification: Shortening the CES-D for Assessing Low, Moderate, and High Risk of Depression0 aStochastic Curtailment of Questionnaires for ThreeLevel Classifi a22-360 v403 aIn clinical assessment, efficient screeners are needed to ensure low respondent burden. In this article, Stochastic Curtailment (SC), a method for efficient computerized testing for classification into two classes for observable outcomes, was extended to three classes. In a post hoc simulation study using the item scores on the Center for Epidemiologic Studies–Depression Scale (CES-D) of a large sample, three versions of SC, SC via Empirical Proportions (SC-EP), SC via Simple Ordinal Regression (SC-SOR), and SC via Multiple Ordinal Regression (SC-MOR) were compared at both respondent burden and classification accuracy. All methods were applied under the regular item order of the CES-D and under an ordering that was optimal in terms of the predictive power of the items. Under the regular item ordering, the three methods were equally accurate, but SC-SOR and SC-MOR needed less items. Under the optimal ordering, additional gains in efficiency were found, but SC-MOR suffered from capitalization on chance substantially. It was concluded that SC-SOR is an efficient and accurate method for clinical screening. Strengths and weaknesses of the methods are discussed.1 aSmits, Niels1 aFinkelman, Matthew, D.1 aKelderman, Henk uhttp://apm.sagepub.com/content/40/1/22.abstract01699nas a2200145 4500008003900000245009300039210006900132490000700201520118000208100001301388700001901401700001501420700001101435856010701446 2016 d00aUsing Response Time to Detect Item Preknowledge in Computer?Based Licensure Examinations0 aUsing Response Time to Detect Item Preknowledge in ComputerBased0 v353 aThis article addresses the issue of how to detect item preknowledge using item response time data in two computer-based large-scale licensure examinations. Item preknowledge is indicated by an unexpected short response time and a correct response. Two samples were used for detecting item preknowledge for each examination. The first sample was from the early stage of the operational test and was used for item calibration. The second sample was from the late stage of the operational test, which may feature item preknowledge. The purpose of this research was to explore whether there was evidence of item preknowledge and compromised items in the second sample using the parameters estimated from the first sample. The results showed that for one nonadaptive operational examination, two items (of 111) were potentially exposed, and two candidates (of 1,172) showed some indications of preknowledge on multiple items. For another licensure examination that featured computerized adaptive testing, there was no indication of item preknowledge or compromised items. Implications for detected aberrant examinees and compromised items are discussed in the article.1 aH., Qian1 aStaniewska, D.1 aReckase, M1 aWoo, A uhttp://www.iacat.org/using-response-time-detect-item-preknowledge-computerbased-licensure-examinations01559nas a2200169 4500008003900000022001400039245007700053210006900130300001300199490000700212520105800219100002101277700001401298700001901312700001701331856004101348 2015 d a1745-398400aAssessing Individual-Level Impact of Interruptions During Online Testing0 aAssessing IndividualLevel Impact of Interruptions During Online  a80–1050 v523 aWith an increase in the number of online tests, the number of interruptions during testing due to unexpected technical issues seems to be on the rise. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. Researchers such as Hill and Sinharay et al. examined the impact of interruptions at an aggregate level. However, there is a lack of research on the assessment of impact of interruptions at an individual level. We attempt to fill that void. We suggest four methodological approaches, primarily based on statistical hypothesis testing, linear regression, and item response theory, which can provide evidence on the individual-level impact of interruptions. We perform a realistic simulation study to compare the Type I error rate and power of the suggested approaches. We then apply the approaches to data from the 2013 Indiana Statewide Testing for Educational Progress-Plus (ISTEP+) test that experienced interruptions.1 aSinharay, Sandip1 aWan, Ping1 aChoi, Seung, W1 aKim, Dong-In uhttp://dx.doi.org/10.1111/jedm.1206401780nas a2200145 4500008003900000245008400039210006900123300001200192490000700204520131700211100001601528700002301544700001401567856005301581 2015 d00aa-Stratified Computerized Adaptive Testing in the Presence of Calibration Error0 aaStratified Computerized Adaptive Testing in the Presence of Cal a260-2830 v753 aa-Stratified computerized adaptive testing with b-blocking (AST), as an alternative to the widely used maximum Fisher information (MFI) item selection method, can effectively balance item pool usage while providing accurate latent trait estimates in computerized adaptive testing (CAT). However, previous comparisons of these methods have treated item parameter estimates as if they are the true population parameter values. Consequently, capitalization on chance may occur. In this article, we examined the performance of the AST method under more realistic conditions where item parameter estimates instead of true parameter values are used in the CAT. Its performance was compared against that of the MFI method when the latter is used in conjunction with Sympson–Hetter or randomesque exposure control. Results indicate that the MFI method, even when combined with exposure control, is susceptible to capitalization on chance. This is particularly true when the calibration sample size is small. On the other hand, AST is more robust to capitalization on chance. Consistent with previous investigations using true item parameter values, AST yields much more balanced item pool usage, with a small loss in the precision of latent trait estimates. The loss is negligible when the test is as long as 40 items.1 aCheng, Ying1 aPatton, Jeffrey, M1 aShao, Can uhttp://epm.sagepub.com/content/75/2/260.abstract01735nas a2200133 4500008003900000245009100039210006900130300001200199490000700211520129100218100001801509700002101527856005301548 2015 d00aBest Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model0 aBest Design for Multidimensional Computerized Adaptive Testing W a954-9780 v753 aMost computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection.1 aSeo, Dong, Gi1 aWeiss, David, J. uhttp://epm.sagepub.com/content/75/6/954.abstract01433nas a2200145 4500008003900000245011700039210006900156300001200225490000700237520092600244100002601170700001401196700002401210856005301234 2015 d00aComparing Simple Scoring With IRT Scoring of Personality Measures: The Navy Computer Adaptive Personality Scales0 aComparing Simple Scoring With IRT Scoring of Personality Measure a144-1540 v393 a

This article analyzes data from U.S. Navy sailors (N = 8,956), with the central measure being the Navy Computer Adaptive Personality Scales (NCAPS). Analyses and results from this article extend and qualify those from previous research efforts by examining the properties of the NCAPS and its adaptive structure in more detail. Specifically, this article examines item exposure rates, the efficiency of item use based on item response theory (IRT)–based Expected A Posteriori (EAP) scoring, and a comparison of IRT-EAP scoring with much more parsimonious scoring methods that appear to work just as well (stem-level scoring and dichotomous scoring). The cutting-edge nature of adaptive personality testing will necessitate a series of future efforts like this: to examine the benefits of adaptive scoring schemes and novel measurement methods continually, while pushing testing technology further ahead.

1 aOswald, Frederick, L.1 aShaw, Amy1 aFarmer, William, L. uhttp://apm.sagepub.com/content/39/2/144.abstract01505nas a2200157 4500008003900000022001400039245008900053210006900142300001200211490000700223520101800230100001701248700001501265700002601280856004101306 2015 d a1745-398400aA Comparison of IRT Proficiency Estimation Methods Under Adaptive Multistage Testing0 aComparison of IRT Proficiency Estimation Methods Under Adaptive  a70–790 v523 aThis inquiry is an investigation of item response theory (IRT) proficiency estimators’ accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two assembly conditions in each module, such as difficulty level and module length. For each panel, we investigated the accuracy of examinees’ proficiency levels derived from seven IRT proficiency estimators. The choice of Bayesian (prior) versus non-Bayesian (no prior) estimators was of more practical significance than the choice of number-correct versus item-pattern scoring estimators. The Bayesian estimators were slightly more efficient than the non-Bayesian estimators, resulting in smaller overall error. Possible score changes caused by the use of different proficiency estimators would be nonnegligible, particularly for low- and high-performing examinees.1 aKim, Sooyeon1 aMoses, Tim1 aYoo, Hanwook, (Henry) uhttp://dx.doi.org/10.1111/jedm.1206301278nas a2200121 4500008003900000245009800039210006900137490000700206520079800213100001701011700001901028856010901047 2015 d00aConsidering the Use of General and Modified Assessment Items in Computerized Adaptive Testing0 aConsidering the Use of General and Modified Assessment Items in 0 v283 aThis article used several data sets from a large-scale state testing program to examine the feasibility of combining general and modified assessment items in computerized adaptive testing (CAT) for different groups of students. Results suggested that several of the assumptions made when employing this type of mixed-item CAT may not be met for students with disabilities that have typically taken alternate assessments based on modified achievement standards (AA-MAS). A simulation study indicated that the abilities of AA-MAS students can be underestimated or overestimated by the mixed-item CAT, depending on students’ location on the underlying ability scale. These findings held across grade levels and test lengths. The mixed-item CAT appeared to function well for non-AA-MAS students.1 aWyse, A., E.1 aAlbano, A., D. uhttp://www.iacat.org/considering-use-general-and-modified-assessment-items-computerized-adaptive-testing01791nas a2200133 4500008003900000245009200039210006900131300001200200490000700212520135400219100001601573700001501589856005301604 2015 d00aThe Effect of Upper and Lower Asymptotes of IRT Models on Computerized Adaptive Testing0 aEffect of Upper and Lower Asymptotes of IRT Models on Computeriz a551-5650 v393 aIn this article, the effect of the upper and lower asymptotes in item response theory models on computerized adaptive testing is shown analytically. This is done by deriving the step size between adjacent latent trait estimates under the four-parameter logistic model (4PLM) and two models it subsumes, the usual three-parameter logistic model (3PLM) and the 3PLM with upper asymptote (3PLMU). The authors show analytically that the large effect of the discrimination parameter on the step size holds true for the 4PLM and the two models it subsumes under both the maximum information method and the b-matching method for item selection. Furthermore, the lower asymptote helps reduce the positive bias of ability estimates associated with early guessing, and the upper asymptote helps reduce the negative bias induced by early slipping. Relative step size between modeling versus not modeling the upper or lower asymptote under the maximum Fisher information method (MI) and the b-matching method is also derived. It is also shown analytically why the gain from early guessing is smaller than the loss from early slipping when the lower asymptote is modeled, and vice versa when the upper asymptote is modeled. The benefit to loss ratio is quantified under both the MI and the b-matching method. Implications of the analytical results are discussed.1 aCheng, Ying1 aLiu, Cheng uhttp://apm.sagepub.com/content/39/7/551.abstract01075nas a2200133 4500008003900000245006600039210006600105490000700171520062900178100001400807700001900821700001700840856008400857 2015 d00aEvaluating Content Alignment in Computerized Adaptive Testing0 aEvaluating Content Alignment in Computerized Adaptive Testing0 v343 aThe alignment between a test and the content domain it measures represents key evidence for the validation of test score inferences. Although procedures have been developed for evaluating the content alignment of linear tests, these procedures are not readily applicable to computerized adaptive tests (CATs), which require large item pools and do not use fixed test forms. This article describes the decisions made in the development of CATs that influence and might threaten content alignment. It outlines a process for evaluating alignment that is sensitive to these threats and gives an empirical example of the process.1 aWise, S L1 aKingsbury, G G1 aWebb, N., L. uhttp://www.iacat.org/evaluating-content-alignment-computerized-adaptive-testing00516nas a2200193 4500008004500000022001400045245004500059210004200104300000900146490000600155653001300161653001500174653001300189653001200202653001100214653001200225100002100237856006400258 2015 Engldsh  a2165-659200aImplementing a CAT: The AMC Experience 0 aImplementing a CAT The AMC Experience a1-120 v310aadaptive10aAssessment10acomputer10amedical10aonline10aTesting1 aBarnard, John, J uhttp://www.iacat.org/jcat/index.php/jcat/article/view/52/2501415nas a2200169 4500008003900000245007000039210006900109300001400178490000700192520091000199100001901109700002101128700001601149700001201165700001401177856005401191 2015 d00aInvestigation of Response Changes in the GRE Revised General Test0 aInvestigation of Response Changes in the GRE Revised General Tes a1002-10200 v753 aResearch on examinees’ response changes on multiple-choice tests over the past 80 years has yielded some consistent findings, including that most examinees make score gains by changing answers. This study expands the research on response changes by focusing on a high-stakes admissions test—the Verbal Reasoning and Quantitative Reasoning measures of the GRE revised General Test. We analyzed data from 8,538 examinees for Quantitative and 9,140 for Verbal sections who took the GRE revised General Test in 12 countries. The analyses yielded findings consistent with prior research. In addition, as examinees’ ability increases, the benefit of response changing increases. The study yielded significant implications for both test agencies and test takers. Computer adaptive tests often do not allow the test takers to review and revise. Findings from this study confirm the benefit of such features.1 aLiu, Ou, Lydia1 aBridgeman, Brent1 aGu, Lixiong1 aXu, Jun1 aKong, Nan uhttp://epm.sagepub.com/content/75/6/1002.abstract01510nas a2200145 4500008003900000245008500039210006900124300001200193490000700205520103200212100001901244700002301263700002501286856005301311 2015 d00aNew Item Selection Methods for Cognitive Diagnosis Computerized Adaptive Testing0 aNew Item Selection Methods for Cognitive Diagnosis Computerized  a167-1880 v393 aThis article introduces two new item selection methods, the modified posterior-weighted Kullback–Leibler index (MPWKL) and the generalized deterministic inputs, noisy “and” gate (G-DINA) model discrimination index (GDI), that can be used in cognitive diagnosis computerized adaptive testing. The efficiency of the new methods is compared with the posterior-weighted Kullback–Leibler (PWKL) item selection index using a simulation study in the context of the G-DINA model. The impact of item quality, generating models, and test termination rules on attribute classification accuracy or test length is also investigated. The results of the study show that the MPWKL and GDI perform very similarly, and have higher correct attribute classification rates or shorter mean test lengths compared with the PWKL. In addition, the GDI has the shortest implementation time among the three indices. The proportion of item usage with respect to the required attributes across the different conditions is also tracked and discussed.1 aKaplan, Mehmet1 ade la Torre, Jimmy1 aBarrada, Juan Ramón uhttp://apm.sagepub.com/content/39/3/167.abstract01322nas a2200145 4500008003900000245005100039210004900090300000900139490000700148520091500155100001801070700001801088700001901106856005101125 2015 d00aOnline Item Calibration for Q-Matrix in CD-CAT0 aOnline Item Calibration for QMatrix in CDCAT a5-150 v393 a

Item replenishment is important for maintaining a large-scale item bank. In this article, the authors consider calibrating new items based on pre-calibrated operational items under the deterministic inputs, noisy-and-gate model, the specification of which includes the so-called -matrix, as well as the slipping and guessing parameters. Making use of the maximum likelihood and Bayesian estimators for the latent knowledge states, the authors propose two methods for the calibration. These methods are applicable to both traditional paper–pencil–based tests, for which the selection of operational items is prefixed, and computerized adaptive tests, for which the selection of operational items is sequential and random. Extensive simulations are done to assess and to compare the performance of these approaches. Extensions to other diagnostic classification models are also discussed.

1 aChen, Yunxiao1 aLiu, Jingchen1 aYing, Zhiliang uhttp://apm.sagepub.com/content/39/1/5.abstract01517nas a2200133 4500008003900000245005300039210005100092300001200143490000700155520113500162100001401297700001901311856005301330 2015 d00aOn-the-Fly Assembled Multistage Adaptive Testing0 aOntheFly Assembled Multistage Adaptive Testing a104-1180 v393 a

Recently, multistage testing (MST) has been adopted by several important large-scale testing programs and become popular among practitioners and researchers. Stemming from the decades of history of computerized adaptive testing (CAT), the rapidly growing MST alleviates several major problems of earlier CAT applications. Nevertheless, MST is only one among all possible solutions to these problems. This article presents a new adaptive testing design, “on-the-fly assembled multistage adaptive testing” (OMST), which combines the benefits of CAT and MST and offsets their limitations. Moreover, OMST also provides some unique advantages over both CAT and MST. A simulation study was conducted to compare OMST with MST and CAT, and the results demonstrated the promising features of OMST. Finally, the “Discussion” section provides suggestions on possible future adaptive testing designs based on the OMST framework, which could provide great flexibility for adaptive tests in the digital future and open an avenue for all types of hybrid designs based on the different needs of specific tests.

1 aZheng, Yi1 aChang, Hua-Hua uhttp://apm.sagepub.com/content/39/2/104.abstract01379nas a2200157 4500008003900000245012700039210006900166300001200235490000700247520082800254100001701082700002701099700001801126700002401144856005301168 2015 d00aStochastic Curtailment in Adaptive Mastery Testing: Improving the Efficiency of Confidence Interval–Based Stopping Rules0 aStochastic Curtailment in Adaptive Mastery Testing Improving the a278-2920 v393 aA well-known stopping rule in adaptive mastery testing is to terminate the assessment once the examinee’s ability confidence interval lies entirely above or below the cut-off score. This article proposes new procedures that seek to improve such a variable-length stopping rule by coupling it with curtailment and stochastic curtailment. Under the new procedures, test termination can occur earlier if the probability is high enough that the current classification decision remains the same should the test continue. Computation of this probability utilizes normality of an asymptotically equivalent version of the maximum likelihood ability estimate. In two simulation sets, the new procedures showed a substantial reduction in average test length while maintaining similar classification accuracy to the original method.1 aSie, Haskell1 aFinkelman, Matthew, D.1 aBartroff, Jay1 aThompson, Nathan, A uhttp://apm.sagepub.com/content/39/4/278.abstract01273nas a2200121 4500008003900000245006200039210006000101490000700161520088200168100001201050700001201062856007701074 2015 d00aUsing Out-of-Level Items in Computerized Adaptive Testing0 aUsing OutofLevel Items in Computerized Adaptive Testing0 v153 aOut-of-level testing refers to the practice of assessing a student with a test that is intended for students at a higher or lower grade level. Although the appropriateness of out-of-level testing for accountability purposes has been questioned by educators and policymakers, incorporating out-of-level items in formative assessments for accurate feedback is recommended. This study made use of a commercial item bank with vertically scaled items across grades and simulated student responses in a computerized adaptive testing (CAT) environment. Results of the study suggested that administration of out-of-level items improved measurement accuracy and test efficiency for students who perform significantly above or below their grade-level peers. This study has direct implications with regards to the relevance, applicability, and benefits of using out-of-level items in CAT.1 aWei, H.1 aLin, J. uhttp://www.iacat.org/using-out-level-items-computerized-adaptive-testing01461nas a2200157 4500008003900000245006800039210006800107300001200175490000700187520097800194100001701172700002701189700001701216700001701233856005301250 2015 d00aUtilizing Response Times in Computerized Classification Testing0 aUtilizing Response Times in Computerized Classification Testing a389-4050 v393 aA well-known approach in computerized mastery testing is to combine the Sequential Probability Ratio Test (SPRT) stopping rule with item selection to maximize Fisher information at the mastery threshold. This article proposes a new approach in which a time limit is defined for the test and examinees’ response times are considered in both item selection and test termination. Item selection is performed by maximizing Fisher information per time unit, rather than Fisher information itself. The test is terminated once the SPRT makes a classification decision, the time limit is exceeded, or there is no remaining item that has a high enough probability of being answered before the time limit. In a simulation study, the new procedure showed a substantial reduction in average testing time while slightly improving classification accuracy compared with the original method. In addition, the new procedure reduced the percentage of examinees who exceeded the time limit.1 aSie, Haskell1 aFinkelman, Matthew, D.1 aRiley, Barth1 aSmits, Niels uhttp://apm.sagepub.com/content/39/5/389.abstract01714nas a2200145 4500008003900000022001400039245008400053210006900137300001400206490000700220520126100227100001901488700002001507856004101527 2015 d a1745-398400aVariable-Length Computerized Adaptive Testing Using the Higher Order DINA Model0 aVariableLength Computerized Adaptive Testing Using the Higher Or a125–1430 v523 aCognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent continuous traits is available. To facilitate the utility of cognitive diagnosis models, corresponding computerized adaptive testing (CAT) algorithms were developed. Most of them adopt the fixed-length rule to terminate CAT and are limited to ordinary cognitive diagnosis models. In this study, the higher order deterministic-input, noisy-and-gate (DINA) model was used as an example, and three criteria based on the minimum-precision termination rule were implemented: one for the latent class, one for the latent trait, and the other for both. The simulation results demonstrated that all of the termination criteria were successful when items were selected according to the Kullback-Leibler information and the posterior-weighted Kullback-Leibler information, and the minimum-precision rule outperformed the fixed-length rule with a similar test length in recovering the latent attributes and the latent trait.1 aHsu, Chia-Ling1 aWang, Wen-Chung uhttp://dx.doi.org/10.1111/jedm.1206900532nas a2200145 4500008004500000245013100045210006900176300001000245490000600255100001900261700001100280700001600291700001500307856006400322 2014 Engldsh 00aCognitive Diagnostic Models and Computerized Adaptive Testing: Two New Item-Selection Methods That Incorporate Response Times0 aCognitive Diagnostic Models and Computerized Adaptive Testing Tw a59-760 v21 aFinkelman, M D1 aKim, W1 aWeissman, A1 aCook, R.J. uhttp://www.iacat.org/jcat/index.php/jcat/article/view/43/2101689nas a2200145 4500008003900000245007800039210006900117300001200186490000700198520124300205100001201448700001301460700001701473856005301490 2014 d00aA Comparison of Four Item-Selection Methods for Severely Constrained CATs0 aComparison of Four ItemSelection Methods for Severely Constraine a677-6960 v743 a

This study compared four item-selection procedures developed for use with severely constrained computerized adaptive tests (CATs). Severely constrained CATs refer to those adaptive tests that seek to meet a complex set of constraints that are often not conclusive to each other (i.e., an item may contribute to the satisfaction of several constraints at the same time). The procedures examined in the study included the weighted deviation model (WDM), the weighted penalty model (WPM), the maximum priority index (MPI), and the shadow test approach (STA). In addition, two modified versions of the MPI procedure were introduced to deal with an edge case condition that results in the item selection procedure becoming dysfunctional during a test. The results suggest that the STA worked best among all candidate methods in terms of measurement accuracy and constraint management. For the other three heuristic approaches, they did not differ significantly in measurement accuracy and constraint management at the lower bound level. However, the WPM method appears to perform considerably better in overall constraint management than either the WDM or MPI method. Limitations and future research directions were also discussed.

1 aHe, Wei1 aDiao, Qi1 aHauser, Carl uhttp://epm.sagepub.com/content/74/4/677.abstract00553nas a2200133 4500008004500000245011300045210006900158260001200227300001000239490000600249100002700255700001700282856012000299 2014 Engldsh 00aA Comparison of Multi-Stage and Linear Test Designs for Medium-Size Licensure and Certification Examinations0 aComparison of MultiStage and Linear Test Designs for MediumSize  c02-2014 a18-360 v21 aBrossman, Bradley., G.1 aGuille, R.A. uhttp://www.iacat.org/content/comparison-multi-stage-and-linear-test-designs-medium-size-licensure-and-certification01373nas a2200133 4500008003900000245008400039210006900123300001200192490000700204520092900211100002201140700002401162856005301186 2014 d00aComputerized Adaptive Testing for the Random Weights Linear Logistic Test Model0 aComputerized Adaptive Testing for the Random Weights Linear Logi a415-4310 v383 a

This article discusses four-item selection rules to design efficient individualized tests for the random weights linear logistic test model (RWLLTM): minimum posterior-weighted -error minimum expected posterior-weighted -error maximum expected Kullback–Leibler divergence between subsequent posteriors (KLP), and maximum mutual information (MUI). The RWLLTM decomposes test items into a set of subtasks or cognitive features and assumes individual-specific effects of the features on the difficulty of the items. The model extends and improves the well-known linear logistic test model in which feature effects are only estimated at the aggregate level. Simulations show that the efficiencies of the designs obtained with the different criteria appear to be equivalent. However, KLP and MUI are given preference over and due to their lesser complexity, which significantly reduces the computational burden.

1 aCrabbe, Marjolein1 aVandebroek, Martina uhttp://apm.sagepub.com/content/38/6/415.abstract00491nam a2200133 4500008004100000020002500041245006100066210006000127260002900187100001600216700002500232700001900257856008100276 2014 eng d a13-978-1-4665-0577-300aComputerized multistage testing: Theory and applications0 aComputerized multistage testing Theory and applications aBoca Raton FLbCRC Press1 aYan, Duanli1 avon Davier, Alina, A1 aLewis, Charles uhttp://www.iacat.org/computerized-multistage-testing-theory-and-applications00689nas a2200193 4500008004500000022001400045245012100059210006900180300001000249490000600259653003100265653002300296653002200319653003200341653002500373653001800398100001500416856006400431 2014 Engldsh  a2165-659200aDetecting Item Preknowledge in Computerized Adaptive Testing Using Information Theory and Combinatorial Optimization0 aDetecting Item Preknowledge in Computerized Adaptive Testing Usi a37-580 v210acombinatorial optimization10ahypothesis testing10aitem preknowledge10aKullback-Leibler divergence10asimulated annealing.10atest security1 aBelov, D I uhttp://www.iacat.org/jcat/index.php/jcat/article/view/36/1801617nas a2200193 4500008003900000022001400039245007400053210006900127300001400196490000700210520105700217100002101274700001401295700001901309700001701328700001801345700001901363856004101382 2014 d a1745-398400aDetermining the Overall Impact of Interruptions During Online Testing0 aDetermining the Overall Impact of Interruptions During Online Te a419–4400 v513 a

With an increase in the number of online tests, interruptions during testing due to unexpected technical issues seem unavoidable. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees’ scores. There is a lack of research on this topic due to the novelty of the problem. This article is an attempt to fill that void. Several methods, primarily based on propensity score matching, linear regression, and item response theory, were suggested to determine the overall impact of the interruptions on the examinees’ scores. A realistic simulation study shows that the suggested methods have satisfactory Type I error rate and power. Then the methods were applied to data from the Indiana Statewide Testing for Educational Progress-Plus (ISTEP+) test that experienced interruptions in 2013. The results indicate that the interruptions did not have a significant overall impact on the student scores for the ISTEP+ test.

1 aSinharay, Sandip1 aWan, Ping1 aWhitaker, Mike1 aKim, Dong-In1 aZhang, Litong1 aChoi, Seung, W uhttp://dx.doi.org/10.1111/jedm.1205201835nas a2200157 4500008003900000022001400039245010200053210006900155300001400224490000700238520133800245100001501583700001901598700001901617856004101636 2014 d a1745-398400aAn Enhanced Approach to Combine Item Response Theory With Cognitive Diagnosis in Adaptive Testing0 aEnhanced Approach to Combine Item Response Theory With Cognitive a358–3800 v513 a

Computerized adaptive testing offers the possibility of gaining information on both the overall ability and cognitive profile in a single assessment administration. Some algorithms aiming for these dual purposes have been proposed, including the shadow test approach, the dual information method (DIM), and the constraint weighted method. The current study proposed two new methods, aggregate ranked information index (ARI) and aggregate standardized information index (ASI), which appropriately addressed the noncompatibility issue inherent in the original DIM method. More flexible weighting schemes that put different emphasis on information about general ability (i.e., θ in item response theory) and information about cognitive profile (i.e., α in cognitive diagnostic modeling) were also explored. Two simulation studies were carried out to investigate the effectiveness of the new methods and weighting schemes. Results showed that the new methods with the flexible weighting schemes could produce more accurate estimation of both overall ability and cognitive profile than the original DIM. Among them, the ASI with both empirical and theoretical weights is recommended, and attribute-level weighting scheme is preferred if some attributes are considered more important from a substantive perspective.

1 aWang, Chun1 aZheng, Chanjin1 aChang, Hua-Hua uhttp://dx.doi.org/10.1111/jedm.1205701425nas a2200157 4500008003900000245009200039210006900131300001200200490000700212520092000219100002001139700001601159700001801175700002101193856005301214 2014 d00aEnhancing Pool Utilization in Constructing the Multistage Test Using Mixed-Format Tests0 aEnhancing Pool Utilization in Constructing the Multistage Test U a268-2800 v383 a

This study investigated a new pool utilization method of constructing multistage tests (MST) using the mixed-format test based on the generalized partial credit model (GPCM). MST simulations of a classification test were performed to evaluate the MST design. A linear programming (LP) model was applied to perform MST reassemblies based on the initial MST construction. Three subsequent MST reassemblies were performed. For each reassembly, three test unit replacement ratios (TRRs; 0.22, 0.44, and 0.66) were investigated. The conditions of the three passing rates (30%, 50%, and 70%) were also considered in the classification testing. The results demonstrated that various MST reassembly conditions increased the overall pool utilization rates, while maintaining the desired MST construction. All MST testing conditions performed equally well in terms of the precision of the classification decision.

1 aPark, Ryoungsun1 aKim, Jiseon1 aChung, Hyewon1 aDodd, Barbara, G uhttp://apm.sagepub.com/content/38/4/268.abstract01889nas a2200157 4500008003900000245006900039210006800108300001200176490000700188520141000195100001901605700001601624700002001640700001801660856005301678 2014 d00aGeneral Test Overlap Control: Improved Algorithm for CAT and CCT0 aGeneral Test Overlap Control Improved Algorithm for CAT and CCT a229-2440 v383 a

This article proposed a new online test overlap control algorithm that is an improvement of Chen’s algorithm in controlling general test overlap rate for item pooling among a group of examinees. Chen’s algorithm is not very efficient in that not only item pooling between current examinee and prior examinees is controlled for but also item pooling between previous examinees, which would have been controlled for when they were current examinees. The proposed improvement increases efficiency by only considering item pooling between current and previous examinees, and its improved performance over Chen is demonstrated in a simulated computerized adaptive testing (CAT) environment. Moreover, the proposed algorithm is adapted for computerized classification testing (CCT) using the sequential probability ratio test procedure and is evaluated against some existing exposure control procedures. The proposed algorithm appears to work best in controlling general test overlap rate among the exposure control procedures examined without sacrificing much classification precision, though longer tests might be required for more stringent control of item pooling among larger groups. Given the capability of the proposed algorithm in controlling item pooling among a group of examinees of any size and its ease of implementation, it appears to be a good test overlap control method.

1 aChen, Shu-Ying1 aLei, Pui-Wa1 aChen, Jyun-Hong1 aLiu, Tzu-Chen uhttp://apm.sagepub.com/content/38/3/229.abstract01984nas a2200121 4500008003900000245008900039210006900128300001200197490000700209520157400216100001501790856005701805 2014 d00aImproving Measurement Precision of Hierarchical Latent Traits Using Adaptive Testing0 aImproving Measurement Precision of Hierarchical Latent Traits Us a452-4770 v393 a

Many latent traits in social sciences display a hierarchical structure, such as intelligence, cognitive ability, or personality. Usually a second-order factor is linearly related to a group of first-order factors (also called domain abilities in cognitive ability measures), and the first-order factors directly govern the actual item responses. Because only a subtest of items is used to measure each domain, the lack of sufficient reliability becomes the primary impediment for generating and reporting domain abilities. In recent years, several item response theory (IRT) models have been proposed to account for hierarchical factor structures, and these models are also shown to alleviate the low reliability issue by using in-test collateral information to improve measurement precision. This article advocates using adaptive item selection together with a higher order IRT model to further increase the reliability of hierarchical latent trait estimation. Two item selection algorithms are proposed—the constrained D-optimal method and the sequencing domain method. Both are shown to yield improved measurement precision as compared to the unidimensional item selection (by treating each dimension separately). The improvement is more prominent when the test length is short and when the correlation between dimensions is high (e.g., higher than .64). Moreover, two reliability indices for hierarchical latent traits are discussed and their use for quantifying the reliability of hierarchical traits measured by adaptive testing is demonstrated.

1 aWang, Chun uhttp://jeb.sagepub.com/cgi/content/abstract/39/6/45201730nas a2200133 4500008003900000245008300039210006900122300001200191490000700203520130000210100001201510700002101522856005301543 2014 d00aItem Pool Design for an Operational Variable-Length Computerized Adaptive Test0 aItem Pool Design for an Operational VariableLength Computerized  a473-4940 v743 a

For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution and item exposure issues. Yet, there is little research on how to design item pools to have those desirable features. The research reported in this article provided step-by-step hands-on guidance on the item pool design process by applying the bin-and-union method to design item pools for a large-scale licensure CAT employing complex adaptive testing algorithm with variable test length, a decision based on stopping rule, content balancing, and exposure control. The design process involved extensive simulations to identify several alternative item pool designs and evaluate their performance against a series of criteria. The design output included the desired item pool size and item parameter distribution. The results indicate that the mechanism used to identify the desirable item pool features functions well and that two recommended item pool designs would support satisfactory performance of the operational testing program.

1 aHe, Wei1 aReckase, Mark, D uhttp://epm.sagepub.com/content/74/3/473.abstract01545nas a2200145 4500008003900000245011500039210006900154300001200223490000700235520102700242100002601269700002601295700002501321856005301346 2014 d00aItem Selection Methods Based on Multiple Objective Approaches for Classifying Respondents Into Multiple Levels0 aItem Selection Methods Based on Multiple Objective Approaches fo a187-2000 v383 a

Computerized classification tests classify examinees into two or more levels while maximizing accuracy and minimizing test length. The majority of currently available item selection methods maximize information at one point on the ability scale, but in a test with multiple cutting points selection methods could take all these points simultaneously into account. If for each cutting point one objective is specified, the objectives can be combined into one optimization function using multiple objective approaches. Simulation studies were used to compare the efficiency and accuracy of eight selection methods in a test based on the sequential probability ratio test. Small differences were found in accuracy and efficiency between different methods depending on the item pool and settings of the classification method. The size of the indifference region had little influence on accuracy but considerable influence on efficiency. Content and exposure control had little influence on accuracy and efficiency.

1 avan Groen, Maaike, M.1 aEggen, Theo, J. H. M.1 aVeldkamp, Bernard, P uhttp://apm.sagepub.com/content/38/3/187.abstract02104nas a2200133 4500008003900000022001400039245013800053210006900191300001200260490000700272520163500279100001501914856004101929 2014 d a1745-398400aMultidimensional CAT Item Selection Methods for Domain Scores and Composite Scores With Item Exposure Control and Content Constraints0 aMultidimensional CAT Item Selection Methods for Domain Scores an a18–380 v513 a

The intent of this research was to find an item selection procedure in the multidimensional computer adaptive testing (CAT) framework that yielded higher precision for both the domain and composite abilities, had a higher usage of the item pool, and controlled the exposure rate. Five multidimensional CAT item selection procedures (minimum angle; volume; minimum error variance of the linear combination; minimum error variance of the composite score with optimized weight; and Kullback-Leibler information) were studied and compared with two methods for item exposure control (the Sympson-Hetter procedure and the fixed-rate procedure, the latter simply refers to putting a limit on the item exposure rate) using simulated data. The maximum priority index method was used for the content constraints. Results showed that the Sympson-Hetter procedure yielded better precision than the fixed-rate procedure but had much lower item pool usage and took more time. The five item selection procedures performed similarly under Sympson-Hetter. For the fixed-rate procedure, there was a trade-off between the precision of the ability estimates and the item pool usage: the five procedures had different patterns. It was found that (1) Kullback-Leibler had better precision but lower item pool usage; (2) minimum angle and volume had balanced precision and item pool usage; and (3) the two methods minimizing the error variance had the best item pool usage and comparable overall score recovery but less precision for certain domains. The priority index for content constraints and item exposure was implemented successfully.

1 aYao, Lihua uhttp://dx.doi.org/10.1111/jedm.1203200965nas a2200121 4500008003900000245008900039210006900128300001200197490000700209520055500216100001900771856005300790 2014 d00aA Numerical Investigation of the Recovery of Point Patterns With Minimal Information0 aNumerical Investigation of the Recovery of Point Patterns With M a329-3350 v383 a

A method has been proposed (Tsogo et al. 2001) in order to reconstruct the geometrical configuration of a large point set using minimal information. This paper employs numerical examples to investigate the proposed procedure. The suggested method has two great advantages. It reduces the volume of the data collection exercise and eases the computational effort involved in analyzing the data. It is suggested, however, that the method while possibly providing a useful starting point for a solution, does not provide a universal panacea.

1 aCox, M., A. A. uhttp://apm.sagepub.com/content/38/4/329.abstract02041nas a2200121 4500008003900000245007400039210006900113300001200182490000700194520163800201100002301839856005701862 2014 d00aThe Sequential Probability Ratio Test and Binary Item Response Models0 aSequential Probability Ratio Test and Binary Item Response Model a203-2300 v393 a

The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has been previously noted (Spray & Reckase, 1994), the SPRT test statistic is not necessarily monotonic with respect to the classification bound when item response functions have nonzero lower asymptotes. Because of nonmonotonicity, several researchers (including Spray & Reckase, 1994) have recommended selecting items at the classification bound rather than the current ability estimate when terminating SPRT-based classification tests. Unfortunately, this well-worn advice is a bit too simplistic. Items yielding optimal evidence for classification depend on the IRT model, item parameters, and location of an examinee with respect to the classification bound. The current study illustrates, in depth, the relationship between the SPRT test statistic and classification evidence in binary IRT models. Unlike earlier studies, we examine the form of the SPRT-based log-likelihood ratio while altering the classification bound and item difficulty. These investigations motivate a novel item selection algorithm based on optimizing the expected SPRT criterion given the current ability estimate. The new expected log-likelihood ratio algorithm results in test lengths noticeably shorter than current, commonly used algorithms, and with no loss in classification accuracy.

1 aNydick, Steven, W. uhttp://jeb.sagepub.com/cgi/content/abstract/39/3/20301176nas a2200121 4500008003900000245009200039210006900131300001100200490000700211520076500218100001900983856005201002 2014 d00aA Sequential Procedure for Detecting Compromised Items in the Item Pool of a CAT System0 aSequential Procedure for Detecting Compromised Items in the Item a87-1040 v383 a

To maintain the validity of a continuous testing system, such as computerized adaptive testing (CAT), items should be monitored to ensure that the performance of test items has not gone through any significant changes during their lifetime in an item pool. In this article, the author developed a sequentially monitoring procedure based on a series of statistical hypothesis tests to examine whether the statistical characteristics of individual items have changed significantly during test administration. Simulation studies show that under the simulated setting, by choosing an appropriate cutoff point, the procedure can control the rate of Type I errors at any reasonable significance level and meanwhile, has a very low rate of Type II errors.

1 aZhang, Jinming uhttp://apm.sagepub.com/content/38/2/87.abstract01676nas a2200145 4500008003900000245012600039210006900165300001200234490000700246520115400253100002601407700002201433700002201455856005301477 2014 d00aStratified Item Selection and Exposure Control in Unidimensional Adaptive Testing in the Presence of Two-Dimensional Data0 aStratified Item Selection and Exposure Control in Unidimensional a563-5760 v383 a

It is not uncommon to use unidimensional item response theory models to estimate ability in multidimensional data with computerized adaptive testing (CAT). The current Monte Carlo study investigated the penalty of this model misspecification in CAT implementations using different item selection methods and exposure control strategies. Three item selection methods—maximum information (MAXI), a-stratification (STRA), and a-stratification with b-blocking (STRB) with and without Sympson–Hetter (SH) exposure control strategy—were investigated. Calibrating multidimensional items as unidimensional items resulted in inaccurate item parameter estimates. Therefore, MAXI performed better than STRA and STRB in estimating the ability parameters. However, all three methods had relatively large standard errors. SH exposure control had no impact on the number of overexposed items. Existing unidimensional CAT implementations might consider using MAXI only if recalibration as multidimensional model is too expensive. Otherwise, building a CAT pool by calibrating multidimensional data as unidimensional is not recommended.

1 aKalinowski, Kevin, E.1 aNatesan, Prathiba1 aHenson, Robin, K. uhttp://apm.sagepub.com/content/38/7/563.abstract01548nas a2200145 4500008003900000245008200039210006900121300001200190490000700202520108300209100001501292700002001307700002201327856005301349 2014 d00aUsing Multidimensional CAT to Administer a Short, Yet Precise, Screening Test0 aUsing Multidimensional CAT to Administer a Short Yet Precise Scr a614-6310 v383 a

Multidimensional computerized adaptive testing (MCAT) provides a mechanism by which the simultaneous goals of accurate prediction and minimal testing time for a screening test could both be met. This article demonstrates the use of MCAT to administer a screening test for the Computerized Adaptive Testing–Armed Services Vocational Aptitude Battery (CAT-ASVAB) under a variety of manipulated conditions. CAT-ASVAB is a test battery administered via unidimensional CAT (UCAT) that is used to qualify applicants for entry into the U.S. military and assign them to jobs. The primary research question being evaluated is whether the use of MCAT to administer a screening test can lead to significant reductions in testing time from the full-length selection test, without significant losses in score precision. Different stopping rules, item selection methods, content constraints, time constraints, and population distributions for the MCAT administration are evaluated through simulation, and compared with results from a regular full-length UCAT administration.

1 aYao, Lihua1 aPommerich, Mary1 aSegall, Daniel, O uhttp://apm.sagepub.com/content/38/8/614.abstract00445nas a2200109 4500008004500000245008700045210006900132300000900201490000600210100002000216856009900236 2014 Engldsh 00aThe Utility of Adaptive Testing in Addressing the Problem of Unmotivated Examinees0 aUtility of Adaptive Testing in Addressing the Problem of Unmotiv a1-170 v21 aWise, Steven, L uhttp://www.iacat.org/content/utility-adaptive-testing-addressing-problem-unmotivated-examinees00493nas a2200121 4500008003900000245013500039210006900174300001200243490000700255100002100262700002000283856006800303 2013 d00aThe Applicability of Multidimensional Computerized Adaptive Testing for Cognitive Ability Measurement in Organizational Assessment0 aApplicability of Multidimensional Computerized Adaptive Testing  a123-1390 v131 aMakransky, Guido1 aGlas, Cees, A W uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2012.67235200572nas a2200133 4500008004500000022001400045245013400059210006900193300001200262490000700274100001700281700001600298856012400314 2013 Engldsh  a1530-505800aThe applicability of multidimensional computerized adaptive testing to cognitive ability measurement in organizational assessment0 aapplicability of multidimensional computerized adaptive testing  a123-1390 v131 aMakransky, G1 aGlas, C A W uhttp://www.iacat.org/content/applicability-multidimensional-computerized-adaptive-testing-cognitive-ability-measurement01583nas a2200133 4500008003900000245012700039210006900166300001200235490000700247520111200254100001701366700001301383856005301396 2013 d00aThe Application of the Monte Carlo Approach to Cognitive Diagnostic Computerized Adaptive Testing With Content Constraints0 aApplication of the Monte Carlo Approach to Cognitive Diagnostic  a482-4960 v373 a

The Monte Carlo approach which has previously been implemented in traditional computerized adaptive testing (CAT) is applied here to cognitive diagnostic CAT to test the ability of this approach to address multiple content constraints. The performance of the Monte Carlo approach is compared with the performance of the modified maximum global discrimination index (MMGDI) method on simulations in which the only content constraint is on the number of items that measure each attribute. The results of the two simulation experiments show that (a) the Monte Carlo method fulfills all the test requirements and produces satisfactory measurement precision and item exposure results and (b) the Monte Carlo method outperforms the MMGDI method when the Monte Carlo method applies either the posterior-weighted Kullback–Leibler algorithm or the hybrid Kullback–Leibler information as the item selection index. Overall, the recovery rate of the knowledge states, the distribution of the item exposure, and the utilization rate of the item bank are improved when the Monte Carlo method is used.

1 aMao, Xiuzhen1 aXin, Tao uhttp://apm.sagepub.com/content/37/6/482.abstract02024nas a2200121 4500008003900000245011000039210006900149300000900218490000700227520160200234100001501836856005101851 2013 d00aComparing the Performance of Five Multidimensional CAT Selection Procedures With Different Stopping Rules0 aComparing the Performance of Five Multidimensional CAT Selection a3-230 v373 a

Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error (SE) and predicted standard error reduction (PSER), are proposed; each MCAT selection process is stopped if either the required precision has been achieved or the selected number of items has reached the maximum limit. The five procedures are as follows: minimum angle (Ag), volume (Vm), minimize the error variance of the linear combination (V 1), minimize the error variance of the composite score with the optimized weight (V 2), and Kullback–Leibler (KL) information. The recovery for the domain scores or content scores and their overall score, test length, and test reliability are compared across the five MCAT procedures and between the two stopping rules. It is found that the two stopping rules are implemented successfully and that KL uses the least number of items to reach the same precision level, followed by Vm; Ag uses the largest number of items. On average, to reach a precision of SE = .35, 40, 55, 63, 63, and 82 items are needed for KL, Vm, V 1, V 2, and Ag, respectively, for the SE stopping rule. PSER yields 38, 45, 53, 58, and 68 items for KL, Vm, V 1, V 2, and Ag, respectively; PSER yields only slightly worse results than SE, but with much fewer items. Overall, KL is recommended for varying-length MCAT.

1 aYao, Lihua uhttp://apm.sagepub.com/content/37/1/3.abstract00520nas a2200121 4500008004500000245011300045210006900158300001000227490000600237100001300243700001900256856012300275 2013 Engldsh 00aA Comparison of Computerized Classification Testing and Computerized Adaptive Testing in Clinical Psychology0 aComparison of Computerized Classification Testing and Computeriz a19-370 v11 aSmits, N1 aFinkelman, M D uhttp://www.iacat.org/content/comparison-computerized-classification-testing-and-computerized-adaptive-testing-clinical00504nas a2200133 4500008003900000245011400039210006900153300001200222490000700234100001900241700001800260700002400278856006800302 2013 d00aA Comparison of Exposure Control Procedures in CAT Systems Based on Different Measurement Models for Testlets0 aComparison of Exposure Control Procedures in CAT Systems Based o a113-1350 v261 aBoyd, Aimee, M1 aDodd, Barbara1 aFitzpatrick, Steven uhttp://www.tandfonline.com/doi/abs/10.1080/08957347.2013.76543401640nas a2200157 4500008003900000245007600039210006900115300001200184490000700196520114800203100002301351700001801374700001601392700002101408856005301429 2013 d00aA Comparison of Exposure Control Procedures in CATs Using the 3PL Model0 aComparison of Exposure Control Procedures in CATs Using the 3PL  a857-8740 v733 a

This study compares the progressive-restricted standard error (PR-SE) exposure control procedure to three commonly used procedures in computerized adaptive testing, the randomesque, Sympson–Hetter (SH), and no exposure control methods. The performance of these four procedures is evaluated using the three-parameter logistic model under the manipulated conditions of item pool size (small vs. large) and stopping rules (fixed-length vs. variable-length). PR-SE provides the advantage of similar constraints to SH, without the need for a preceding simulation study to execute it. Overall for the large and small item banks, the PR-SE method administered almost all of the items from the item pool, whereas the other procedures administered about 52% or less of the large item bank and 80% or less of the small item bank. The PR-SE yielded the smallest amount of item overlap between tests across conditions and administered fewer items on average than SH. PR-SE obtained these results with similar, and acceptable, measurement precision compared to the other exposure control procedures while vastly improving on item pool usage.

1 aLeroux, Audrey, J.1 aLopez, Myriam1 aHembry, Ian1 aDodd, Barbara, G uhttp://epm.sagepub.com/content/73/5/857.abstract00583nas a2200121 4500008004600000245017700046210006900223300001100292490000600303100001100309700001700320856012400337 2013 Engldish 00aA Comparison of Four Methods for Obtaining Information Functions for Scores From Computerized Adaptive Tests With Normally Distributed Item Difficulties and Discriminations0 aComparison of Four Methods for Obtaining Information Functions f a88-1070 v11 aIto, K1 aSegall, D.O. uhttp://www.iacat.org/content/comparison-four-methods-obtaining-information-functions-scores-computerized-adaptive-tests02198nas a2200145 4500008003900000245007900039210006900118300001100187490000700198520173800205100001501943700001901958700002301977856005202000 2013 d00aDeriving Stopping Rules for Multidimensional Computerized Adaptive Testing0 aDeriving Stopping Rules for Multidimensional Computerized Adapti a99-1220 v373 a

Multidimensional computerized adaptive testing (MCAT) is able to provide a vector of ability estimates for each examinee, which could be used to provide a more informative profile of an examinee’s performance. The current literature on MCAT focuses on the fixed-length tests, which can generate less accurate results for those examinees whose abilities are quite different from the average difficulty level of the item bank when there are only a limited number of items in the item bank. Therefore, instead of stopping the test with a predetermined fixed test length, the authors use a more informative stopping criterion that is directly related to measurement accuracy. Specifically, this research derives four stopping rules that either quantify the measurement precision of the ability vector (i.e., minimum determinant rule [D-rule], minimum eigenvalue rule [E-rule], and maximum trace rule [T-rule]) or quantify the amount of available information carried by each item (i.e., maximum Kullback–Leibler divergence rule [K-rule]). The simulation results showed that all four stopping rules successfully terminated the test when the mean squared error of ability estimation is within a desired range, regardless of examinees’ true abilities. It was found that when using the D-, E-, or T-rule, examinees with extreme abilities tended to have tests that were twice as long as the tests received by examinees with moderate abilities. However, the test length difference with K-rule is not very dramatic, indicating that K-rule may not be very sensitive to measurement precision. In all cases, the cutoff value for each stopping rule needs to be adjusted on a case-by-case basis to find an optimal solution.

1 aWang, Chun1 aChang, Hua-Hua1 aBoughton, Keith, A uhttp://apm.sagepub.com/content/37/2/99.abstract00532nas a2200145 4500008004500000245008500045210006900130300001000199490000600209100001700215700001700232700001700249700001000266856011000276 2013 Engldsh 00aEstimating Measurement Precision in Reduced-Length Multi-Stage Adaptive Testing 0 aEstimating Measurement Precision in ReducedLength MultiStage Ada a67-870 v11 aCrotts, K.M.1 aZenisky, A L1 aSireci, S.G.1 aLi, X uhttp://www.iacat.org/content/estimating-measurement-precision-reduced-length-multi-stage-adaptive-testing01409nas a2200157 4500008003900000245009300039210006900132300001000201490000700211520091300218100002301131700001501154700001701169700001301186856005201199 2013 d00aThe Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing0 aInfluence of Item Calibration Error on VariableLength Computeriz a24-400 v373 a

Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be “tailored” to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends on the item parameter values. However, items are chosen on the basis of their parameter estimates, and capitalization on chance may occur. In this article, the authors investigated the effects of capitalization on chance on test length and classification accuracy in several VL-CAT simulations. The results confirm that capitalization on chance occurs in VL-CAT and has complex effects on test length, ability estimation, and classification accuracy. These results have important implications for the design and implementation of VL-CATs.

1 aPatton, Jeffrey, M1 aYing Cheng1 aYuan, Ke-Hai1 aDiao, Qi uhttp://apm.sagepub.com/content/37/1/24.abstract01277nas a2200133 4500008003900000245006600039210006500105300001200170490000700182520086900189100001301058700001901071856005301090 2013 d00aIntegrating Test-Form Formatting Into Automated Test Assembly0 aIntegrating TestForm Formatting Into Automated Test Assembly a361-3740 v373 a

Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using a simultaneous optimization model is more attractive than any of the current, more time-consuming two-stage processes. The goal of this study was to provide such simultaneous models both for computer-delivered and paper forms, as well as explore their performances relative to two-stage optimization. Empirical examples are presented to show that it is possible to automatically produce fully formatted optimal test forms directly from item pools up to some 2,000 items on a regular PC in realistic times.

1 aDiao, Qi1 aLinden, Wim, J uhttp://apm.sagepub.com/content/37/5/361.abstract00533nas a2200145 4500008004100000245009500041210006900136300001000205490000600215100001900221700001100240700001000251700001300261856011300274 2013 en d00aItem Ordering in Stochastically Curtailed Health Questionnaires With an Observable Outcome0 aItem Ordering in Stochastically Curtailed Health Questionnaires  a38-660 v11 aFinkelman, M D1 aKim, W1 aHe, Y1 aLai, A M uhttp://www.iacat.org/content/item-ordering-stochastically-curtailed-health-questionnaires-observable-outcome01492nas a2200121 4500008003900000245009200039210006900131300001200200490000700212520108000219100001801299856005301317 2013 d00aItem Pocket Method to Allow Response Review and Change in Computerized Adaptive Testing0 aItem Pocket Method to Allow Response Review and Change in Comput a259-2750 v373 a

Most computerized adaptive testing (CAT) programs do not allow test takers to review and change their responses because it could seriously deteriorate the efficiency of measurement and make tests vulnerable to manipulative test-taking strategies. Several modified testing methods have been developed that provide restricted review options while limiting the trade-off in CAT efficiency. The extent to which these methods provided test takers with options to review test items, however, still was quite limited. This study proposes the item pocket (IP) method, a new testing approach that allows test takers greater flexibility in changing their responses by eliminating restrictions that prevent them from moving across test sections to review their answers. A series of simulations were conducted to evaluate the robustness of the IP method against various manipulative test-taking strategies. Findings and implications of the study suggest that the IP method may be an effective solution for many CAT programs when the IP size and test time limit are properly set.

1 aHan, Kyung, T uhttp://apm.sagepub.com/content/37/4/259.abstract01220nas a2200133 4500008003900000022001400039245003600053210003600089300001400125490000700139520088200146100001701028856004101045 2013 d a1745-398400aLongitudinal Multistage Testing0 aLongitudinal Multistage Testing a447–4680 v503 a

This article introduces longitudinal multistage testing (lMST), a special form of multistage testing (MST), as a method for adaptive testing in longitudinal large-scale studies. In lMST designs, test forms of different difficulty levels are used, whereas the values on a pretest determine the routing to these test forms. Since lMST allows for testing in paper and pencil mode, lMST may represent an alternative to conventional testing (CT) in assessments for which other adaptive testing designs are not applicable. In this article the performance of lMST is compared to CT in terms of test targeting as well as bias and efficiency of ability and change estimates. Using a simulation study, the effect of the stability of ability across waves, the difficulty level of the different test forms, and the number of link items between the test forms were investigated.

1 aPohl, Steffi uhttp://dx.doi.org/10.1111/jedm.1202801865nas a2200121 4500008003900000245012200039210006900161300001400230490000700244520142300251100001501674856005401689 2013 d00aMutual Information Item Selection Method in Cognitive Diagnostic Computerized Adaptive Testing With Short Test Length0 aMutual Information Item Selection Method in Cognitive Diagnostic a1017-10350 v733 a

Cognitive diagnostic computerized adaptive testing (CD-CAT) purports to combine the strengths of both CAT and cognitive diagnosis. Cognitive diagnosis models aim at classifying examinees into the correct mastery profile group so as to pinpoint the strengths and weakness of each examinee whereas CAT algorithms choose items to determine those strengths and weakness as efficiently as possible. Most of the existing CD-CAT item selection algorithms are evaluated when test length is relatively long whereas several applications of CD-CAT, such as in interim assessment, require an item selection algorithm that is able to accurately recover examinees’ mastery profile with short test length. In this article, we introduce the mutual information item selection method in the context of CD-CAT and then provide a computationally easier formula to make the method more amenable in real time. Mutual information is then evaluated against common item selection methods, such as Kullback–Leibler information, posterior weighted Kullback–Leibler information, and Shannon entropy. Based on our simulations, mutual information consistently results in nearly the highest attribute and pattern recovery rate in more than half of the conditions. We conclude by discussing how the number of attributes, Q-matrix structure, correlations among the attributes, and item quality affect estimation accuracy.

1 aWang, Chun uhttp://epm.sagepub.com/content/73/6/1017.abstract00637nas a2200181 4500008003900000022001400039245011500053210006900168300001100237490000700248653001800255653002900273653003000302653004200332100002200374700001800396856004100414 2013 d a1745-399200aThe Philosophical Aspects of IRT Equating: Modeling Drift to Evaluate Cohort Growth in Large-Scale Assessments0 aPhilosophical Aspects of IRT Equating Modeling Drift to Evaluate a2–140 v3210acohort growth10aconstruct-relevant drift10aevaluation of scale drift10aphilosophical aspects of IRT equating1 aTaherbhai, Husein1 aSeo, Daeryong uhttp://dx.doi.org/10.1111/emip.1200001599nas a2200145 4500008003900000245010600039210006900145300001200214490000700226520111100233100002001344700001801364700001801382856005301400 2013 d00aThe Random-Threshold Generalized Unfolding Model and Its Application of Computerized Adaptive Testing0 aRandomThreshold Generalized Unfolding Model and Its Application  a179-2000 v373 a

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs Sampler) freeware, which adopts a Bayesian approach for estimation. A series of simulations was conducted to evaluate the parameter recovery of the new model and the consequences of ignoring the randomness in thresholds. The results showed that the parameters of RTGUM were recovered fairly well and that ignoring the randomness in thresholds led to biased estimates. Computerized adaptive testing was also implemented on RTGUM, where the Fisher information criterion was used for item selection and the maximum a posteriori method was used for ability estimation. The simulation study showed that the longer the test length, the smaller the randomness in thresholds, and the more categories in an item, the more precise the ability estimates would be.

1 aWang, Wen-Chung1 aLiu, Chen-Wei1 aWu, Shiu-Lien uhttp://apm.sagepub.com/content/37/3/179.abstract00516nas a2200121 4500008004100000245009900041210006900140260002300209100001200232700001500244700001500259856012000274 2013 eng d00aReporting differentiated literacy results in PISA by using multidimensional adaptive testing. 0 aReporting differentiated literacy results in PISA by using multi bDodrecht: Springer1 aFrey, A1 aSeitz, N-N1 aKröhne, U uhttp://www.iacat.org/content/reporting-differentiated-literacy-results-pisa-using-multidimensional-adaptive-testing01630nas a2200157 4500008003900000245010100039210006900140300001200209490000700221520111200228100001501340700001601355700001901371700002501390856005701415 2013 d00aA Semiparametric Model for Jointly Analyzing Response Times and Accuracy in Computerized Testing0 aSemiparametric Model for Jointly Analyzing Response Times and Ac a381-4170 v383 a

The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees’ responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the advantage of conciseness, but may suffer from reduced flexibility to fit real data. We propose a semiparametric approach, specifically, the Cox proportional hazards model with a latent speed covariate to model the RTs, embedded within the hierarchical framework proposed by van der Linden to model the RTs and response accuracy simultaneously. This semiparametric approach combines the flexibility of nonparametric modeling and the brevity and interpretability of the parametric modeling. A Markov chain Monte Carlo method for parameter estimation is given and may be used with sparse data obtained by computerized adaptive testing. Both simulation studies and real data analysis are carried out to demonstrate the applicability of the new model.

1 aWang, Chun1 aFan, Zhewen1 aChang, Hua-Hua1 aDouglas, Jeffrey, A. uhttp://jeb.sagepub.com/cgi/content/abstract/38/4/38101189nas a2200133 4500008003900000245003700039210003700076300001200113490000700125520082900132100001900961700001800980856005700998 2013 d00aSpeededness and Adaptive Testing0 aSpeededness and Adaptive Testing a418-4380 v383 a

Two simple constraints on the item parameters in a response–time model are proposed to control the speededness of an adaptive test. As the constraints are additive, they can easily be included in the constraint set for a shadow-test approach (STA) to adaptive testing. Alternatively, a simple heuristic is presented to control speededness in plain adaptive testing without any constraints. Both types of control are easy to implement and do not require any other real-time parameter estimation during the test than the regular update of the test taker’s ability estimate. Evaluation of the two approaches using simulated adaptive testing showed that the STA was especially effective. It guaranteed testing times that differed less than 10 seconds from a reference test across a variety of conditions.

1 aLinden, Wim, J1 aXiong, Xinhui uhttp://jeb.sagepub.com/cgi/content/abstract/38/4/41801575nas a2200145 4500008003900000245008500039210006900124300001200193490000700205520109100212100002501303700002701328700002101355856005301376 2013 d00aUncertainties in the Item Parameter Estimates and Robust Automated Test Assembly0 aUncertainties in the Item Parameter Estimates and Robust Automat a123-1390 v373 a

Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values, and uncertainty is not taken into account. As a consequence, resulting tests might be off target or less informative than expected. In this article, the process of parameter estimation is described to provide insight into the causes of uncertainty in the item parameters. The consequences of uncertainty are studied. Besides, an alternative automated test assembly algorithm is presented that is robust against uncertainties in the data. Several numerical examples demonstrate the performance of the robust test assembly algorithm, and illustrate the consequences of not taking this uncertainty into account. Finally, some recommendations about the use of robust test assembly and some directions for further research are given.

1 aVeldkamp, Bernard, P1 aMatteucci, Mariagiulia1 aJong, Martijn, G uhttp://apm.sagepub.com/content/37/2/123.abstract01716nas a2200145 4500008003900000245008600039210006900125300001200194490000700206520124600213100001901459700002001478700001901498856005301517 2013 d00aVariable-Length Computerized Adaptive Testing Based on Cognitive Diagnosis Models0 aVariableLength Computerized Adaptive Testing Based on Cognitive  a563-5820 v373 a

Interest in developing computerized adaptive testing (CAT) under cognitive diagnosis models (CDMs) has increased recently. CAT algorithms that use a fixed-length termination rule frequently lead to different degrees of measurement precision for different examinees. Fixed precision, in which the examinees receive the same degree of measurement precision, is a major advantage of CAT over nonadaptive testing. In addition to the precision issue, test security is another important issue in practical CAT programs. In this study, the authors implemented two termination criteria for the fixed-precision rule and evaluated their performance under two popular CDMs using simulations. The results showed that using the two criteria with the posterior-weighted Kullback–Leibler information procedure for selecting items could achieve the prespecified measurement precision. A control procedure was developed to control item exposure and test overlap simultaneously among examinees. The simulation results indicated that in contrast to no method of controlling exposure, the control procedure developed in this study could maintain item exposure and test overlap at the prespecified level at the expense of only a few more items.

1 aHsu, Chia-Ling1 aWang, Wen-Chung1 aChen, Shu-Ying uhttp://apm.sagepub.com/content/37/7/563.abstract00330nas a2200097 4500008004100000245004100041210003800082260003300120100001200153856006700165 2012 eng d00aAdaptives Testen [Adaptive testing].0 aAdaptives Testen Adaptive testing aBerlinbHeidelberg: Springer1 aFrey, A uhttp://www.iacat.org/content/adaptives-testen-adaptive-testing01744nas a2200145 4500008003900000245009400039210006900133300001200202490000700214520125900221100001901480700002501499700002101524856005301545 2012 d00aBalancing Flexible Constraints and Measurement Precision in Computerized Adaptive Testing0 aBalancing Flexible Constraints and Measurement Precision in Comp a629-6480 v723 a

Managing test specifications—both multiple nonstatistical constraints and flexibly defined constraints—has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT, and the weighted penalty model in balancing multiple flexible constraints and maximizing measurement precision in a fixed-length CAT. The study also addressed the effect of two different test lengths—25 items and 50 items—and of including or excluding the randomesque item exposure control procedure with the three methods, all of which were found effective in selecting items that met flexible test constraints when used in the item selection process for longer tests. When the randomesque method was included to control for item exposure, the weighted penalty model and the flexible modified constrained CAT models performed better than did the constrained CAT procedure in maintaining measurement precision. When no item exposure control method was used in the item selection process, no practical difference was found in the measurement precision of each balancing method.

1 aMoyer, Eric, L1 aGalindo, Jennifer, L1 aDodd, Barbara, G uhttp://epm.sagepub.com/content/72/4/629.abstract01847nas a2200169 4500008004100000245012200041210006900163300001200232490000700244520124800251100001201499700001101511700001401522700001101536700001401547856011601561 2012 eng d00aComparison Between Dichotomous and Polytomous Scoring of Innovative Items in a Large-Scale Computerized Adaptive Test0 aComparison Between Dichotomous and Polytomous Scoring of Innovat a493-5090 v723 a

This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test settings were explored in one real data analysis and two simulation studies when two different polytomous scoring algorithms, automated polytomous scoring and rater-generated polytomous scoring, were applied. For the real data analyses, the ability estimates from dichotomous and polytomous scoring were highly correlated; the classification consistency between different scoring algorithms was nearly perfect. Information distribution changed slightly in the operational item bank. In the two simulation studies comparing each polytomous scoring with dichotomous scoring, the ability estimates resulting from polytomous scoring had slightly higher measurement precision than those resulting from dichotomous scoring. The practical impact related to classification decision was minor because of the extremely small number of items that could be scored polytomously in this current study.

1 aJiao, H1 aLiu, J1 aHaynie, K1 aWoo, A1 aGorham, J uhttp://www.iacat.org/content/comparison-between-dichotomous-and-polytomous-scoring-innovative-items-large-scale01906nas a2200133 4500008003900000245013200039210006900171300001200240490000700252520142100259100001801680700002101698856005301719 2012 d00aComparison of Exposure Controls, Item Pool Characteristics, and Population Distributions for CAT Using the Partial Credit Model0 aComparison of Exposure Controls Item Pool Characteristics and Po a159-1750 v723 a

This study investigated item exposure control procedures under various combinations of item pool characteristics and ability distributions in computerized adaptive testing based on the partial credit model. Three variables were manipulated: item pool characteristics (120 items for each of easy, medium, and hard item pools), two ability distributions (normally distributed and negatively skewed data), and three exposure control procedures (randomesque procedure, progressive–restricted procedure, and maximum information procedure). A number of measurement precision indexes such as descriptive statistics, correlations between known and estimated ability levels, bias, root mean squared error, and average absolute difference, exposure rates, item usage, and item overlap were computed to assess the impact of matched or nonmatched item pool and ability distributions on the accuracy of ability estimation and the performance of exposure control procedures. As expected, the medium item pool produced better precision of measurement than both the easy and hard item pools. The progressive–restricted procedure performed better in terms of maximum exposure rates, item average overlap, and pool utilization than both the randomesque procedure and the maximum information procedure. The easy item pool with the negatively skewed data as a mismatched condition produced the worst performance.

1 aLee, HwaYoung1 aDodd, Barbara, G uhttp://epm.sagepub.com/content/72/1/159.abstract02776nas a2200229 4500008004100000022001400041245015400055210006900209260000900278300000800287490000700295520193000302653001802232653003702250653001102287653002702298653002302325653003702348100002002385700001902405856012202424 2012 eng d a1471-228800aComparison of two Bayesian methods to detect mode effects between paper-based and computerized adaptive assessments: a preliminary Monte Carlo study.0 aComparison of two Bayesian methods to detect mode effects betwee c2012 a1240 v123 a

BACKGROUND: Computerized adaptive testing (CAT) is being applied to health outcome measures developed as paper-and-pencil (P&P) instruments. Differences in how respondents answer items administered by CAT vs. P&P can increase error in CAT-estimated measures if not identified and corrected.

METHOD: Two methods for detecting item-level mode effects are proposed using Bayesian estimation of posterior distributions of item parameters: (1) a modified robust Z (RZ) test, and (2) 95% credible intervals (CrI) for the CAT-P&P difference in item difficulty. A simulation study was conducted under the following conditions: (1) data-generating model (one- vs. two-parameter IRT model); (2) moderate vs. large DIF sizes; (3) percentage of DIF items (10% vs. 30%), and (4) mean difference in θ estimates across modes of 0 vs. 1 logits. This resulted in a total of 16 conditions with 10 generated datasets per condition.

RESULTS: Both methods evidenced good to excellent false positive control, with RZ providing better control of false positives and with slightly higher power for CrI, irrespective of measurement model. False positives increased when items were very easy to endorse and when there with mode differences in mean trait level. True positives were predicted by CAT item usage, absolute item difficulty and item discrimination. RZ outperformed CrI, due to better control of false positive DIF.

CONCLUSIONS: Whereas false positives were well controlled, particularly for RZ, power to detect DIF was suboptimal. Research is needed to examine the robustness of these methods under varying prior assumptions concerning the distribution of item and person parameters and when data fail to conform to prior assumptions. False identification of DIF when items were very easy to endorse is a problem warranting additional investigation.

10aBayes Theorem10aData Interpretation, Statistical10aHumans10aMathematical Computing10aMonte Carlo Method10aOutcome Assessment (Health Care)1 aRiley, Barth, B1 aCarle, Adam, C uhttp://www.iacat.org/content/comparison-two-bayesian-methods-detect-mode-effects-between-paper-based-and-computerized01663nas a2200097 4500008004500000245007600045210006900121520126100190100001601451856009801467 2012 Engldsh 00aComputerized Adaptive Testing for Student Selection to Higher Education0 aComputerized Adaptive Testing for Student Selection to Higher Ed3 a

The purpose of the present study is to discuss applicability of computerized adaptive testing format as an alternative for current student selection examinations to higher education in Turkey. In the study, first problems associated with current student selection system are given. These problems exerts pressure on students that results in test anxiety, produce measurement experiences that can be criticized, and lessen credibility of student selection system. Next, computerized adaptive test are introduced and advantages they provide are presented. Then results of a study that used two research designs (simulation and live testing) were presented. Results revealed that (i) computerized adaptive format provided a reduction up to 80% in the number of items given to students compared to paper and pencil format of student selection examination, (ii) ability estimations have high reliabilities. Correlations between ability estimations obtained from simulation and traditional format were higher than 0.80. At the end of the study solutions provided by computerized adaptive testing implementation to the current problems were discussed. Also some issues for application of CAT format for student selection examinations in Turkey are given.

1 aKalender, I uhttp://www.iacat.org/content/computerized-adaptive-testing-student-selection-higher-education00479nas a2200109 4500008004100000245007800041210006900119260005000188490001000238100001700248856010400265 2012 eng d00aComputerized adaptive testing in industrial and organizational psychology0 aComputerized adaptive testing in industrial and organizational p aTwente, The NetherlandsbUniversity of Twente0 vPh.D.1 aMakransky, G uhttp://www.iacat.org/content/computerized-adaptive-testing-industrial-and-organizational-psychology01240nas a2200145 4500008003900000245009000039210006900129300001200198490000700210520076800217100001900985700001701004700002001021856005301041 2012 d00aComputerized Adaptive Testing Using a Class of High-Order Item Response Theory Models0 aComputerized Adaptive Testing Using a Class of HighOrder Item Re a689-7060 v363 a

In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage.

1 aHuang, Hung-Yu1 aChen, Po-Hsi1 aWang, Wen-Chung uhttp://apm.sagepub.com/content/36/8/689.abstract01496nas a2200157 4500008003900000022001400039245006400053210006400117300001400181490000700195520101300202100002401215700002001239700002401259856005501283 2012 d a1745-398400aDetecting Local Item Dependence in Polytomous Adaptive Data0 aDetecting Local Item Dependence in Polytomous Adaptive Data a127–1470 v493 a

A rapidly expanding arena for item response theory (IRT) is in attitudinal and health-outcomes survey applications, often with polytomous items. In particular, there is interest in computer adaptive testing (CAT). Meeting model assumptions is necessary to realize the benefits of IRT in this setting, however. Although initial investigations of local item dependence have been studied both for polytomous items in fixed-form settings and for dichotomous items in CAT settings, there have been no publications applying local item dependence detection methodology to polytomous items in CAT despite its central importance to these applications. The current research uses a simulation study to investigate the extension of widely used pairwise statistics, Yen's Q3 Statistic and Pearson's Statistic X2, in this context. The simulation design and results are contextualized throughout with a real item bank of this type from the Patient-Reported Outcomes Measurement Information System (PROMIS).

1 aMislevy, Jessica, L1 aRupp, André, A1 aHarring, Jeffrey, R uhttp://dx.doi.org/10.1111/j.1745-3984.2012.00165.x00541nas a2200181 4500008004500000245006300045210006300108300001400171490000700185100002300192700002000215700002200235700001700257700001600274700001800290700002100308856003000329 2012 Engldsh 00aDevelopment of a computerized adaptive test for depression0 aDevelopment of a computerized adaptive test for depression a1105-11120 v691 aGibbons, Robert, D1 aWeiss, David, J1 aPilkonis, Paul, A1 aFrank, Ellen1 aMoore, Tara1 aKim, Jong Bae1 aKupfer, David, J uWWW.ARCHGENPSYCHIATRY.COM01355nas a2200133 4500008003900000022001400039245010100053210006900154300001400223490000700237520090400244100001801148856005501166 2012 d a1745-398400aAn Efficiency Balanced Information Criterion for Item Selection in Computerized Adaptive Testing0 aEfficiency Balanced Information Criterion for Item Selection in  a225–2460 v493 a

Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation and long-term quality control of CAT. This study proposed a new item selection method using the “efficiency balanced information” criterion to address issues with the maximum Fisher information method and stratification methods. According to the simulation results, the new efficiency balanced information method had desirable advantages over the other studied item selection methods in terms of improving the optimality of CAT assembly and utilizing items with low a-values while eliminating the need for item pool stratification.

1 aHan, Kyung, T uhttp://dx.doi.org/10.1111/j.1745-3984.2012.00173.x01556nas a2200169 4500008003900000245012400039210006900163300001000232490000700242520099400249100001901243700001801262700001801280700001601298700002001314856005201334 2012 d00aAn Empirical Evaluation of the Slip Correction in the Four Parameter Logistic Models With Computerized Adaptive Testing0 aEmpirical Evaluation of the Slip Correction in the Four Paramete a75-870 v363 a

In a selected response test, aberrant responses such as careless errors and lucky guesses might cause error in ability estimation because these responses do not actually reflect the knowledge that examinees possess. In a computerized adaptive test (CAT), these aberrant responses could further cause serious estimation error due to dynamic item administration. To enhance the robust performance of CAT against aberrant responses, Barton and Lord proposed the four-parameter logistic (4PL) item response theory (IRT) model. However, most studies relevant to the 4PL IRT model were conducted based on simulation experiments. This study attempts to investigate the performance of the 4PL IRT model as a slip-correction mechanism with an empirical experiment. The results showed that the 4PL IRT model could not only reduce the problematic underestimation of the examinees’ ability introduced by careless mistakes in practical situations but also improve measurement efficiency.

1 aYen, Yung-Chin1 aHo, Rong-Guey1 aLaio, Wen-Wei1 aChen, Li-Ju1 aKuo, Ching-Chin uhttp://apm.sagepub.com/content/36/2/75.abstract00517nas a2200109 4500008004500000245012600045210006900171100001700240700001900257700001600276856011500292 2012 Engldsh 00aImproving personality facet scores with multidimensional computerized adaptive testing: An illustration with the NEO PI-R0 aImproving personality facet scores with multidimensional compute1 aMakransky, G1 aMortensen, E L1 aGlas, C A W uhttp://www.iacat.org/content/improving-personality-facet-scores-multidimensional-computerized-adaptive-testing01089nas a2200157 4500008003900000022001400039245007000053210006900123300001400192490000700206520061300213100001600826700001700842700001700859856005500876 2012 d a1745-398400aInvestigating the Effect of Item Position in Computer-Based Tests0 aInvestigating the Effect of Item Position in ComputerBased Tests a362–3790 v493 a

Computer-based tests (CBTs) often use random ordering of items in order to minimize item exposure and reduce the potential for answer copying. Little research has been done, however, to examine item position effects for these tests. In this study, different versions of a Rasch model and different response time models were examined and applied to data from a CBT administration of a medical licensure examination. The models specifically were used to investigate whether item position affected item difficulty and item intensity estimates. Results indicated that the position effect was negligible.

1 aLi, Feiming1 aCohen, Allan1 aShen, Linjun uhttp://dx.doi.org/10.1111/j.1745-3984.2012.00181.x01288nas a2200109 4500008004500000245009100045210006900136490000700205520083400212100001501046856011701061 2012 Engldsh 00aItem Overexposure in Computerized Classification Tests Using Sequential Item Selection0 aItem Overexposure in Computerized Classification Tests Using Seq0 v173 a

Computerized classification tests (CCTs) often use sequential item selection which administers items according to maximizing psychometric information at a cut point demarcating passing and failing scores. This paper illustrates why this method of item selection leads to the overexposure of a significant number of items, and the performances of three different methods for controlling maximum item exposure rates in CCTs are compared. Specifically, the Sympson-Hetter, restricted, and item eligibility methods are examined in two studies realistically simulating different types of CCTs and are evaluated based upon criteria including classification accuracy, the number of items exceeding the desired maximum exposure rate, and test overlap. The pros and cons of each method are discussed from a practical perspective.

1 aHuebner, A uhttp://www.iacat.org/content/item-overexposure-computerized-classification-tests-using-sequential-item-selection00442nas a2200121 4500008003900000245008600039210006900125300001200194490000700206100001800213700002100231856006800252 2012 d00aItem Selection and Ability Estimation Procedures for a Mixed-Format Adaptive Test0 aItem Selection and Ability Estimation Procedures for a MixedForm a305-3260 v251 aHo, Tsung-Han1 aDodd, Barbara, G uhttp://www.tandfonline.com/doi/abs/10.1080/08957347.2012.71468601899nas a2200157 4500008003900000245009300039210007100132300001200203490000700215520139800222100001401620700002101634700001601655700001701671856005301688 2012 d00aA Mixture Rasch Model–Based Computerized Adaptive Test for Latent Class Identification0 aMixture Rasch Model–Based Computerized Adaptive Test for Latent  a469-4930 v363 a

This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback–Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was large, all item selection methods did not differ evidently in terms of accuracy in classifying examinees into different latent classes and estimating latent ability. However, when item separation was small, two methods with class-specific ability estimates performed better than the other two methods based on a single latent ability estimate across all latent classes. The three types of KL information distributions were compared. The KL and the reversed KL information could be the same or different depending on the ability level and the item difficulty difference between latent classes. Although the KL information and the reversed KL information were different at some ability levels and item difficulty difference levels, the use of the KL, the reversed KL, or the adaptive KL information did not affect the results substantially due to the symmetric distribution of item difficulty differences between latent classes in the simulated item pools. Item pool usage and classification convergence points were examined as well.

1 aHong Jiao1 aMacready, George1 aLiu, Junhui1 aCho, Youngmi uhttp://apm.sagepub.com/content/36/6/469.abstract00464nas a2200133 4500008003900000245007200039210006900111300001200180490000700192100002400199700002000223700001900243856006800262 2012 d00aMultistage Computerized Adaptive Testing With Uniform Item Exposure0 aMultistage Computerized Adaptive Testing With Uniform Item Expos a118-1410 v251 aEdwards, Michael, C1 aFlora, David, B1 aThissen, David uhttp://www.tandfonline.com/doi/abs/10.1080/08957347.2012.66036301421nas a2200157 4500008003900000245008000039210006900119300001200188490000700200520092800207100001601135700001801151700002101169700002001190856005301210 2012 d00aPanel Design Variations in the Multistage Test Using the Mixed-Format Tests0 aPanel Design Variations in the Multistage Test Using the MixedFo a574-5880 v723 a

This study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized adaptive test (CAT) conditions provided baseline comparisons. Three passing rate conditions were also included. The various MST conditions using mixed-format tests were constructed properly and performed well. When the levels of TIFs at the first stage were higher, the simulations produced a greater number of correct classifications. CAT with the randomesque-10 procedure yielded comparable results to the MST with increased levels of TIFs. Finally, all MST conditions achieved better test security results compared with CAT’s maximum information conditions.

1 aKim, Jiseon1 aChung, Hyewon1 aDodd, Barbara, G1 aPark, Ryoungsun uhttp://epm.sagepub.com/content/72/4/574.abstract00922nas a2200121 4500008003900000245007500039210006900114300001200183490000700195520052700202100001800729856005300747 2012 d00aThe Problem of Bias in Person Parameter Estimation in Adaptive Testing0 aProblem of Bias in Person Parameter Estimation in Adaptive Testi a255-2700 v363 a

It is shown that deviations of estimated from true values of item difficulty parameters, caused for example by item calibration errors, the neglect of randomness of item difficulty parameters, testlet effects, or rule-based item generation, can lead to systematic bias in point estimation of person parameters in the context of adaptive testing. This effect occurs even when the errors of the item difficulty parameters are themselves unbiased. Analytical calculations as well as simulation studies are discussed.

1 aDoebler, Anna uhttp://apm.sagepub.com/content/36/4/255.abstract01222nas a2200157 4500008003900000245013900039210006900178300001200247490000700259520066600266100002100932700001900953700001500972700002400987856005301011 2012 d00aOn the Reliability and Validity of a Numerical Reasoning Speed Dimension Derived From Response Times Collected in Computerized Testing0 aReliability and Validity of a Numerical Reasoning Speed Dimensio a245-2630 v723 a

Data from 181 college students were used to assess whether math reasoning item response times in computerized testing can provide valid and reliable measures of a speed dimension. The alternate forms reliability of the speed dimension was .85. A two-dimensional structural equation model suggests that the speed dimension is related to the accuracy of speeded responses. Speed factor scores were significantly correlated with performance on the ACT math scale. Results suggest that the speed dimension underlying response times can be reliably measured and that the dimension is related to the accuracy of performance under the pressure of time limits.

1 aDavison, Mark, L1 aSemmes, Robert1 aHuang, Lan1 aClose, Catherine, N uhttp://epm.sagepub.com/content/72/2/245.abstract01281nas a2200133 4500008003900000245009500039210006900134300001200203490000700215520083800222100001801060700001601078856005301094 2012 d00aA Stochastic Method for Balancing Item Exposure Rates in Computerized Classification Tests0 aStochastic Method for Balancing Item Exposure Rates in Computeri a181-1880 v363 a

Computerized classification tests (CCTs) classify examinees into categories such as pass/fail, master/nonmaster, and so on. This article proposes the use of stochastic methods from sequential analysis to address item overexposure, a practical concern in operational CCTs. Item overexposure is traditionally dealt with in CCTs by the Sympson-Hetter (SH) method, but this method is unable to restrict the exposure of the most informative items to the desired level. The authors’ new method of stochastic item exposure balance (SIEB) works in conjunction with the SH method and is shown to greatly reduce the number of overexposed items in a pool and improve overall exposure balance while maintaining classification accuracy comparable with using the SH method alone. The method is demonstrated using a simulation study.

1 aHuebner, Alan1 aLi, Zhushan uhttp://apm.sagepub.com/content/36/3/181.abstract01281nas a2200133 4500008003900000245009500039210006900134300001200203490000700215520083800222100001801060700001601078856005301094 2012 d00aA Stochastic Method for Balancing Item Exposure Rates in Computerized Classification Tests0 aStochastic Method for Balancing Item Exposure Rates in Computeri a181-1880 v363 a

Computerized classification tests (CCTs) classify examinees into categories such as pass/fail, master/nonmaster, and so on. This article proposes the use of stochastic methods from sequential analysis to address item overexposure, a practical concern in operational CCTs. Item overexposure is traditionally dealt with in CCTs by the Sympson-Hetter (SH) method, but this method is unable to restrict the exposure of the most informative items to the desired level. The authors’ new method of stochastic item exposure balance (SIEB) works in conjunction with the SH method and is shown to greatly reduce the number of overexposed items in a pool and improve overall exposure balance while maintaining classification accuracy comparable with using the SH method alone. The method is demonstrated using a simulation study.

1 aHuebner, Alan1 aLi, Zhushan uhttp://apm.sagepub.com/content/36/3/181.abstract00556nas a2200133 4500008004500000022001400045245012600059210006900185300000900254490000600263100001500269700001400284856012400298 2012 Engldsh  a2165-659200aTermination Criteria in Computerized Adaptive Tests: Do Variable-Length CATs Provide Efficient and Effective Measurement?0 aTermination Criteria in Computerized Adaptive Tests Do VariableL a1-180 v11 aBabcock, B1 aWeiss, DJ uhttp://www.iacat.org/content/termination-criteria-computerized-adaptive-tests-do-variable-length-cats-provide-efficient00627nas a2200169 4500008004100000245008900041210006900130260001200199653000800211653002500219653002700244653002100271653001200292100002300304700001600327856011400343 2011 eng d00aAdaptive Item Calibration and Norming: Unique Considerations of a Global Deployment0 aAdaptive Item Calibration and Norming Unique Considerations of a c10/201110aCAT10acommon item equating10aFigural Reasoning Test10aitem calibration10anorming1 aSchwall, Alexander1 aSinar, Evan uhttp://www.iacat.org/content/adaptive-item-calibration-and-norming-%0Bunique-considerations-global-deployment00493nas a2200133 4500008003900000245008200039210006900121300001400190490000800204100001300212700001600225700001500241856010300256 2011 d00aApplying computerized adaptive testing to the CES-D scale: A simulation study0 aApplying computerized adaptive testing to the CESD scale A simul a147–1550 v1881 aSmits, N1 aCuijpers, P1 aStraten, A uhttp://www.iacat.org/content/applying-computerized-adaptive-testing-ces-d-scale-simulation-study-001666nas a2200169 4500008004100000020004100041022001300082245008200095210006900177250001500246260001000261520108000271100001301351700001601364700001501380856010101395 2011 Eng d a0165-1781 (Print)0165-1781 (Linking) a2120866000aApplying computerized adaptive testing to the CES-D scale: A simulation study0 aApplying computerized adaptive testing to the CESD scale A simul a2011/01/07 cJan 33 aIn this paper we studied the appropriateness of developing an adaptive version of the Center of Epidemiological Studies-Depression (CES-D, Radloff, 1977) scale. Computerized Adaptive Testing (CAT) involves the computerized administration of a test in which each item is dynamically selected from a pool of items until a pre-specified measurement precision is reached. Two types of analyses were performed using the CES-D responses of a large sample of adolescents (N=1392). First, it was shown that the items met the psychometric requirements needed for CAT. Second, CATs were simulated by using the existing item responses as if they had been collected adaptively. CATs selecting only a small number of items gave results which, in terms of depression measurement and criterion validity, were only marginally different from the results of full CES-D assessment. It was concluded that CAT is a very fruitful way of improving the efficiency of the CES-D questionnaire. The discussion addresses the strengths and limitations of the application of CAT in mental health research.1 aSmits, N1 aCuijpers, P1 aStraten, A uhttp://www.iacat.org/content/applying-computerized-adaptive-testing-ces-d-scale-simulation-study02030nas a2200133 4500008003900000245007700039210006900116250001000185300000900195490001100204520156600215100001401781856010101795 2011 d00aBetter Data From Better Measurements Using Computerized Adaptive Testing0 aBetter Data From Better Measurements Using Computerized Adaptive aNo. 1 a1-270 vVol. 23 aThe process of constructing a fixed-length conventional test frequently focuses on maximizing internal consistency reliability by selecting test items that are of average difficulty and high discrimination (a ―peaked‖ test). The effect of constructing such a test, when viewed from the perspective of item response theory, is test scores that are precise for examinees whose trait levels are near the point at which the test is peaked; as examinee trait levels deviate from the mean, the precision of their scores decreases substantially. Results of a small simulation study demonstrate that when peaked tests are ―off target‖ for an examinee, their scores are biased and have spuriously high standard deviations, reflecting substantial amounts of error. These errors can reduce the correlations of these kinds of scores with other variables and adversely affect the results of standard statistical tests. By contrast, scores from adaptive tests are essentially unbiased and have standard deviations that are much closer to true values. Basic concepts of adaptive testing are introduced and fully adaptive computerized tests (CATs) based on IRT are described. Several examples of response records from CATs are discussed to illustrate how CATs function. Some operational issues, including item exposure, content balancing, and enemy items are also briefly discussed. It is concluded that because CAT constructs a unique test for examinee, scores from CATs will be more precise and should provide better data for social science research and applications.1 aWeiss, DJ uhttp://www.iacat.org/content/better-data-better-measurements-using-computerized-adaptive-testing00494nas a2200121 4500008004100000245009500041210006900136653001800205653000800223653000900231100001900240856011300259 2011 eng d00aBuilding Affordable CD-CAT Systems for Schools To Address Today's Challenges In Assessment0 aBuilding Affordable CDCAT Systems for Schools To Address Todays 10aaffordability10aCAT10acost1 aChang, Hua-Hua uhttp://www.iacat.org/content/building-affordable-cd-cat-systems-schools-address-todays-challenges-assessment01165nas a2200157 4500008004100000245005700041210005600098520065200154653002100806653003400827653001500861653002500876100001300901700001500914856007800929 2011 eng d00acatR: An R Package for Computerized Adaptive Testing0 acatR An R Package for Computerized Adaptive Testing3 a

Computerized adaptive testing (CAT) is an active current research field in psychometrics and educational measurement. However, there is very little software available to handle such adaptive tasks. The R package catR was developed to perform adaptive testing with as much flexibility as possible, in an attempt to provide a developmental and testing platform to the interested user. Several item-selection rules and ability estimators are implemented. The item bank can be provided by the user or randomly generated from parent distributions of item parameters. Three stopping rules are available. The output can be graphically displayed.

10acomputer program10acomputerized adaptive testing10aEstimation10aItem Response Theory1 aMagis, D1 aRaîche, G uhttp://www.iacat.org/content/catr-r-package-computerized-adaptive-testing01223nas a2200121 4500008003900000245007300039210006900112300001200181490000700193520082900200100001901029856005301048 2011 d00aA Comment on Early Student Blunders on Computer-Based Adaptive Tests0 aComment on Early Student Blunders on ComputerBased Adaptive Test a165-1740 v353 a

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that the ‘‘bias’’ can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not from adaptive testing. Because very proficient test takers rarely err on items of middle difficulty, the so-called bias is one of selective data analysis. Furthermore, the apparently large score penalty for one error on an otherwise perfect response pattern is shown to result from the relative stretching of the IRT scale at very high and very low proficiencies. The recommended use of a four-parameter IRT model is shown to have drawbacks.

1 aGreen, Bert, F uhttp://apm.sagepub.com/content/35/2/165.abstract01233nas a2200121 4500008004500000245007300045210006900118300001200187490000700199520079700206100001401003856009401017 2011 Engldsh 00aA Comment on Early Student Blunders on Computer-Based Adaptive Tests0 aComment on Early Student Blunders on ComputerBased Adaptive Test a165-1740 v353 a

This article refutes a recent claim that computer-based tests produce biased scores for very proficient test takers who make mistakes on one or two initial items and that they can be reduced by using a four-parameter IRT model. Because the same effect occurs with pattern scores on nonadaptive tests, the effect results from IRT scoring, not from adaptive testing. Because very proficient test takers rarely err on items of middle difficulty, the so-called bias is one of selective data analysis. Furthermore, the apparently large score penalty for one error on an otherwise perfect response pattern is shown to result from the relative stretching of the IRT scale at very high and very low proficiencies. The recommended use of a four-parameter IRT model is shown to have drawbacks.

1 aGreen, BF uhttp://www.iacat.org/content/comment-early-student-blunders-computer-based-adaptive-tests01006nas a2200121 4500008004500000245008100045210006900126490000700195520054900202100001600751700001100767856010600778 2011 Engldsh 00aComputer adaptive testing for small scale programs and instructional systems0 aComputer adaptive testing for small scale programs and instructi0 v123 a

This study investigates measurement decision theory (MDT) as an underlying model for computer adaptive testing when the goal is to classify examinees into one of a finite number of groups. The first analysis compares MDT with a popular item response theory model and finds little difference in terms of the percentage of correct classifications. The second analysis examines the number of examinees needed to calibrate MDT item parameters and finds accurate classifications even with calibration sample sizes as small as 100 examinees.

1 aRudner, L M1 aGuo, F uhttp://www.iacat.org/content/computer-adaptive-testing-small-scale-programs-and-instructional-systems01960nas a2200193 4500008004100000020001400041245009500055210006900150300001200219490000700231520131000238100001501548700001801563700001701581700001401598700001301612700001901625856012201644 2011 eng d a0022-389100aComputerized adaptive assessment of personality disorder: Introducing the CAT–PD project0 aComputerized adaptive assessment of personality disorder Introdu a380-3890 v933 aAssessment of personality disorders (PD) has been hindered by reliance on the problematic categorical model embodied in the most recent Diagnostic and Statistical Model of Mental Disorders (DSM), lack of consensus among alternative dimensional models, and inefficient measurement methods. This article describes the rationale for and early results from a multiyear study funded by the National Institute of Mental Health that was designed to develop an integrative and comprehensive model and efficient measure of PD trait dimensions. To accomplish these goals, we are in the midst of a 5-phase project to develop and validate the model and measure. The results of Phase 1 of the project—which was focused on developing the PD traits to be assessed and the initial item pool—resulted in a candidate list of 59 PD traits and an initial item pool of 2,589 items. Data collection and structural analyses in community and patient samples will inform the ultimate structure of the measure, and computerized adaptive testing will permit efficient measurement of the resultant traits. The resultant Computerized Adaptive Test of Personality Disorder (CAT–PD) will be well positioned as a measure of the proposed DSM–5 PD traits. Implications for both applied and basic personality research are discussed.1 aSimms, L J1 aGoldberg, L R1 aRoberts, J E1 aWatson, D1 aWelte, J1 aRotterman, J H uhttp://www.iacat.org/content/computerized-adaptive-assessment-personality-disorder-introducing-cat%E2%80%93pd-project00466nas a2200121 4500008003900000245009900039210006900138300001200207490000700219100001900226700003100245856006800276 2011 d00aComputerized Adaptive Testing with the Zinnes and Griggs Pairwise Preference Ideal Point Model0 aComputerized Adaptive Testing with the Zinnes and Griggs Pairwis a231-2470 v111 aStark, Stephen1 aChernyshenko, Oleksandr, S uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2011.56145901379nas a2200133 4500008003900000245008500039210006900124300001200193490000700205520094200212100002001154700001801174856005301192 2011 d00aComputerized Classification Testing Under the Generalized Graded Unfolding Model0 aComputerized Classification Testing Under the Generalized Graded a114-1280 v713 a

The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree—disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut score/sequential probability ratio test method and (b) evaluated their accuracy and efficiency in classification through simulations. The results indicated that both methods were very accurate and efficient. The more points each item had and the fewer the classification categories, the more accurate and efficient the classification would be. However, the latter method may yield a very low accuracy in dichotomous items with a short maximum test length. Thus, if it is to be used to classify examinees with dichotomous items, the maximum text length should be increased.

1 aWang, Wen-Chung1 aLiu, Chen-Wei uhttp://epm.sagepub.com/content/71/1/114.abstract01976nas a2200133 4500008003900000245011600039210006900155300001200224490000700236520150500243100002001748700002101768856005301789 2011 d00aComputerized Classification Testing Under the One-Parameter Logistic Response Model With Ability-Based Guessing0 aComputerized Classification Testing Under the OneParameter Logis a925-9410 v713 a

The one-parameter logistic model with ability-based guessing (1PL-AG) has been recently developed to account for effect of ability on guessing behavior in multiple-choice items. In this study, the authors developed algorithms for computerized classification testing under the 1PL-AG and conducted a series of simulations to evaluate their performances. Four item selection methods (the Fisher information, the Fisher information with a posterior distribution, the progressive method, and the adjusted progressive method) and two termination criteria (the ability confidence interval [ACI] method and the sequential probability ratio test [SPRT]) were developed. In addition, the Sympson–Hetter online method with freeze (SHOF) was implemented for item exposure control. Major results include the following: (a) when no item exposure control was made, all the four item selection methods yielded very similar correct classification rates, but the Fisher information method had the worst item bank usage and the highest item exposure rate; (b) SHOF can successfully maintain the item exposure rate at a prespecified level, without compromising substantial accuracy and efficiency in classification; (c) once SHOF was implemented, all the four methods performed almost identically; (d) ACI appeared to be slightly more efficient than SPRT; and (e) in general, a higher weight of ability in guessing led to a slightly higher accuracy and efficiency, and a lower forced classification rate.

1 aWang, Wen-Chung1 aHuang, Sheng-Yun uhttp://epm.sagepub.com/content/71/6/925.abstract01695nas a2200217 4500008004100000020004600041245012100087210006900208250001500277300001100292490000700303520094700310100001701257700001301274700001601287700001001303700001201313700001601325700001801341856011801359 2011 eng d a1541-3144 (Electronic)0194-2638 (Linking)00aContent range and precision of a computer adaptive test of upper extremity function for children with cerebral palsy0 aContent range and precision of a computer adaptive test of upper a2010/10/15 a90-1020 v313 aThis article reports on the content range and measurement precision of an upper extremity (UE) computer adaptive testing (CAT) platform of physical function in children with cerebral palsy. Upper extremity items representing skills of all abilities were administered to 305 parents. These responses were compared with two traditional standardized measures: Pediatric Outcomes Data Collection Instrument and Functional Independence Measure for Children. The UE CAT correlated strongly with the upper extremity component of these measures and had greater precision when describing individual functional ability. The UE item bank has wider range with items populating the lower end of the ability spectrum. This new UE item bank and CAT have the capability to quickly assess children of all ages and abilities with good precision and, most importantly, with items that are meaningful and appropriate for their age and level of physical function.1 aMontpetit, K1 aHaley, S1 aBilodeau, N1 aNi, P1 aTian, F1 aGorton, 3rd1 aMulcahey, M J uhttp://www.iacat.org/content/content-range-and-precision-computer-adaptive-test-upper-extremity-function-children01633nas a2200145 4500008004100000245005200041210005000093260001200143520119300155653000801348653001601356653002001372100002301392856007201415 2011 eng d00aContinuous Testing (an avenue for CAT research)0 aContinuous Testing an avenue for CAT research c10/20113 a

Publishing an Adaptive Test

Problems with Publishing

Research Questions

10aCAT10aitem filter10aitem filtration1 aKingsbury, Gage, G uhttp://www.iacat.org/content/continuous-testing-avenue-cat-research01600nas a2200121 4500008004500000245011000045210006900155490000700224520114200231100001901373700001401392856007201406 2011 Engldsh 00aCreating a K-12 Adaptive Test: Examining the Stability of Item Parameter Estimates and Measurement Scales0 aCreating a K12 Adaptive Test Examining the Stability of Item Par0 v123 a

Development of adaptive tests used in K-12 settings requires the creation of stable measurement scales to measure the growth of individual students from one grade to the next, and to measure change in groups from one year to the next. Accountability systems
like No Child Left Behind require stable measurement scales so that accountability has meaning across time. This study examined the stability of the measurement scales used with the Measures of Academic Progress. Difficulty estimates for test questions from the reading and mathematics scales were examined over a period ranging from 7 to 22 years. Results showed high correlations between item difficulty estimates from the time at which they where originally calibrated and the current calibration. The average drift in item difficulty estimates was less than .01 standard deviations. The average impact of change in item difficulty estimates was less than the smallest reported difference on the score scale for two actual tests. The findings of the study indicate that an IRT scale can be stable enough to allow consistent measurement of student achievement.

1 aKingsbury, G G1 aWise, S L uhttp://www.testpublishers.org/journal-of-applied-testing-technology02592nas a2200313 4500008004100000020004600041245011200087210006900199250001500268260001900283300000700302490000600309520160100315100001901916700001801935700001701953700001801970700001701988700001402005700001602019700001502035700001402050700002602064700001602090700001302106700001502119700001902134856012502153 2011 Eng d a1477-7525 (Electronic)1477-7525 (Linking)00aCross-cultural development of an item list for computer-adaptive testing of fatigue in oncological patients0 aCrosscultural development of an item list for computeradaptive t a2011/03/31 cMarch 29, 2011 a100 v93 aABSTRACT: INTRODUCTION: Within an ongoing project of the EORTC Quality of Life Group, we are developing computerized adaptive test (CAT) measures for the QLQ-C30 scales. These new CAT measures are conceptualised to reflect the same constructs as the QLQ-C30 scales. Accordingly, the Fatigue-CAT is intended to capture physical and general fatigue. METHODS: The EORTC approach to CAT development comprises four phases (literature search, operationalisation, pre-testing, and field testing). Phases I-III are described in detail in this paper. A literature search for fatigue items was performed in major medical databases. After refinement through several expert panels, the remaining items were used as the basis for adapting items and/or formulating new items fitting the EORTC item style. To obtain feedback from patients with cancer, these English items were translated into Danish, French, German, and Spanish and tested in the respective countries. RESULTS: Based on the literature search a list containing 588 items was generated. After a comprehensive item selection procedure focusing on content, redundancy, item clarity and item difficulty a list of 44 fatigue items was generated. Patient interviews (n=52) resulted in 12 revisions of wording and translations. DISCUSSION: The item list developed in phases I-III will be further investigated within a field-testing phase (IV) to examine psychometric characteristics and to fit an item response theory model. The Fatigue CAT based on this item bank will provide scores that are backward-compatible to the original QLQ-C30 fatigue scale.1 aGiesinger, J M1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aArraras, J I1 aConroy, T1 aGamper, E M1 aKemmler, G1 aKing, M T1 aOberguggenberger, A S1 aVelikova, G1 aYoung, T1 aHolzner, B1 aEortc-Qlg, E O uhttp://www.iacat.org/content/cross-cultural-development-item-list-computer-adaptive-testing-fatigue-oncological-patients01889nas a2200169 4500008004500000245015100045210006900196490000700265520128400272100001601556700001701572700001401589700001501603700001501618700001401633856007201647 2011 Engldsh 00aDesign of a Computer-Adaptive Test to Measure English Literacy and Numeracy in the Singapore Workforce: Considerations, Benefits, and Implications0 aDesign of a ComputerAdaptive Test to Measure English Literacy an0 v123 a

A computer adaptive test CAT) is a delivery methodology that serves the larger goals of the assessment system in which it is embedded. A thorough analysis of the assessment system for which a CAT is being designed is critical to ensure that the delivery platform is appropriate and addresses all relevant complexities. As such, a CAT engine must be designed to conform to the
validity and reliability of the overall system. This design takes the form of adherence to the assessment goals and objectives of the adaptive assessment system. When the assessment is adapted for use in another country, consideration must be given to any necessary revisions including content differences. This article addresses these considerations while drawing, in part, on the process followed in the development of the CAT delivery system designed to test English language workplace skills for the Singapore Workforce Development Agency. Topics include item creation and selection, calibration of the item pool, analysis and testing of the psychometric properties, and reporting and interpretation of scores. The characteristics and benefits of the CAT delivery system are detailed as well as implications for testing programs considering the use of a
CAT delivery system.

1 aJacobsen, J1 aAckermann, R1 aEgüez, J1 aGanguli, D1 aRickard, P1 aTaylor, L uhttp://www.testpublishers.org/journal-of-applied-testing-technology01231nas a2200193 4500008004100000245009400041210006900135260001200204520052700216653002600743653000800769653000800777653003100785653003200816653003000848100002000878700001900898856012000917 2011 eng d00aDetecting DIF between Conventional and Computerized Adaptive Testing: A Monte Carlo Study0 aDetecting DIF between Conventional and Computerized Adaptive Tes c10/20113 a

A comparison od two procedures, Modified Robust Z and 95% Credible Interval, were compared in a Monte Carlo study. Both procedures evidenced adequate control of false positive DIF results.

10a95% Credible Interval10aCAT10aDIF10adifferential item function10amodified robust Z statistic10aMonte Carlo methodologies1 aRiley, Barth, B1 aCarle, Adam, C uhttp://www.iacat.org/content/detecting-dif-between-conventional-and-computerized-adaptive-testing-monte-carlo-study02037nas a2200109 4500008004100000245008900041210006900130490001000199520159300209100001601802856010901818 2011 eng d00aEffects of Different Computerized Adaptive Testing Strategies of Recovery of Ability0 aEffects of Different Computerized Adaptive Testing Strategies of0 vPh.D.3 a

The purpose of the present study is to compare ability estimations obtained from computerized adaptive testing (CAT) procedure with the paper and pencil test administration results of Student Selection Examination (SSE) science subtest considering different ability estimation methods and test termination rules. There are two phases in the present study. In the first phase, a post-hoc simulation was conducted to find out relationships between examinee ability levels estimated by CAT and paper and pencil test versions of the SSE. Maximum Likelihood Estimation and Expected A Posteriori were used as ability estimation method. Test termination rules were standard error threshold and fixed number of items. Second phase was actualized by implementing a CAT administration to a group of examinees to investigate performance of CAT administration in an environment other than simulated administration. Findings of post-hoc simulations indicated CAT could be implemented by using Expected A Posteriori estimation method with standard error threshold value of 0.30 or higher for SSE. Correlation between ability estimates obtained by CAT and real SSE was found to be 0.95. Mean of number of items given to examinees by CAT is 18.4. Correlation between live CAT and real SSE ability estimations was 0.74. Number of items used for CAT administration is approximately 50% of the items in paper and pencil SSE science subtest. Results indicated that CAT for SSE science subtest provided ability estimations with higher reliability with fewer items compared to paper and pencil format.

1 aKalender, I uhttp://www.iacat.org/content/effects-different-computerized-adaptive-testing-strategies-recovery-ability00937nas a2200133 4500008004100000245006700041210006500108260004700173490000700220520046100227100001800688700001400706856008300720 2011 eng d00aA framework for the development of computerized adaptive tests0 aframework for the development of computerized adaptive tests bPractical Assessment Research & Evaluation0 v163 aA substantial amount of research has been conducted over the past 40 years on technical aspects of computerized adaptive testing (CAT), such as item selection algorithms, item exposure controls, and termination criteria. However, there is little literature providing practical guidance on the development of a CAT. This paper seeks to collate some of the available research methodologies into a general framework for the development of any CAT assessment. 1 aThompson, N A1 aWeiss, DJ uhttp://www.iacat.org/content/framework-development-computerized-adaptive-tests02531nas a2200205 4500008004100000245011900041210006900160260001200229520179400241653000802035653000802043653003402051653003002085653000802115653003102123653001602154653001302170100002002183856012202203 2011 eng d00aFrom Reliability to Validity: Expanding Adaptive Testing Practice to Find the Most Valid Score for Each Test Taker0 aFrom Reliability to Validity Expanding Adaptive Testing Practice c10/20113 a

CAT is an exception to the traditional conception of validity. It is one of the few examples of individualized testing. Item difficulty is tailored to each examinee. The intent, however, is increased efficiency. Focus on reliability (reduced standard error); Equivalence with paper & pencil tests is valued; Validity is enhanced through improved reliability.

How Else Might We Individualize Testing Using CAT?

An ISV-Based View of Validity

Test Event -- An examinee encounters a series of items in a particular context.

CAT Goal: individualize testing to address CIV threats to score validity (i.e., maximize ISV).

Some Research Issues:

10aCAT10aCIV10aconstruct-irrelevant variance10aIndividual Score Validity10aISV10alow test taking motivation10aReliability10avalidity1 aWise, Steven, L uhttp://www.iacat.org/content/reliability-validity-expanding-adaptive-testing-practice-find-most-valid-score-each-test00482nas a2200145 4500008004100000245006100041210005900102653000800161653001600169653001300185100001900198700001600217700002200233856008100255 2011 eng d00aA Heuristic Of CAT Item Selection Procedure For Testlets0 aHeuristic Of CAT Item Selection Procedure For Testlets10aCAT10ashadow test10atestlets1 aChien, Yuehmei1 aShin, David1 aWay, Walter Denny uhttp://www.iacat.org/content/heuristic-cat-item-selection-procedure-testlets00538nas a2200121 4500008004100000245011800041210006900159653000800228653002400236653001100260100002000271856012500291 2011 eng d00aHigh-throughput Health Status Measurement using CAT in the Era of Personal Genomics: Opportunities and Challenges0 aHighthroughput Health Status Measurement using CAT in the Era of10aCAT10ahealth applications10aPROMIS1 aKrishnan, Eswar uhttp://www.iacat.org/content/high-throughput-health-status-measurement-using-cat-era-personal-genomics-opportunities-and00506nas a2200121 4500008003900000245011000039210006900149300001200218490000700230100001200237700001500249856012000264 2011 d00aHypothetical use of multidimensional adaptive testing for the assessment of student achievement in PISA. 0 aHypothetical use of multidimensional adaptive testing for the as a503-5220 v711 aFrey, A1 aSeitz, N-N uhttp://www.iacat.org/content/hypothetical-use-multidimensional-adaptive-testing-assessment-student-achievement-pisa00774nas a2200145 4500008004100000245005700041210005700098260001200155520031700167653001500484100001700499700001300516700001900529856008000548 2011 eng d00aImpact of Item Drift on Candidate Ability Estimation0 aImpact of Item Drift on Candidate Ability Estimation c10/20113 a

For large operational pools, candidate ability estimates appear robust to item drift, especially under conditions that may represent ‘normal’ amounts of drift. Even with ‘extreme’ conditions of drift (e.g., 20% of items drifting 1.00 logits), decision consistency was still high.

10aitem drift1 aHagge, Sarah1 aWoo, Ada1 aDickison, Phil uhttp://www.iacat.org/content/impact-item-drift-candidate-ability-estimation00653nas a2200157 4500008004100000020001400041245015700055210006900212100001800281700001400299700001500313700001600328700001500344700001300359856012300372 2011 eng d a1073-191100aItem banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): depression, anxiety, and anger0 aItem banks for measuring emotional distress from the PatientRepo1 aPilkonis, P A1 aChoi, S W1 aReise, S P1 aStover, A M1 aRiley, W T1 aCella, D uhttp://www.iacat.org/content/item-banks-measuring-emotional-distress-patient-reported-outcomes-measurement-information01700nas a2200121 4500008003900000245009500039210006900134300001000203490000700213520128800220100001801508856005201526 2011 d00aItem Selection Criteria With Practical Constraints for Computerized Classification Testing0 aItem Selection Criteria With Practical Constraints for Computeri a20-360 v713 a

This study compares four item selection criteria for a two-category computerized classification testing: (1) Fisher information (FI), (2) Kullback—Leibler information (KLI), (3) weighted log-odds ratio (WLOR), and (4) mutual information (MI), with respect to the efficiency and accuracy of classification decision using the sequential probability ratio test as well as the extent of item usage. The comparability of the four item selection criteria are examined primarily under three types of item selection conditions: (1) using only the four item selection algorithms, (2) using the four item selection algorithms and content balancing control, and (3) using the four item selection algorithms, content balancing control, and item exposure control. The comparability of the four item selection criteria is also evaluated in two types of proficiency distribution and three levels of indifference region width. The results show that the differences of the four item selection criteria are washed out as more realistic constraints are imposed. Moreover, within two-category classification testing, the use of MI does not necessarily generate greater efficiency than FI, WLOR, and KLI, although MI might seem attractive for its general form of formula in item selection.

1 aLin, Chuan-Ju uhttp://epm.sagepub.com/content/71/1/20.abstract01251nas a2200181 4500008004100000245012100041210006900162260001200231520055600243653003300799653000800832653001900840653003500859100001800894700001600912700002200928856011900950 2011 eng d00aItem Selection Methods based on Multiple Objective Approaches for Classification of Respondents into Multiple Levels0 aItem Selection Methods based on Multiple Objective Approaches fo c10/20113 a

Is it possible to develop new item selection methods which take advantage of the fact that we want to classify into multiple categories? New methods: Taking multiple points on the ability scale into account; Based on multiple objective approaches.

Conclusions

10aadaptive classification test10aCAT10aitem selection10asequential classification test1 aGroen, Maaike1 aEggen, Theo1 aVeldkamp, Bernard uhttp://www.iacat.org/content/item-selection-methods-based-multiple-objective-approaches-classification-respondents00387nas a2200109 4500008003900000245006500039210006400104260001200168490000700180100001800187856007200205 2011 d00aJATT Special Issue on Adaptive Testing: Welcome and Overview0 aJATT Special Issue on Adaptive Testing Welcome and Overview c05/20110 v121 aThompson, N A uhttp://www.testpublishers.org/journal-of-applied-testing-technology00447nas a2200121 4500008004500000245006900045210006900114300001100183490000600194100001400200700001800214856009300232 2011 Engldsh 00aMeasuring Individual Growth With Conventional and Adaptive Tests0 aMeasuring Individual Growth With Conventional and Adaptive Tests a80-1010 v21 aWeiss, DJ1 aVon Minden, S uhttp://www.iacat.org/content/measuring-individual-growth-conventional-and-adaptive-tests01257nas a2200181 4500008004100000245008300041210006900124260001200193520063300205653000800838653002600846653000900872653003500881653001600916653001400932100002300946856010600969 2011 eng d00aMoving beyond Efficiency to Allow CAT to Provide Better Diagnostic Information0 aMoving beyond Efficiency to Allow CAT to Provide Better Diagnost c10/20113 a
Future CATs will provide better diagnostic information to
–Examinees
–Regulators, Educators, Employers
–Test Developers
This goal will be accomplished by
–Smart CATs which collect additional information during the test
–Psychomagic
The time is now for Reporting
10aCAT10adianostic information10aMIRT10aMultiple unidimensional scales10apsychomagic10asmart CAT1 aBontempo, Brian, D uhttp://www.iacat.org/content/moving-beyond-efficiency-allow-cat-provide-better-diagnostic-information01545nas a2200109 4500008004500000245005800045210005400103490000700157520117100164100001501335856008501350 2011 Engldsh 00aNational Tests in Denmark – CAT as a Pedagogic Tool0 aNational Tests in Denmark CAT as a Pedagogic Tool0 v123 a

Testing and test results can be used in different ways. They can be used for regulation and control, but they can also be a pedagogic tool for assessment of student proficiency in order to target teaching, improve learning and facilitate local pedagogical leadership. To serve these purposes the test has to be used for low stakes purposes, and to ensure this, the Danish National test results are made strictly confidential by law. The only test results that are made public are the overall national results. Because of the test design, test results are directly comparable, offering potential for monitoring added value and developing new ways of using test results in a pedagogical context. This article gives the background and status for the development of the Danish national tests, describes what is special about these tests (e.g., Information Technology [IT]-based, 3 tests in 1, adaptive), how the national test are carried out, and what
is tested. Furthermore, it describes strategies for disseminating the results to the pupil, parents, teacher, headmaster and municipality; and how the results can be used by the teacher and headmaster.

1 aWandall, J uhttp://www.iacat.org/content/national-tests-denmark-%E2%80%93-cat-pedagogic-tool00768nas a2200157 4500008004500000245008000045210006900125490000700194520022700201100001500428700001600443700001700459700001600476700001500492856010300507 2011 Engldsh 00aA new adaptive testing algorithm for shortening health literacy assessments0 anew adaptive testing algorithm for shortening health literacy as0 v113 a

 

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3178473/?tool=pmcentrez
1 aKandula, S1 aAncker, J S1 aKaufman, D R1 aCurrie, L M1 aQing, Z -T uhttp://www.iacat.org/content/new-adaptive-testing-algorithm-shortening-health-literacy-assessments01203nas a2200145 4500008003900000245005800039210005600097300001000153490000700163520077300170100001900943700002200962700002100984856005201005 2011 d00aA New Stopping Rule for Computerized Adaptive Testing0 aNew Stopping Rule for Computerized Adaptive Testing a37-530 v713 a

The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared with that of the minimum standard error stopping rule and a modified version of the minimum information stopping rule in a series of simulated adaptive tests, drawn from a number of item pools. Results indicate that the PSER makes efficient use of CAT item pools, administering fewer items when predictive gains in information are small and increasing measurement precision when information is abundant.

1 aChoi, Seung, W1 aGrady, Matthew, W1 aDodd, Barbara, G uhttp://epm.sagepub.com/content/71/1/37.abstract01103nas a2200169 4500008004100000245006600041210006600107260001200173520055300185653002600738653000800764653002100772653001700793653001000810100002200820856009100842 2011 eng d00aOptimal Calibration Designs for Computerized Adaptive Testing0 aOptimal Calibration Designs for Computerized Adaptive Testing c10/20113 a

Optimaztion

How can we exploit the advantages of Balanced Block Design while keeping the logistics manageable?

Homogeneous Designs: Overlap between test booklets as regular as possible

Conclusions:

10abalanced block design10aCAT10aitem calibration10aoptimization10aRasch1 aVerschoor, Angela uhttp://www.iacat.org/content/optimal-calibration-designs-computerized-adaptive-testing01307nas a2200133 4500008004100000245005000041210004800091260001200139520089400151653000801045653003501053100001201088856007301100 2011 eng d00aA Paradigm for Multinational Adaptive Testing0 aParadigm for Multinational Adaptive Testing c10/20113 a

Impact of Issues in “Exported” Adaptive Testing

Goal is construct equivalency in the new environment

Research Questions

10aCAT10amultinational adaptive testing1 aZara, A uhttp://www.iacat.org/content/paradigm-multinational-adaptive-testing01445nas a2200133 4500008003900000245012700039210006900166300001400235490000700249520096400256100001701220700002001237856005401257 2011 d00aPolytomous Adaptive Classification Testing: Effects of Item Pool Size, Test Termination Criterion, and Number of Cutscores0 aPolytomous Adaptive Classification Testing Effects of Item Pool  a1006-10220 v713 a

Computer-adaptive classification tests focus on classifying respondents in different proficiency groups (e.g., for pass/fail decisions). To date, adaptive classification testing has been dominated by research on dichotomous response formats and classifications in two groups. This article extends this line of research to polytomous classification tests for two- and three-group scenarios (e.g., inferior, mediocre, and superior proficiencies). Results of two simulation experiments with generated and real responses (N = 2,000) to established personality scales of different length (12, 20, or 29 items) demonstrate that adaptive item presentations significantly reduce the number of items required to make such classification decisions while maintaining a consistent classification accuracy. Furthermore, the simulations highlight the importance of the selected test termination criterion, which has a significant impact on the average test length.

1 aGnambs, Timo1 aBatinic, Bernad uhttp://epm.sagepub.com/content/71/6/1006.abstract00688nas a2200217 4500008004100000245006000041210005800101260001200159653001700171653001700188653000800205653001500213653002500228653003200253653001700285100001800302700002100320700001600341700002400357856008900381 2011 eng d00aPractitioner’s Approach to Identify Item Drift in CAT0 aPractitioner s Approach to Identify Item Drift in CAT c10/201110aCUSUM method10aG2 statistic10aIPA10aitem drift10aitem parameter drift10aLord's chi-square statistic10aRaju's NCDIF1 aMeng, Huijuan1 aSteinkamp, Susan1 aJones, Paul1 aMatthews-Lopez, Joy uhttp://www.iacat.org/content/practitioner%E2%80%99s-approach-identify-item-drift-cat01369nas a2200157 4500008003900000022001400039245010400053210006900157300001400226490000700240520085700247100001501104700001901119700001801138856005501156 2011 d a1745-398400aRestrictive Stochastic Item Selection Methods in Cognitive Diagnostic Computerized Adaptive Testing0 aRestrictive Stochastic Item Selection Methods in Cognitive Diagn a255–2730 v483 a

This paper proposes two new item selection methods for cognitive diagnostic computerized adaptive testing: the restrictive progressive method and the restrictive threshold method. They are built upon the posterior weighted Kullback-Leibler (KL) information index but include additional stochastic components either in the item selection index or in the item selection procedure. Simulation studies show that both methods are successful at simultaneously suppressing overexposed items and increasing the usage of underexposed items. Compared to item selection based upon (1) pure KL information and (2) the Sympson-Hetter method, the two new methods strike a better balance between item exposure control and measurement accuracy. The two new methods are also compared with Barrada et al.'s (2008) progressive method and proportional method.

1 aWang, Chun1 aChang, Hua-Hua1 aHuebner, Alan uhttp://dx.doi.org/10.1111/j.1745-3984.2011.00145.x00317nas a2200109 4500008004100000245003200041210003100073653000800104653001600112100001800128856006100146 2011 eng d00aSmall-Sample Shadow Testing0 aSmallSample Shadow Testing10aCAT10ashadow test1 aJudd, Wallace uhttp://www.iacat.org/content/small-sample-shadow-testing00781nas a2200205 4500008004100000245003400041210003200075260001200107520027300119653000800392653000800400653002300408653001000431653001200441653000800453100002200461700001900483700001600502856005700518 2011 eng d00aA Test Assembly Model for MST0 aTest Assembly Model for MST c10/20113 a

This study is just a short exploration in the matter of optimization of a MST. It is extremely hard or maybe impossible to chart influence of item pool and test specifications on optimization process. Simulations are very helpful in finding an acceptable MST.

10aCAT10amst10amultistage testing10aRasch10arouting10atif1 aVerschoor, Angela1 aRadtke, Ingrid1 aEggen, Theo uhttp://www.iacat.org/content/test-assembly-model-mst00476nas a2200121 4500008004500000245008000045210006900125300001200194490000700206100001700213700001600230856010800246 2011 Engldsh 00aUnproctored Internet test verification: Using adaptive confirmation testing0 aUnproctored Internet test verification Using adaptive confirmati a608-6300 v141 aMakransky, G1 aGlas, C A W uhttp://www.iacat.org/content/unproctored-internet-test-verification-using-adaptive-confirmation-testing02120nas a2200193 4500008004100000245007900041210006900120260001200189520146800201653002801669653000801697653001801705100002001723700001701743700002301760700002301783700002301806856009701829 2011 eng d00aThe Use of Decision Trees for Adaptive Item Selection and Score Estimation0 aUse of Decision Trees for Adaptive Item Selection and Score Esti c10/20113 a

Conducted post-hoc simulations comparing the relative efficiency, and precision of decision trees (using CHAID and CART) vs. IRT-based CAT.

Conclusions

Decision tree methods were more efficient than CAT

But,...

Conclusions

CAT selects items based on two criteria: Item location relative to current estimate of theta, Item discrimination

Decision Trees select items that best discriminate between groups defined by the total score.

CAT is optimal only when trait level is well estimated.
Findings suggest that combining decision tree followed by CAT item selection may be advantageous.

10aadaptive item selection10aCAT10adecision tree1 aRiley, Barth, B1 aFunk, Rodney1 aDennis, Michael, L1 aLennox, Richard, D1 aFinkelman, Matthew uhttp://www.iacat.org/content/use-decision-trees-adaptive-item-selection-and-score-estimation01352nas a2200133 4500008003900000245008000039210006900119300001200188490000700200520091200207100001901119700002301138856005701161 2011 d00aUsing Item Response Theory and Adaptive Testing in Online Career Assessment0 aUsing Item Response Theory and Adaptive Testing in Online Career a274-2860 v193 a

The present article describes the potential utility of item response theory (IRT) and adaptive testing for scale evaluation and for web-based career assessment. The article describes the principles of both IRT and adaptive testing and then illustrates these with reference to data analyses and simulation studies of the Career Confidence Inventory (CCI). The kinds of information provided by IRT are shown to give a more precise look at scale quality across the trait continuum and also to permit the use of adaptive testing, where the items administered are tailored to the individual being tested. Such tailoring can significantly reduce testing time while maintaining high quality of measurement. This efficiency is especially useful when multiscale inventories and/or a large number of scales are to be administered. Readers are encouraged to consider using these advances in career assessment.

1 aBetz, Nancy, E1 aTurner, Brandon, M uhttp://jca.sagepub.com/cgi/content/abstract/19/3/27401392nas a2200145 4500008004100000245007100041210006900112260001200181520089200193653000801085653001801093653001701111100002601128856009201154 2011 eng d00aWalking the Tightrope: Using Better Content Control to Improve CAT0 aWalking the Tightrope Using Better Content Control to Improve CA c10/20113 a

All testing involves a balance between measurement precision and content considerations. CAT item-selection algorithms have evolved to accommodate content considerations. Reviews CAT evolution including: Original/”Pure” adaptive exams, Constrained CAT, Weighted-deviations method, Shadow-Test Approach, Testlets instead of fully adapted tests, Administration of one item may preclude the administration of other item(s), and item relationships.

Research Questions

 

10aCAT10aCAT evolution10atest content1 aGialluca, Kathleen, A uhttp://www.iacat.org/content/walking-tightrope-using-better-content-control-improve-cat00411nas a2200109 4500008004100000245006400041210006400105300001200169100001600181700001300197856009100210 2010 eng d00aAdaptive Mastery Testing Using a Multidimensional IRT Model0 aAdaptive Mastery Testing Using a Multidimensional IRT Model a409-4311 aGlas, C A W1 aVos, H J uhttp://www.iacat.org/content/adaptive-mastery-testing-using-multidimensional-irt-model00360nas a2200097 4500008004100000245005600041210005600097300001200153100001600165856008100181 2010 eng d00aAdaptive Tests for Measuring Anxiety and Depression0 aAdaptive Tests for Measuring Anxiety and Depression a123-1361 aWalter, O B uhttp://www.iacat.org/content/adaptive-tests-measuring-anxiety-and-depression00444nas a2200121 4500008004100000245006700041210006700108300001200175100001800187700001300205700001400218856009000232 2010 eng d00aAssembling an Inventory of Multistage Adaptive Testing Systems0 aAssembling an Inventory of Multistage Adaptive Testing Systems a247-2661 aBreithaupt, K1 aAriel, A1 aHare, D R uhttp://www.iacat.org/content/assembling-inventory-multistage-adaptive-testing-systems00406nas a2200109 4500008004500000245006300045210006000108490000700168100001700175700001600192856008800208 2010 Engldsh 00aAn automatic online calibration design in adaptive testing0 aautomatic online calibration design in adaptive testing0 v111 aMakransky, G1 aGlas, C A W uhttp://www.iacat.org/content/automatic-online-calibration-design-adaptive-testing-001384nas a2200133 4500008004100000245006000041210006000101300001200161490000700173520093200180653003401112100001801146856008601164 2010 eng d00aBayesian item selection in constrained adaptive testing0 aBayesian item selection in constrained adaptive testing a149-1690 v313 aApplication of Bayesian item selection criteria in computerized adaptive testing might result in improvement of bias and MSE of the ability estimates. The question remains how to apply Bayesian item selection criteria in the context of constrained adaptive testing, where large numbers of specifications have to be taken into account in the item selection process. The Shadow Test Approach is a general purpose algorithm for administering constrained CAT. In this paper it is shown how the approach can be slightly modified to handle Bayesian item selection criteria. No differences in performance were found between the shadow test approach and the modifiedapproach. In a simulation study of the LSAT, the effects of Bayesian item selection criteria are illustrated. The results are compared to item selection based on Fisher Information. General recommendations about the use of Bayesian item selection criteria are provided.10acomputerized adaptive testing1 aVeldkamp, B P uhttp://www.iacat.org/content/bayesian-item-selection-constrained-adaptive-testing01688nas a2200145 4500008003900000245020500039210006900244300001200313490000700325520109200332100002001424700002301444700002201467856005301489 2010 d00aA Comparison of Content-Balancing Procedures for Estimating Multiple Clinical Domains in Computerized Adaptive Testing: Relative Precision, Validity, and Detection of Persons With Misfitting Responses0 aComparison of ContentBalancing Procedures for Estimating Multipl a410-4230 v343 a

This simulation study sought to compare four different computerized adaptive testing (CAT) content-balancing procedures designed for use in a multidimensional assessment with respect to measurement precision, symptom severity classification, validity of clinical diagnostic recommendations, and sensitivity to atypical responding. The four content-balancing procedures were (a) no content balancing, (b) screener-based, (c) mixed (screener plus content balancing), and (d) full content balancing. In full content balancing and in mixed content balancing following administration of the screener items, item selection was based on (a) whether the target number of items for the item’s subscale was reached and (b) the item’s information function. Mixed and full content balancing provided the best representation of items from each of the main subscales of the Internal Mental Distress Scale. These procedures also resulted in higher CAT to full-scale correlations for the Trauma and Homicidal/Suicidal Thought subscales and improved detection of atypical responding.

1 aRiley, Barth, B1 aDennis, Michael, L1 aConrad, Kendon, J uhttp://apm.sagepub.com/content/34/6/410.abstract01767nas a2200157 4500008004100000020002300041245020500064210006900269300001200338490000700350520108200357100001501439700001601454700001601470856012301486 2010 eng d a0146-62161552-349700aA comparison of content-balancing procedures for estimating multiple clinical domains in computerized adaptive testing: Relative precision, validity, and detection of persons with misfitting responses0 acomparison of contentbalancing procedures for estimating multipl a410-4230 v343 aThis simulation study sought to compare four different computerized adaptive testing (CAT) content-balancing procedures designed for use in a multidimensional assessment with respect to measurement precision, symptom severity classification, validity of clinical diagnostic recommendations, and sensitivity to atypical responding. The four content-balancing procedures were (a) no content balancing, (b) screener-based, (c) mixed (screener plus content balancing), and (d) full content balancing. In full content balancing and in mixed content balancing following administration of the screener items, item selection was based on (a) whether the target numberof items for the item’s subscale was reached and (b) the item’s information function. Mixed and full content balancing provided the best representation of items from each of the main subscales of the Internal Mental Distress Scale. These procedures also resulted in higher CAT to full-scale correlations for the Trauma and Homicidal/Suicidal Thought subscales and improved detection of atypical responding.Keywords1 aRiley, B B1 aDennis, M L1 aConrad, K J uhttp://www.iacat.org/content/comparison-content-balancing-procedures-estimating-multiple-clinical-domains-computerized01176nas a2200145 4500008003900000245005900039210005700098300001200155490000700167520073700174100002200911700002100933700002300954856005300977 2010 d00aA Comparison of Item Selection Techniques for Testlets0 aComparison of Item Selection Techniques for Testlets a424-4370 v343 a

This study examined the performance of the maximum Fisher’s information, the maximum posterior weighted information, and the minimum expected posterior variance methods for selecting items in a computerized adaptive testing system when the items were grouped in testlets. A simulation study compared the efficiency of ability estimation among the item selection techniques under varying conditions of local-item dependency when the response model was either the three-parameter-logistic item response theory or the three-parameter-logistic testlet response theory. The item selection techniques performed similarly within any particular condition, the practical implications of which are discussed within the article.

1 aMurphy, Daniel, L1 aDodd, Barbara, G1 aVaughn, Brandon, K uhttp://apm.sagepub.com/content/34/6/424.abstract00465nas a2200133 4500008004100000245005800041210005800099260004200157300001200199490000700211100001200218700001700230856008400247 2010 eng d00aComputerized adaptive testing based on decision trees0 aComputerized adaptive testing based on decision trees aSousse, TunisiabIEEE Computer Sience a191-1930 v581 aUeno, M1 aSongmuang, P uhttp://www.iacat.org/content/computerized-adaptive-testing-based-decision-trees00351nas a2200097 4500008004100000245005100041210005100092300001000143100002300153856007700176 2010 eng d00aConstrained Adaptive Testing with Shadow Tests0 aConstrained Adaptive Testing with Shadow Tests a31-561 avan der Linden, WJ uhttp://www.iacat.org/content/constrained-adaptive-testing-shadow-tests-000474nas a2200121 4500008004100000245008000041210006900121300001200190100001700202700001800219700001300237856010200250 2010 eng d00aDesigning and Implementing a Multistage Adaptive Test: The Uniform CPA Exam0 aDesigning and Implementing a Multistage Adaptive Test The Unifor a167-1901 aMelican, G J1 aBreithaupt, K1 aZhang, Y uhttp://www.iacat.org/content/designing-and-implementing-multistage-adaptive-test-uniform-cpa-exam00367nas a2200109 4500008004100000245004600041210004600087300001200133100001800145700002300163856007100186 2010 eng d00aDesigning Item Pools for Adaptive Testing0 aDesigning Item Pools for Adaptive Testing a231-2451 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/designing-item-pools-adaptive-testing01430nas a2200133 4500008004100000020001400041245008500055210006900140300001200209490000700221520094900228100001701177856010201194 2010 eng d a2190-050700aDesigning item pools to optimize the functioning of a computerized adaptive test0 aDesigning item pools to optimize the functioning of a computeriz a127-1410 v523 aComputerized adaptive testing (CAT) is a testing procedure that can result in improved precision for a specified test length or reduced test length with no loss of precision. However, these attractive psychometric features of CATs are only achieved if appropriate test items are available for administration. This set of test items is commonly called an “item pool.” This paper discusses the optimal characteristics for an item pool that will lead to the desired properties for a CAT. Then, a procedure is described for designing the statistical characteristics of the item parameters for an optimal item pool within an item response theory framework. Because true optimality is impractical, methods for achieving practical approximations to optimality are described. The results of this approach are shown for an operational testing program including comparisons to the results from the item pool currently used in that testing program.Key1 aReckase, M D uhttp://www.iacat.org/content/designing-item-pools-optimize-functioning-computerized-adaptive-test00376nas a2200109 4500008004100000245004800041210004800089300001200137100001600149700002700165856007400192 2010 eng d00aDetecting Person Misfit in Adaptive Testing0 aDetecting Person Misfit in Adaptive Testing a315-3291 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/detecting-person-misfit-adaptive-testing01349nas a2200229 4500008004100000020001300041245011700054210006900171300001200240490000700252520057500259653000800834653003400842653001900876653001500895100002000910700001600930700001800946700001500964700001400979856012600993 2010 eng d a0191886900aDetection of aberrant item score patterns in computerized adaptive testing: An empirical example using the CUSUM0 aDetection of aberrant item score patterns in computerized adapti a921-9250 v483 aThe scalability of individual trait scores on a computerized adaptive test (CAT) was assessed through investigating the consistency of individual item score patterns. A sample of N = 428 persons completed a personality CAT as part of a career development procedure. To detect inconsistent item score patterns, we used a cumulative sum (CUSUM) procedure. Combined information from the CUSUM, other personality measures, and interviews showed that similar estimated trait values may have a different interpretation.Implications for computer-based assessment are discussed.10aCAT10acomputerized adaptive testing10aCUSUM approach10aperson Fit1 aEgberink, I J L1 aMeijer, R R1 aVeldkamp, B P1 aSchakel, L1 aSmid, N G uhttp://www.iacat.org/content/detection-aberrant-item-score-patterns-computerized-adaptive-testing-empirical-example-using03049nas a2200241 4500008004100000020004100041245017000082210007100252250001500323300001000338490000700348520214300355653001402498653006602512653001102578653001302589100001402602700001202616700001402628700001502642700001702657856013302674 2010 spa d a0214-9915 (Print)0214-9915 (Linking)00aDeterioro de parámetros de los ítems en tests adaptativos informatizados: estudio con eCAT [Item parameter drift in computerized adaptive testing: Study with eCAT]0 aDeterioro de parámetros de los ítems en tests adaptativos inform a2010/04/29 a340-70 v223 a

En el presente trabajo se muestra el análisis realizado sobre un Test Adaptativo Informatizado (TAI) diseñado para la evaluación del nivel de inglés, denominado eCAT, con el objetivo de estudiar el deterioro de parámetros (parameter drift) producido desde la calibración inicial del banco de ítems. Se ha comparado la calibración original desarrollada para la puesta en servicio del TAI (N= 3224) y la calibración actual obtenida con las aplicaciones reales del TAI (N= 7254). Se ha analizado el Funcionamiento Diferencial de los Ítems (FDI) en función de los parámetros utilizados y se ha simulado el impacto que sobre el nivel de rasgo estimado tiene la variación en los parámetros. Los resultados muestran que se produce especialmente un deterioro de los parámetros a y c, que hay unimportante número de ítems del banco para los que existe FDI y que la variación de los parámetros produce un impacto moderado en la estimación de θ de los evaluados con nivel de inglés alto. Se concluye que los parámetros de los ítems se han deteriorado y deben ser actualizados.Item parameter drift in computerized adaptive testing: Study with eCAT. This study describes the parameter drift analysis conducted on eCAT (a Computerized Adaptive Test to assess the written English level of Spanish speakers). The original calibration of the item bank (N = 3224) was compared to a new calibration obtained from the data provided by most eCAT operative administrations (N =7254). A Differential Item Functioning (DIF) study was conducted between the original and the new calibrations. The impact that the new parameters have on the trait level estimates was obtained by simulation. Results show that parameter drift is found especially for a and c parameters, an important number of bank items show DIF, and the parameter change has a moderate impact on high-level-English θ estimates. It is then recommended to replace the original estimates by the new set. by the new set.

10a*Software10aEducational Measurement/*methods/*statistics & numerical data10aHumans10aLanguage1 aAbad, F J1 aOlea, J1 aAguado, D1 aPonsoda, V1 aBarrada, J R uhttp://www.iacat.org/content/deterioro-de-par%C3%A1metros-de-los-%C3%ADtems-en-tests-adaptativos-informatizados-estudio-con-ecat00557nas a2200157 4500008004100000245008700041210006900128300001400197490001000211100001300221700001200234700001400246700001400260700001400274856011100288 2010 eng d00aDevelopment and evaluation of a confidence-weighting computerized adaptive testing0 aDevelopment and evaluation of a confidenceweighting computerized a163–1760 v13(3)1 aYen, Y C1 aHo, R G1 aChen, L J1 aChou, K Y1 aChen, Y L uhttp://www.iacat.org/content/development-and-evaluation-confidence-weighting-computerized-adaptive-testing03103nas a2200445 4500008004100000020004100041245012000082210006900202250001500271260001000286300001100296490000700307520175400314653003802068653002102106653001002127653000902137653002202146653002802168653003302196653001102229653001102240653000902251653001602260653001802276653001902294653003102313653003102344653001602375100001602391700001002407700001402417700001502431700001402446700001502460700001802475700002402493700001802517856012202535 2010 eng d a0161-8105 (Print)0161-8105 (Linking)00aDevelopment and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments0 aDevelopment and validation of patientreported outcome measures f a2010/06/17 cJun 1 a781-920 v333 aSTUDY OBJECTIVES: To develop an archive of self-report questions assessing sleep disturbance and sleep-related impairments (SRI), to develop item banks from this archive, and to validate and calibrate the item banks using classic validation techniques and item response theory analyses in a sample of clinical and community participants. DESIGN: Cross-sectional self-report study. SETTING: Academic medical center and participant homes. PARTICIPANTS: One thousand nine hundred ninety-three adults recruited from an Internet polling sample and 259 adults recruited from medical, psychiatric, and sleep clinics. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: This study was part of PROMIS (Patient-Reported Outcomes Information System), a National Institutes of Health Roadmap initiative. Self-report item banks were developed through an iterative process of literature searches, collecting and sorting items, expert content review, qualitative patient research, and pilot testing. Internal consistency, convergent validity, and exploratory and confirmatory factor analysis were examined in the resulting item banks. Factor analyses identified 2 preliminary item banks, sleep disturbance and SRI. Item response theory analyses and expert content review narrowed the item banks to 27 and 16 items, respectively. Validity of the item banks was supported by moderate to high correlations with existing scales and by significant differences in sleep disturbance and SRI scores between participants with and without sleep disorders. CONCLUSIONS: The PROMIS sleep disturbance and SRI item banks have excellent measurement properties and may prove to be useful for assessing general aspects of sleep and SRI with various groups of patients and interventions.10a*Outcome Assessment (Health Care)10a*Self Disclosure10aAdult10aAged10aAged, 80 and over10aCross-Sectional Studies10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aPsychometrics10aQuestionnaires10aReproducibility of Results10aSleep Disorders/*diagnosis10aYoung Adult1 aBuysse, D J1 aYu, L1 aMoul, D E1 aGermain, A1 aStover, A1 aDodds, N E1 aJohnston, K L1 aShablesky-Cade, M A1 aPilkonis, P A uhttp://www.iacat.org/content/development-and-validation-patient-reported-outcome-measures-sleep-disturbance-and-sleep02223nas a2200289 4500008004100000020004600041245010800087210006900195250001500264300001200279490000700291520131000298100001801608700001701626700001801643700001401661700001401675700001801689700001401707700001701721700001501738700001301753700001401766700001601780700001301796856012401809 2010 Eng d a1573-2649 (Electronic)0962-9343 (Linking)00aDevelopment of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension0 aDevelopment of computerized adaptive testing CAT for the EORTC Q a2010/10/26 a479-4900 v203 aPURPOSE: Computerized adaptive test (CAT) methods, based on item response theory (IRT), enable a patient-reported outcome instrument to be adapted to the individual patient while maintaining direct comparability of scores. The EORTC Quality of Life Group is developing a CAT version of the widely used EORTC QLQ-C30. We present the development and psychometric validation of the item pool for the first of the scales, physical functioning (PF). METHODS: Initial developments (including literature search and patient and expert evaluations) resulted in 56 candidate items. Responses to these items were collected from 1,176 patients with cancer from Denmark, France, Germany, Italy, Taiwan, and the United Kingdom. The items were evaluated with regard to psychometric properties. RESULTS: Evaluations showed that 31 of the items could be included in a unidimensional IRT model with acceptable fit and good content coverage, although the pool may lack items at the upper extreme (good PF). There were several findings of significant differential item functioning (DIF). However, the DIF findings appeared to have little impact on the PF estimation. CONCLUSIONS: We have established an item pool for CAT measurement of PF and believe that this CAT instrument will clearly improve the EORTC measurement of PF.1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aChie, W C1 aConroy, T1 aCostantini, A1 aFayers, P1 aHelbostad, J1 aHolzner, B1 aKaasa, S1 aSinger, S1 aVelikova, G1 aYoung, T uhttp://www.iacat.org/content/development-computerized-adaptive-testing-cat-eortc-qlq-c30-physical-functioning-dimension00605nas a2200157 4500008004100000245011500041210006900156300001400225490001000239100001200249700001500261700001800276700001400294700001300308856012600321 2010 eng d00aEfficiency of static and computer adaptive short forms compared to full-length measures of depressive symptoms0 aEfficiency of static and computer adaptive short forms compared  a125–1360 v19(1)1 aChoi, S1 aReise, S P1 aPilkonis, P A1 aHays, R D1 aCella, D uhttp://www.iacat.org/content/efficiency-static-and-computer-adaptive-short-forms-compared-full-length-measures-depressive00358nam a2200121 4500008004100000245003300041210003300074260002300107300000800130100002300138700001600161856005900177 2010 eng d00aElements of Adaptive Testing0 aElements of Adaptive Testing aNew YorkbSpringer a4371 avan der Linden, WJ1 aGlas, C A W uhttp://www.iacat.org/content/elements-adaptive-testing00470nas a2200121 4500008004100000245007900041210006900120300001200189100001600201700002300217700001700240856009100257 2010 eng d00aEstimation of the Parameters in an Item-Cloning Model for Adaptive Testing0 aEstimation of the Parameters in an ItemCloning Model for Adaptiv a289-3141 aGlas, C A W1 avan der Linden, WJ1 aGeerlings, H uhttp://www.iacat.org/content/estimation-parameters-item-cloning-model-adaptive-testing01124nas a2200157 4500008004100000020004100041245013100082210006900213250001500282300001100297490000700308520049700315100001500812700001400827856012500841 2010 eng d a1529-7713 (Print)1529-7713 (Linking)00aFeatures of the sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules0 aFeatures of the sampling distribution of the ability estimate in a2010/12/18 a424-310 v113 aWhether paper and pencil or computerized adaptive, tests are usually described by a set of rules managing how they are administered: which item will be first, which should follow any given item, when to administer the last one. This article focus on the latter and looks at the effect of two stopping rules on the estimated sampling distribution of the ability estimate in a CAT: the number of items administered and the a priori determined size of the standard error of the ability estimate.1 aBlais, J G1 aRaiche, G uhttp://www.iacat.org/content/features-sampling-distribution-ability-estimate-computerized-adaptive-testing-according-two00427nas a2200097 4500008004100000245008300041210006900124300001200193100001600205856010800221 2010 eng d00aImplementing the Graduate Management Admission Test Computerized Adaptive Test0 aImplementing the Graduate Management Admission Test Computerized a151-1661 aRudner, L M uhttp://www.iacat.org/content/implementing-graduate-management-admission-test-computerized-adaptive-test01417nas a2200121 4500008003900000245015400039210006900193300001200262490000700274520094600281100001501227856005301242 2010 d00aImproving Cognitive Diagnostic Computerized Adaptive Testing by Balancing Attribute Coverage: The Modified Maximum Global Discrimination Index Method0 aImproving Cognitive Diagnostic Computerized Adaptive Testing by  a902-9130 v703 a

This article proposes a new item selection method, namely, the modified maximum global discrimination index (MMGDI) method, for cognitive diagnostic computerized adaptive testing (CD-CAT). The new method captures two aspects of the appeal of an item: (a) the amount of contribution it can make toward adequate coverage of every attribute and (b) the amount of contribution it can make toward recovering the latent cognitive profile. A simulation study shows that the new method ensures adequate coverage of every attribute, which improves the validity of the test scores, and defensibility of the proposed uses of the test. Furthermore, compared with the original global discrimination index method, the MMGDI method improves the recovery rate of each attribute and of the entire cognitive profile, especially the latter. Therefore, the new method improves both the validity and reliability of the test scores from a CD-CAT program.

1 aYing Cheng uhttp://epm.sagepub.com/content/70/6/902.abstract00414nas a2200133 4500008004100000245004600041210004600087300001200133100001800145700001600163700001300179700001700192856007100209 2010 eng d00aInnovative Items for Computerized Testing0 aInnovative Items for Computerized Testing a215-2301 aParshall, C G1 aHarmes, J C1 aDavey, T1 aPashley, P J uhttp://www.iacat.org/content/innovative-items-computerized-testing00398nas a2200097 4500008004100000245007300041210006900114300001200183100001300195856009200208 2010 eng d00aThe Investigation of Differential Item Functioning in Adaptive Tests0 aInvestigation of Differential Item Functioning in Adaptive Tests a331-3521 aZwick, R uhttp://www.iacat.org/content/investigation-differential-item-functioning-adaptive-tests00352nas a2200097 4500008004100000245005200041210005200093300001200145100001600157856008100173 2010 eng d00aItem Parameter Estimation and Item Fit Analysis0 aItem Parameter Estimation and Item Fit Analysis a269-2881 aGlas, C A W uhttp://www.iacat.org/content/item-parameter-estimation-and-item-fit-analysis00449nas a2200121 4500008004100000245006200041210006200103260002300165300000900188100002300197700001700220856009000237 2010 eng d00aItem Selection and Ability Estimation in Adaptive Testing0 aItem Selection and Ability Estimation in Adaptive Testing aNew YorkbSpringer a3-301 avan der Linden, WJ1 aPashley, P J uhttp://www.iacat.org/content/item-selection-and-ability-estimation-adaptive-testing-001511nas a2200217 4500008004100000245008100041210006900122300001200191490000700203520078900210653001100999653003401010653002201044653003501066653002101101653002101122100001901143700001401162700001601176856010101192 2010 eng d00aItem Selection and Hypothesis Testing for the Adaptive Measurement of Change0 aItem Selection and Hypothesis Testing for the Adaptive Measureme a238-2540 v343 a

Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC framework. This study introduced a new item selection criterion and two new test statistics for detecting change with AMC that were specifically designed for the paradigm of hypothesis testing. In two simulation sets, the new methods for detecting significant change improved on existing procedures by demonstrating better adherence to Type I error rates and substantially better power for detecting relatively small change. 

10achange10acomputerized adaptive testing10aindividual change10aKullback–Leibler information10alikelihood ratio10ameasuring change1 aFinkelman, M D1 aWeiss, DJ1 aKim-Kang, G uhttp://www.iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change-000481nas a2200109 4500008004100000245010100041210006900142300001200211100001400223700001500237856011900252 2010 eng d00aA Japanese Adaptive Test of English as a Foreign Language: Developmental and Operational Aspects0 aJapanese Adaptive Test of English as a Foreign Language Developm a191-2111 aNogami, Y1 aHayashi, N uhttp://www.iacat.org/content/japanese-adaptive-test-english-foreign-language-developmental-and-operational-aspects00481nas a2200109 4500008004100000245008100041210006900122260004900191100001400240700001500254856010200269 2010 eng d00aManual for CATSim: Comprehensive simulation of computerized adaptive testing0 aManual for CATSim Comprehensive simulation of computerized adapt aSt. Paul, MNbAssessment Systems Corporation1 aWeiss, DJ1 aGuyer, R D uhttp://www.iacat.org/content/manual-catsim-comprehensive-simulation-computerized-adaptive-testing01561nas a2200157 4500008004100000020004100041245008400082210006900166250001500235300001100250490000700261520099300268100001601261700002301277856010301300 2010 eng d a0007-1102 (Print)0007-1102 (Linking)00aMarginal likelihood inference for a model for item responses and response times0 aMarginal likelihood inference for a model for item responses and a2010/01/30 a603-260 v633 a

Marginal maximum-likelihood procedures for parameter estimation and testing the fit of a hierarchical model for speed and accuracy on test items are presented. The model is a composition of two first-level models for dichotomous responses and response times along with multivariate normal models for their item and person parameters. It is shown how the item parameters can easily be estimated using Fisher's identity. To test the fit of the model, Lagrange multiplier tests of the assumptions of subpopulation invariance of the item parameters (i.e., no differential item functioning), the shape of the response functions, and three different types of conditional independence were derived. Simulation studies were used to show the feasibility of the estimation and testing procedures and to estimate the power and Type I error rate of the latter. In addition, the procedures were applied to an empirical data set from a computerized adaptive test of language comprehension.

1 aGlas, C A W1 avan der Linden, WJ uhttp://www.iacat.org/content/marginal-likelihood-inference-model-item-responses-and-response-times00450nas a2200109 4500008004100000245007500041210006900116300001200185100002500197700002400222856009400246 2010 eng d00aMATHCAT: A Flexible Testing System in Mathematics Education for Adults0 aMATHCAT A Flexible Testing System in Mathematics Education for A a137-1501 aVerschoor, Angela, J1 aStraetmans, G J J M uhttp://www.iacat.org/content/mathcat-flexible-testing-system-mathematics-education-adults01871nas a2200157 4500008003900000245008900039210006900128300001200197490000700209520135600216100002501572700001601597700002101613700002601634856005301660 2010 d00aA Method for the Comparison of Item Selection Rules in Computerized Adaptive Testing0 aMethod for the Comparison of Item Selection Rules in Computerize a438-4520 v343 a

In a typical study comparing the relative efficiency of two item selection rules in computerized adaptive testing, the common result is that they simultaneously differ in accuracy and security, making it difficult to reach a conclusion on which is the more appropriate rule. This study proposes a strategy to conduct a global comparison of two or more selection rules. A plot showing the performance of each selection rule for several maximum exposure rates is obtained and the whole plot is compared with other rule plots. The strategy was applied in a simulation study with fixed-length CATs for the comparison of six item selection rules: the point Fisher information, Fisher information weighted by likelihood, Kullback-Leibler weighted by likelihood, maximum information stratification with blocking, progressive and proportional methods. Our results show that there is no optimal rule for any overlap value or root mean square error (RMSE). The fact that a rule, for a given level of overlap, has lower RMSE than another does not imply that this pattern holds for another overlap rate. A fair comparison of the rules requires extensive manipulation of the maximum exposure rates. The best methods were the Kullback-Leibler weighted by likelihood, the proportional method, and the maximum information stratification method with blocking.

1 aBarrada, Juan Ramón1 aOlea, Julio1 aPonsoda, Vicente1 aAbad, Francisco José uhttp://apm.sagepub.com/content/34/6/438.abstract00561nas a2200145 4500008003900000245015500039210006900194300001200263490000700275100001700282700001400299700001800313700001600331856006800347 2010 d00aA Monte Carlo Simulation Investigating the Validity and Reliability of Ability Estimation in Item Response Theory with Speeded Computer Adaptive Tests0 aMonte Carlo Simulation Investigating the Validity and Reliabilit a230-2610 v101 aSchmitt, T A1 aSass, D A1 aSullivan, J R1 aWalker, C M uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2010.48809800478nas a2200109 4500008004100000245008900041210007100130300001100201100001400212700002300226856011900249 2010 eng d00aMultidimensional Adaptive Testing with Kullback–Leibler Information Item Selection0 aMultidimensional Adaptive Testing with Kullback–Leibler Informat a77-1021 aMulder, J1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-kullback%E2%80%93leibler-information-item-selection00581nas a2200121 4500008004400000245017600044210006900220300001000289490000700299100001200306700001500318856012600333 2010 Germdn 00aMultidimensionale adaptive Kompetenzdiagnostik: Ergebnisse zur Messeffizienz [Multidimensional adaptive testing of competencies: Results regarding measurement efficiency].0 aMultidimensionale adaptive Kompetenzdiagnostik Ergebnisse zur Me a40-510 v561 aFrey, A1 aSeitz, N-N uhttp://www.iacat.org/content/multidimensionale-adaptive-kompetenzdiagnostik-ergebnisse-zur-messeffizienz-multidimensional00410nas a2200121 4500008004100000245005400041210005100095300001200146100001700158700001800175700001500193856008000208 2010 eng d00aMultistage Testing: Issues, Designs, and Research0 aMultistage Testing Issues Designs and Research a355-3721 aZenisky, A L1 aHambleton, RK1 aLuecht, RM uhttp://www.iacat.org/content/multistage-testing-issues-designs-and-research01299nas a2200181 4500008004100000020004100041245005800082210005600140250001500196260001000211300000900221490000700230520075600237100001400993700001501007700001401022856008101036 2010 Eng d a0013-1644 (Print)0013-1644 (Linking)00aA new stopping rule for computerized adaptive testing0 anew stopping rule for computerized adaptive testing a2011/02/01 cDec 1 a1-170 v703 aThe goal of the current study was to introduce a new stopping rule for computerized adaptive testing. The predicted standard error reduction stopping rule (PSER) uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared to that of the minimum standard error stopping rule and a modified version of the minimum information stopping rule in a series of simulated adaptive tests, drawn from a number of item pools. Results indicate that the PSER makes efficient use of CAT item pools, administering fewer items when predictive gains in information are small and increasing measurement precision when information is abundant.1 aChoi, S W1 aGrady, M W1 aDodd, B G uhttp://www.iacat.org/content/new-stopping-rule-computerized-adaptive-testing01593nas a2200145 4500008004100000020001400041245007300055210006900128300001200197490000700209520110600216100001501322700001201337856009801349 2010 eng d a0033-312300aOnline calibration via variable length computerized adaptive testing0 aOnline calibration via variable length computerized adaptive tes a140-1570 v753 aItem calibration is an essential issue in modern item response theory based psychological or educational testing. Due to the popularity of computerized adaptive testing, methods to efficiently calibrate new items have become more important than that in the time when paper and pencil test administration is the norm. There are many calibration processes being proposed and discussed from both theoretical and practical perspectives. Among them, the online calibration may be one of the most cost effective processes. In this paper, under a variable length computerized adaptive testing scenario, we integrate the methods of adaptive design, sequential estimation, and measurement error models to solve online item calibration problems. The proposed sequential estimate of item parameters is shown to be strongly consistent and asymptotically normally distributed with a prechosen accuracy. Numerical results show that the proposed method is very promising in terms of both estimation accuracy and efficiency. The results of using calibrated items to estimate the latent trait levels are also reported.1 aChang, Y I1 aLu, H Y uhttp://www.iacat.org/content/online-calibration-variable-length-computerized-adaptive-testing00349nas a2200097 4500008004100000245005200041210005200093300001000145100001600155856008000171 2010 eng d00aPrinciples of Multidimensional Adaptive Testing0 aPrinciples of Multidimensional Adaptive Testing a57-761 aSegall, D O uhttp://www.iacat.org/content/principles-multidimensional-adaptive-testing-001445nas a2200121 4500008003900000245008600039210006900125300001200194490000700206520103800213100001901251856005301270 2010 d00aA Procedure for Controlling General Test Overlap in Computerized Adaptive Testing0 aProcedure for Controlling General Test Overlap in Computerized A a393-4090 v343 a

To date, exposure control procedures that are designed to control test overlap in computerized adaptive tests (CATs) are based on the assumption of item sharing between pairs of examinees. However, in practice, examinees may obtain test information from more than one previous test taker. This larger scope of information sharing needs to be considered in conducting test overlap control. The purpose of this study is to propose a test overlap control method such that the proportion of overlapping items encountered by an examinee with a group of previous examinees (described as general test overlap rate) can be controlled. Results indicated that item exposure rate and general test overlap rate could be simultaneously controlled by implementing the procedure. In addition, these two indices were controlled on the fly without any iterative simulations conducted prior to operational CATs. Thus, the proposed procedure would be an efficient method for controlling both the item exposure and general test overlap in CATs.

1 aChen, Shu-Ying uhttp://apm.sagepub.com/content/34/6/393.abstract00296nas a2200085 4500008004100000245004000041210004000081100002300121856006600144 2010 eng d00aSequencing an Adaptive Test Battery0 aSequencing an Adaptive Test Battery1 avan der Linden, WJ uhttp://www.iacat.org/content/sequencing-adaptive-test-battery00336nas a2200085 4500008004100000245009100041210006900132100001300201856003600214 2010 eng d00aSimulCAT: Windows application that simulates computerized adaptive test administration0 aSimulCAT Windows application that simulates computerized adaptiv1 aHan, K T uhttp://www.hantest.net/simulcat01719nas a2200157 4500008003900000022001400039245009400053210006900147300001400216490000700230520121600237100001401453700002001467700001901487856005501506 2010 d a1745-398400aStratified and Maximum Information Item Selection Procedures in Computer Adaptive Testing0 aStratified and Maximum Information Item Selection Procedures in  a202–2260 v473 a

In this study we evaluated and compared three item selection procedures: the maximum Fisher information procedure (F), the a-stratified multistage computer adaptive testing (CAT) (STR), and a refined stratification procedure that allows more items to be selected from the high a strata and fewer items from the low a strata (USTR), along with completely random item selection (RAN). The comparisons were with respect to error variances, reliability of ability estimates and item usage through CATs simulated under nine test conditions of various practical constraints and item selection space. The results showed that F had an apparent precision advantage over STR and USTR under unconstrained item selection, but with very poor item usage. USTR reduced error variances for STR under various conditions, with small compromises in item usage. Compared to F, USTR enhanced item usage while achieving comparable precision in ability estimates; it achieved a precision level similar to F with improved item usage when items were selected under exposure control and with limited item selection space. The results provide implications for choosing an appropriate item selection procedure in applied settings.

1 aDeng, Hui1 aAnsley, Timothy1 aChang, Hua-Hua uhttp://dx.doi.org/10.1111/j.1745-3984.2010.00109.x00519nas a2200133 4500008004100000245009400041210006900135300001200204490000700216100001200223700001400235700001600249856012000265 2010 Eng d00aStratified and maximum information item selection procedures in computer adaptive testing0 aStratified and maximum information item selection procedures in  a202-2260 v471 aDeng, H1 aAnsley, T1 aChang, H -H uhttp://www.iacat.org/content/stratified-and-maximum-information-item-selection-procedures-computer-adaptive-testing00349nas a2200109 4500008004100000245004300041210004200084300001200126100001300138700001600151856007200167 2010 eng d00aTestlet-Based Adaptive Mastery Testing0 aTestletBased Adaptive Mastery Testing a387-4091 aVos, H J1 aGlas, C A W uhttp://www.iacat.org/content/testlet-based-adaptive-mastery-testing02926nas a2200145 4500008004100000245009900041210006900140300001100209490000700220520238700227100001202614700001402626700001702640856012302657 2010 eng d00aTests informatizados y otros nuevos tipos de tests [Computerized and other new types of tests]0 aTests informatizados y otros nuevos tipos de tests Computerized  a94-1070 v313 aRecientemente se ha producido un considerable desarrollo de los tests adaptativos informatizados, en los que el test se adapta progresivamente al rendimiento del evaluando, y de otros tipos de tests: a) los test basados en modelos (se dispone de un modelo o teoría de cómo se responde a cada ítem, lo que permite predecir su dificultad), b) los tests ipsativos (el evaluado ha de elegir entre opciones que tienen parecida deseabilidad social, por lo que pueden resultar eficaces para controlar algunos sesgos de respuestas), c) los tests conductuales (miden rasgos que ordinariamente se han venido midiendo con autoinformes, mediante tareas que requieren respuestas no verbales) y d) los tests situacionales (en los que se presenta al evaluado una situación de conflicto laboral, por ejemplo, con varias posibles soluciones, y ha de elegir la que le parece la mejor descripción de lo que el haría en esa situación). El artículo comenta las características, ventajas e inconvenientes de todos ellos y muestra algunos ejemplos de tests concretos. Palabras clave: Test adaptativo informatizado, Test situacional, Test comportamental, Test ipsativo y generación automática de ítems.The paper provides a short description of some test types that are earning considerable interest in both research and applied areas. The main feature of a computerized adaptive test is that in despite of the examinees receiving different sets of items, their test scores are in the same metric and can be directly compared. Four other test types are considered: a) model-based tests (a model or theory is available to explain the item response process and this makes the prediction of item difficulties possible), b) ipsative tests (the examinee has to select one among two or more options with similar social desirability; so, these tests can help to control faking or other examinee’s response biases), c) behavioral tests (personality traits are measured from non-verbal responses rather than from self-reports), and d) situational tests (the examinee faces a conflictive situation and has to select the option that best describes what he or she will do). The paper evaluates these types of tests, comments on their pros and cons and provides some specific examples. Key words: Computerized adaptive test, Situational test, Behavioral test, Ipsative test and y automatic item generation.1 aOlea, J1 aAbad, F J1 aBarrada, J R uhttp://www.iacat.org/content/tests-informatizados-y-otros-nuevos-tipos-de-tests-computerized-and-other-new-types-tests00348nas a2200097 4500008004100000245005100041210005000092300001200142100001600154856008000170 2010 eng d00aThree-Category Adaptive Classification Testing0 aThreeCategory Adaptive Classification Testing a373-3871 aEggen, Theo uhttp://www.iacat.org/content/three-category-adaptive-classification-testing01857nas a2200181 4500008004100000020001400041245011000055210006900165300001200234490000700246520122300253100001601476700001601492700001601508700001201524700001301536856012601549 2010 eng d a1529-771300aThe use of PROMIS and assessment center to deliver patient-reported outcome measures in clinical research0 ause of PROMIS and assessment center to deliver patientreported o a304-3140 v113 aThe Patient-Reported Outcomes Measurement Information System (PROMIS) was developed as one of the first projects funded by the NIH Roadmap for Medical Research Initiative to re-engineer the clinical research enterprise. The primary goal of PROMIS is to build item banks and short forms that measure key health outcome domains that are manifested in a variety of chronic diseases which could be used as a "common currency" across research projects. To date, item banks, short forms and computerized adaptive tests (CAT) have been developed for 13 domains with relevance to pediatric and adult subjects. To enable easy delivery of these new instruments, PROMIS built a web-based resource (Assessment Center) for administering CATs and other self-report data, tracking item and instrument development, monitoring accrual, managing data, and storing statistical analysis results. Assessment Center can also be used to deliver custom researcher developed content, and has numerous features that support both simple and complicated accrual designs (branching, multiple arms, multiple time points, etc.). This paper provides an overview of the development of the PROMIS item banks and details Assessment Center functionality.1 aGershon, RC1 aRothrock, N1 aHanrahan, R1 aBass, M1 aCella, D uhttp://www.iacat.org/content/use-promis-and-assessment-center-deliver-patient-reported-outcome-measures-clinical-research02757nas a2200241 4500008004100000020004600041245009400087210006900181250001500250300000800265490000600273520198300279100001502262700001602277700001402293700001302307700002002320700001902340700001702359700001302376700001402389856011202403 2010 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aValidation of a computer-adaptive test to evaluate generic health-related quality of life0 aValidation of a computeradaptive test to evaluate generic health a2010/12/07 a1470 v83 aBACKGROUND: Health Related Quality of Life (HRQoL) is a relevant variable in the evaluation of health outcomes. Questionnaires based on Classical Test Theory typically require a large number of items to evaluate HRQoL. Computer Adaptive Testing (CAT) can be used to reduce tests length while maintaining and, in some cases, improving accuracy. This study aimed at validating a CAT based on Item Response Theory (IRT) for evaluation of generic HRQoL: the CAT-Health instrument. METHODS: Cross-sectional study of subjects aged over 18 attending Primary Care Centres for any reason. CAT-Health was administered along with the SF-12 Health Survey. Age, gender and a checklist of chronic conditions were also collected. CAT-Health was evaluated considering: 1) feasibility: completion time and test length; 2) content range coverage, Item Exposure Rate (IER) and test precision; and 3) construct validity: differences in the CAT-Health scores according to clinical variables and correlations between both questionnaires. RESULTS: 396 subjects answered CAT-Health and SF-12, 67.2% females, mean age (SD) 48.6 (17.7) years. 36.9% did not report any chronic condition. Median completion time for CAT-Health was 81 seconds (IQ range = 59-118) and it increased with age (p < 0.001). The median number of items administered was 8 (IQ range = 6-10). Neither ceiling nor floor effects were found for the score. None of the items in the pool had an IER of 100% and it was over 5% for 27.1% of the items. Test Information Function (TIF) peaked between levels -1 and 0 of HRQoL. Statistically significant differences were observed in the CAT-Health scores according to the number and type of conditions. CONCLUSIONS: Although domain-specific CATs exist for various areas of HRQoL, CAT-Health is one of the first IRT-based CATs designed to evaluate generic HRQoL and it has proven feasible, valid and efficient, when administered to a broad sample of individuals attending primary care settings.1 aRebollo, P1 aCastejon, I1 aCuervo, J1 aVilla, G1 aGarcia-Cueto, E1 aDiaz-Cuervo, H1 aZardain, P C1 aMuniz, J1 aAlonso, J uhttp://www.iacat.org/content/validation-computer-adaptive-test-evaluate-generic-health-related-quality-life01276nas a2200121 4500008003900000245007100039210006900110300001000179490000700189520087700196100002901073856005201102 2010 d00aVariations on Stochastic Curtailment in Sequential Mastery Testing0 aVariations on Stochastic Curtailment in Sequential Mastery Testi a27-450 v343 a

In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability of changing classification decisions is low. The estimation of such a probability is therefore a critical component of a stochastically curtailed test. This article examines several variations on stochastic curtailment where the key probability is estimated more aggressively than the standard formulation, resulting in additional savings in average test length (ATL). In two simulation sets, the variations successfully reduced the ATL, and in many cases the average loss, compared with the standard formulation.

1 aFinkelman, Matthew David uhttp://apm.sagepub.com/content/34/1/27.abstract00496nas a2200097 4500008004100000245007500041210006900116260009700185100001500282856010100297 2009 eng d00aAdaptive computer-based tasks under an assessment engineering paradigm0 aAdaptive computerbased tasks under an assessment engineering par aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aLuecht, RM uhttp://www.iacat.org/content/adaptive-computer-based-tasks-under-assessment-engineering-paradigm01919nas a2200109 4500008004100000245010800041210006900149260009700218520135200315100001901667856012301686 2009 eng d00aAdaptive item calibration: A process for estimating item parameters within a computerized adaptive test0 aAdaptive item calibration A process for estimating item paramete aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThe characteristics of an adaptive test change the characteristics of the field testing that is necessary to add items to an existing measurement scale. The process used to add field-test items to the adaptive test might lead to scale drift or disrupt the test by administering items of inappropriate difficulty. The current study makes use of the transitivity of examinee and item in item response theory to describe a process for adaptive item calibration. In this process an item is successively administered to examinees whose ability levels match the performance of a given field-test item. By treating the item as if it were taking an adaptive test, examinees can be selected who provide the most information about the item at its momentary difficulty level. This should provide a more efficient procedure for estimating item parameters. The process is described within the context of the one-parameter logistic IRT model. The process is then simulated to identify whether it can be more accurate and efficient than random presentation of field-test items to examinees. Results indicated that adaptive item calibration might provide a viable approach to item calibration within the context of an adaptive test. It might be most useful for expanding item pools in settings with small sample sizes or needs for large numbers of items.1 aKingsbury, G G uhttp://www.iacat.org/content/adaptive-item-calibration-process-estimating-item-parameters-within-computerized-adaptive02651nas a2200181 4500008004100000020001400041245007900055210006900134300001000203490000700213520201300220653005202233653004002285100001502325700001302340700001502353856010102368 2009 eng d a0360-131500aAn adaptive testing system for supporting versatile educational assessment0 aadaptive testing system for supporting versatile educational ass a53-670 v523 aWith the rapid growth of computer and mobile technology, it is a challenge to integrate computer based test (CBT) with mobile learning (m-learning) especially for formative assessment and self-assessment. In terms of self-assessment, computer adaptive test (CAT) is a proper way to enable students to evaluate themselves. In CAT, students are assessed through a process that uses item response theory (IRT), a well-founded psychometric theory. Furthermore, a large item bank is indispensable to a test, but when a CAT system has a large item bank, the test item selection of IRT becomes more tedious. Besides the large item bank, item exposure mechanism is also essential to a testing system. However, IRT all lack the above-mentioned points. These reasons have motivated the authors to carry out this study. This paper describes a design issue aimed at the development and implementation of an adaptive testing system. The system can support several assessment functions and different devices. Moreover, the researchers apply a novel approach, particle swarm optimization (PSO) to alleviate the computational complexity and resolve the problem of item exposure. Throughout the development of the system, a formative evaluation was embedded into an integral part of the design methodology that was used for improving the system. After the system was formally released onto the web, some questionnaires and experiments were conducted to evaluate the usability, precision, and efficiency of the system. The results of these evaluations indicated that the system provides an adaptive testing for different devices and supports versatile assessment functions. Moreover, the system can estimate students' ability reliably and validly and conduct an adaptive test efficiently. Furthermore, the computational complexity of the system was alleviated by the PSO approach. By the approach, the test item selection procedure becomes efficient and the average best fitness values are very close to the optimal solutions.10aArchitectures for educational technology system10aDistance education and telelearning1 aHuang, Y-M1 aLin, Y-T1 aCheng, S-C uhttp://www.iacat.org/content/adaptive-testing-system-supporting-versatile-educational-assessment00590nas a2200121 4500008004100000245010000041210006900141260009700210100001600307700001500323700001500338856011500353 2009 eng d00aAdequacy of an item pool measuring proficiency in English language to implement a CAT procedure0 aAdequacy of an item pool measuring proficiency in English langua aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aKarino, C A1 aCosta, D R1 aLaros, J A uhttp://www.iacat.org/content/adequacy-item-pool-measuring-proficiency-english-language-implement-cat-procedure00636nas a2200145 4500008004100000245010000041210006900141260009700210100001300307700001300320700001300333700001400346700001700360856011300377 2009 eng d00aApplications of CAT in admissions to higher education in Israel: Twenty-two years of experience0 aApplications of CAT in admissions to higher education in Israel  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aGafni, N1 aCohen, Y1 aRoded, K1 aBaumer, M1 aMoshinsky, A uhttp://www.iacat.org/content/applications-cat-admissions-higher-education-israel-twenty-two-years-experience00571nas a2200109 4500008004100000245010000041210006900141260009700210100001400307700001700321856012300338 2009 eng d00aAn approach to implementing adaptive testing using item response theory both offline and online0 aapproach to implementing adaptive testing using item response th aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aPadaki, M1 aNatarajan, V uhttp://www.iacat.org/content/approach-implementing-adaptive-testing-using-item-response-theory-both-offline-and-online00568nas a2200121 4500008004100000245008900041210006900130260009800199100001400297700001300311700001300324856010900337 2009 eng d00aAssessing the equivalence of Internet-based vs. paper-and-pencil psychometric tests.0 aAssessing the equivalence of Internetbased vs paperandpencil psy a D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aBaumer, M1 aRoded, K1 aGafni, N uhttp://www.iacat.org/content/assessing-equivalence-internet-based-vs-paper-and-pencil-psychometric-tests00462nas a2200097 4500008004100000245006300041210006000104260009700164100001700261856008600278 2009 eng d00aAn automatic online calibration design in adaptive testing0 aautomatic online calibration design in adaptive testing aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aMakransky, G uhttp://www.iacat.org/content/automatic-online-calibration-design-adaptive-testing01940nas a2200121 4500008004100000245010300041210006900144260010000213520135600313100001601669700001401685856011901699 2009 eng d00aA burdened CAT: Incorporating response burden with maximum Fisher's information for item selection0 aburdened CAT Incorporating response burden with maximum Fishers  aIn D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aWidely used in various educational and vocational assessment applications, computerized adaptive testing (CAT) has recently begun to be used to measure patient-reported outcomes Although successful in reducing respondent burden, most current CAT algorithms do not formally consider it as part of the item selection process. This study used a loss function approach motivated by decision theory to develop an item selection method that incorporates respondent burden into the item selection process based on maximum Fisher information item selection. Several different loss functions placing varying degrees of importance on respondent burden were compared, using an item bank of 62 polytomous items measuring depressive symptoms. One dataset consisted of the real responses from the 730 subjects who responded to all the items. A second dataset consisted of simulated responses to all the items based on a grid of latent trait scores with replicates at each grid point. The algorithm enables a CAT administrator to more efficiently control the respondent burden without severely affecting the measurement precision than when using MFI alone. In particular, the loss function incorporating respondent burden protected respondents from receiving longer tests when their estimated trait score fell in a region where there were few informative items. 1 aSwartz, R J1 aChoi, S W uhttp://www.iacat.org/content/burdened-cat-incorporating-response-burden-maximum-fishers-information-item-selection00492nas a2200121 4500008004100000245008500041210006900126260001800195100001700213700001600230700001600246856010800262 2009 eng d00aComparing methods to recalibrate drifting items in computerized adaptive testing0 aComparing methods to recalibrate drifting items in computerized  aSan Diego, CA1 aMasters, J S1 aMuckle, T J1 aBontempo, B uhttp://www.iacat.org/content/comparing-methods-recalibrate-drifting-items-computerized-adaptive-testing00578nas a2200109 4500008004100000245011400041210006900155260009700224100001200321700001500333856012000348 2009 eng d00aComparison of ability estimation and item selection methods in multidimensional computerized adaptive testing0 aComparison of ability estimation and item selection methods in m aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aDiao, Q1 aReckase, M uhttp://www.iacat.org/content/comparison-ability-estimation-and-item-selection-methods-multidimensional-computerized00572nas a2200097 4500008004100000245013000041210006900171260009700240100001400337856012300351 2009 eng d00aComparison of adaptive Bayesian estimation and weighted Bayesian estimation in multidimensional computerized adaptive testing0 aComparison of adaptive Bayesian estimation and weighted Bayesian aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aChen, P H uhttp://www.iacat.org/content/comparison-adaptive-bayesian-estimation-and-weighted-bayesian-estimation-multidimensional01148nas a2200133 4500008003900000245006700039210006700106300001200173490000700185520072700192100001900919700002300938856005300961 2009 d00aComparison of CAT Item Selection Criteria for Polytomous Items0 aComparison of CAT Item Selection Criteria for Polytomous Items a419-4400 v333 a

Item selection is a core component in computerized adaptive testing (CAT). Several studies have evaluated new and classical selection methods; however, the few that have applied such methods to the use of polytomous items have reported conflicting results. To clarify these discrepancies and further investigate selection method properties, six different selection methods are compared systematically. The results showed no clear benefit from more sophisticated selection criteria and showed one method previously believed to be superior—the maximum expected posterior weighted information (MEPWI)—to be mathematically equivalent to a simpler method, the maximum posterior weighted information (MPWI).

1 aChoi, Seung, W1 aSwartz, Richard, J uhttp://apm.sagepub.com/content/33/6/419.abstract00437nas a2200121 4500008004100000245006700041210006700108300001400175490000700189100001400196700001600210856008900226 2009 eng d00aComparison of CAT item selection criteria for polytomous items0 aComparison of CAT item selection criteria for polytomous items a419–4400 v331 aChoi, S W1 aSwartz, R J uhttp://www.iacat.org/content/comparison-cat-item-selection-criteria-polytomous-items02949nas a2200205 4500008004100000020004100041245009800082210006900180250001500249260000800264300001200272490000700284520217900291653004302470653006402513100001702577700001402594700001802608856011702626 2009 eng d a0214-9915 (Print)0214-9915 (Linking)00aComparison of methods for controlling maximum exposure rates in computerized adaptive testing0 aComparison of methods for controlling maximum exposure rates in  a2009/05/01 cMay a313-3200 v213 aThis paper has two objectives: (a) to provide a clear description of three methods for controlling the maximum exposure rate in computerized adaptive testing —the Symson-Hetter method, the restricted method, and the item-eligibility method— showing how all three can be interpreted as methods for constructing the variable sub-bank of items from which each examinee receives the items in his or her test; (b) to indicate the theoretical and empirical limitations of each method and to compare their performance. With the three methods, we obtained basically indistinguishable results in overlap rate and RMSE (differences in the third decimal place). The restricted method is the best method for controlling exposure rate, followed by the item-eligibility method. The worst method is the Sympson-Hetter method. The restricted method presents problems of sequential overlap rate. Our advice is to use the item-eligibility method, as it saves time and satisfies the goals of restricting maximum exposure. Comparación de métodos para el control de tasa máxima en tests adaptativos informatizados. Este artículo tiene dos objetivos: (a) ofrecer una descripción clara de tres métodos para el control de la tasa máxima en tests adaptativos informatizados, el método Symson-Hetter, el método restringido y el métodode elegibilidad del ítem, mostrando cómo todos ellos pueden interpretarse como métodos para la construcción del subbanco de ítems variable, del cual cada examinado recibe los ítems de su test; (b) señalar las limitaciones teóricas y empíricas de cada método y comparar sus resultados. Se obtienen resultados básicamente indistinguibles en tasa de solapamiento y RMSE con los tres métodos (diferencias en la tercera posición decimal). El método restringido es el mejor en el control de la tasa de exposición,seguido por el método de elegibilidad del ítem. El peor es el método Sympson-Hetter. El método restringido presenta un problema de solapamiento secuencial. Nuestra recomendación sería utilizar el método de elegibilidad del ítem, puesto que ahorra tiempo y satisface los objetivos de limitar la tasa máxima de exposición.10a*Numerical Analysis, Computer-Assisted10aPsychological Tests/*standards/*statistics & numerical data1 aBarrada, J R1 aAbad, F J1 aVeldkamp, B P uhttp://www.iacat.org/content/comparison-methods-controlling-maximum-exposure-rates-computerized-adaptive-testing00595nas a2200133 4500008004100000245008600041210006900127260009700196100001500293700001600308700001700324700001700341856010300358 2009 eng d00aA comparison of three methods of item selection for computerized adaptive testing0 acomparison of three methods of item selection for computerized a aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aCosta, D R1 aKarino, C A1 aMoura, F A S1 aAndrade, D F uhttp://www.iacat.org/content/comparison-three-methods-item-selection-computerized-adaptive-testing02278nas a2200109 4500008004100000245008100041210006900122260009700191520175400288100001902042856010702061 2009 eng d00aComputerized adaptive testing by mutual information and multiple imputations0 aComputerized adaptive testing by mutual information and multiple aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aOver the years, most computerized adaptive testing (CAT) systems have used score estimation procedures from item response theory (IRT). IRT models have salutary properties for score estimation, error reporting, and next-item selection. However, some testing purposes favor scoring approaches outside IRT. Where a criterion metric is readily available and more relevant than the assessed construct, for example in the selection of job applicants, a predictive model might be appropriate (Scarborough & Somers, 2006). In these cases, neither IRT scoring nor a unidimensional assessment structure can be assumed. Yet, the primary benefit of CAT remains desirable: shorter assessments with minimal loss of accuracy due to unasked items. In such a case, it remains possible to create a CAT system that produces an estimated score from a subset of available items, recognizes differential item information given the emerging item response pattern, and optimizes the accuracy of the score estimated at every successive item. The method of multiple imputations (Rubin, 1987) can be used to simulate plausible scores given plausible response patterns to unasked items (Thissen-Roe, 2005). Mutual information can then be calculated in order to select an optimally informative next item (or set of items). Previously observed response patterns to two complete neural network-scored assessments were resampled according to MIMI CAT item selection. The reproduced CAT scores were compared to full-length assessment scores. Approximately 95% accurate assignment of examinees to one of three score categories was achieved with a 70%-80% reduction in median test length. Several algorithmic factors influencing accuracy and computational performance were examined.1 aThissen-Roe, A uhttp://www.iacat.org/content/computerized-adaptive-testing-mutual-information-and-multiple-imputations00448nas a2200097 4500008004100000245005800041210005800099260009700157100001300254856008300267 2009 eng d00aComputerized adaptive testing for cognitive diagnosis0 aComputerized adaptive testing for cognitive diagnosis aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aCheng, Y uhttp://www.iacat.org/content/computerized-adaptive-testing-cognitive-diagnosis00459nas a2200097 4500008004100000245010100041210006900142100001500211700001400226856012100240 2009 eng d00aComputerized adaptive testing using the two parameter logistic model with ability-based guessing0 aComputerized adaptive testing using the two parameter logistic m1 aShih, H -J1 aWang, W-C uhttp://www.iacat.org/content/computerized-adaptive-testing-using-two-parameter-logistic-model-ability-based-guessing00566nas a2200109 4500008004100000245010000041210006900141260009700210100001500307700001600322856011800338 2009 eng d00aComputerized classification testing in more than two categories by using stochastic curtailment0 aComputerized classification testing in more than two categories  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aWouda, J T1 aEggen, Theo uhttp://www.iacat.org/content/computerized-classification-testing-more-two-categories-using-stochastic-curtailment01700nas a2200157 4500008003900000022001400039245008000053210006900133300001300202490000700215520119700222100002301419700002301442700002201465856005501487 2009 d a1745-398400aA Conditional Exposure Control Method for Multidimensional Adaptive Testing0 aConditional Exposure Control Method for Multidimensional Adaptiv a84–1030 v463 a

In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed for tests employing the unidimensional 3-PL model. The present article explores the issues associated with controlling exposure rates when a multidimensional item response theory (MIRT) model is utilized and exposure rates must be controlled conditional upon ability. This situation is complicated by the exponentially increasing number of possible ability values in multiple dimensions. The article introduces a new procedure, called the generalized Stocking-Lewis method, that controls the exposure rate for students of comparable ability as well as with respect to the overall population. A realistic simulation set compares the new method with three other approaches: Kullback-Leibler information with no exposure control, Kullback-Leibler information with unconditional Sympson-Hetter exposure control, and random item selection.

1 aFinkelman, Matthew1 aNering, Michael, L1 aRoussos, Louis, A uhttp://dx.doi.org/10.1111/j.1745-3984.2009.01070.x00495nas a2200133 4500008004100000245008000041210006900121300001100190490000700201100001700208700001600225700001700241856010300258 2009 eng d00aA conditional exposure control method for multidimensional adaptive testing0 aconditional exposure control method for multidimensional adaptiv a84-1030 v461 aFinkelman, M1 aNering, M L1 aRoussos, L A uhttp://www.iacat.org/content/conditional-exposure-control-method-multidimensional-adaptive-testing01452nas a2200205 4500008004100000020004100041245016200082210006900244250001500313300001100328490000700339520065200346653002500998653001501023653003701038653002401075100001401099700001501113856011801128 2009 eng d a1529-7713 (Print)1529-7713 (Linking)00aConsiderations about expected a posteriori estimation in adaptive testing: adaptive a priori, adaptive correction for bias, and adaptive integration interval0 aConsiderations about expected a posteriori estimation in adaptiv a2009/07/01 a138-560 v103 aIn a computerized adaptive test, we would like to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Unfortunately, decreasing the number of items is accompanied by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. The authors suggest that it is possible to reduced the bias, and even the standard error of the estimate, by applying to each provisional estimation one or a combination of the following strategies: adaptive correction for bias proposed by Bock and Mislevy (1982), adaptive a priori estimate, and adaptive integration interval.10a*Bias (Epidemiology)10a*Computers10aData Interpretation, Statistical10aModels, Statistical1 aRaiche, G1 aBlais, J G uhttp://www.iacat.org/content/considerations-about-expected-posteriori-estimation-adaptive-testing-adaptive-priori00513nas a2200109 4500008004100000245006900041210006900110260009700179100001500276700001600291856009600307 2009 eng d00aConstrained item selection using a stochastically curtailed SPRT0 aConstrained item selection using a stochastically curtailed SPRT aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aWouda, J T1 aEggen, Theo uhttp://www.iacat.org/content/constrained-item-selection-using-stochastically-curtailed-sprt00618nas a2200145 4500008004100000245016200041210006900203300001000272490000700282100001300289700001900302700001500321700001100336856012500347 2009 eng d00aConstraint-weighted a-stratification for computerized adaptive testing with nonstatistical constraints: Balancing measurement efficiency and exposure control0 aConstraintweighted astratification for computerized adaptive tes a35-490 v691 aCheng, Y1 aChang, Hua-Hua1 aDouglas, J1 aGuo, F uhttp://www.iacat.org/content/constraint-weighted-stratification-computerized-adaptive-testing-nonstatistical-constraints01651nas a2200157 4500008003900000245010700039210006900146300001000215490000700225520113900232100001501371700001901386700002101405700001501426856005201441 2009 d00aConstraint-Weighted a-Stratification for Computerized Adaptive Testing With Nonstatistical Constraints0 aConstraintWeighted aStratification for Computerized Adaptive Tes a35-490 v693 a

a-stratification is a method that utilizes items with small discrimination (a) parameters early in an exam and those with higher a values when more is learned about the ability parameter. It can achieve much better item usage than the maximum information criterion (MIC). To make a-stratification more practical and more widely applicable, a method for weighting the item selection process in a-stratification as a means of satisfying multiple test constraints is proposed. This method is studied in simulation against an analogous method without stratification as well as a-stratification using descending-rather than ascending-a procedures. In addition, a variation of a-stratification that allows for unbalanced usage of a parameters is included in the study to examine the trade-off between efficiency and exposure control. Finally, MIC and randomized item selection are included as baseline measures. Results indicate that the weighting mechanism successfully addresses the constraints, that stratification helps to a great extent balancing exposure rates, and that the ascending-a design improves measurement precision.

1 aYing Cheng1 aChang, Hua-Hua1 aDouglas, Jeffrey1 aFanmin Guo uhttp://epm.sagepub.com/content/69/1/35.abstract01893nas a2200157 4500008004100000245007800041210006900119260009700188520126000285100001801545700001801563700002001581700001701601700001601618856010101634 2009 eng d00aCriterion-related validity of an innovative CAT-based personality measure0 aCriterionrelated validity of an innovative CATbased personality  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThis paper describes development and initial criterion-related validation of the PreVisor Computer Adaptive Personality Scales (PCAPS), a computerized adaptive testing-based personality measure that uses an ideal point IRT model based on forced-choice, paired-comparison responses. Based on results from a large consortium study, a composite of six PCAPS scales identified as relevant to the population of interest (first-line supervisors) had an estimated operational validity against an overall job performance criterion of ρ = .25. Uncorrected and corrected criterion-related validity results for each of the six PCAPS scales making up the composite are also reported. Because the PCAPS algorithm computes intermediate scale scores until a stopping rule is triggered, we were able to graph number of statement-pairs presented against criterion-related validities. Results showed generally monotonically increasing functions. However, asymptotic validity levels, or at least a reduction in the rate of increase in slope, were often reached after 5-7 statement-pairs were presented. In the case of the composite measure, there was some evidence that validities decreased after about six statement-pairs. A possible explanation for this is provided.1 aSchneider, RJ1 aMcLellan, R A1 aKantrowitz, T M1 aHouston, J S1 aBorman, W C uhttp://www.iacat.org/content/criterion-related-validity-innovative-cat-based-personality-measure01663nas a2200145 4500008004100000245004900041210004800090260009700138520115900235100001301394700001101407700001401418700001101432856007401443 2009 eng d00aDeveloping item variants: An empirical study0 aDeveloping item variants An empirical study aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aLarge-scale standardized test have been widely used for educational and licensure testing. In computerized adaptive testing (CAT), one of the practical concerns for maintaining large-scale assessments is to ensure adequate numbers of high-quality items that are required for item pool functioning. Developing items at specific difficulty levels and for certain areas of test plans is a wellknown challenge. The purpose of this study was to investigate strategies for varying items that can effectively generate items at targeted difficulty levels and specific test plan areas. Each variant item generation model was developed by decomposing selected source items possessing ideal measurement properties and targeting the desirable content domains. 341 variant items were generated from 72 source items. Data were collected from six pretest periods. Items were calibrated using the Rasch model. Initial results indicate that variant items showed desirable measurement properties. Additionally, compared to an average of approximately 60% of the items passing pretest criteria, an average of 84% of the variant items passed the pretest criteria. 1 aWendt, A1 aKao, S1 aGorham, J1 aWoo, A uhttp://www.iacat.org/content/developing-item-variants-empirical-study02749nas a2200409 4500008004100000020004600041245009400087210006900181250001500250260000800265300001200273490000700285520144500292653001501737653002001752653003101772653003001803653002001833653001901853653002601872653001101898653001101909653000901920653001601929653002601945653003701971653003002008653004402038653001802082653002002100653002802120100002002148700002302168700001602191700001702207856011502224 2009 eng d a1528-8447 (Electronic)1526-5900 (Linking)00aDevelopment and preliminary testing of a computerized adaptive assessment of chronic pain0 aDevelopment and preliminary testing of a computerized adaptive a a2009/07/15 cSep a932-9430 v103 aThe aim of this article is to report the development and preliminary testing of a prototype computerized adaptive test of chronic pain (CHRONIC PAIN-CAT) conducted in 2 stages: (1) evaluation of various item selection and stopping rules through real data-simulated administrations of CHRONIC PAIN-CAT; (2) a feasibility study of the actual prototype CHRONIC PAIN-CAT assessment system conducted in a pilot sample. Item calibrations developed from a US general population sample (N = 782) were used to program a pain severity and impact item bank (kappa = 45), and real data simulations were conducted to determine a CAT stopping rule. The CHRONIC PAIN-CAT was programmed on a tablet PC using QualityMetric's Dynamic Health Assessment (DYHNA) software and administered to a clinical sample of pain sufferers (n = 100). The CAT was completed in significantly less time than the static (full item bank) assessment (P < .001). On average, 5.6 items were dynamically administered by CAT to achieve a precise score. Scores estimated from the 2 assessments were highly correlated (r = .89), and both assessments discriminated across pain severity levels (P < .001, RV = .95). Patients' evaluations of the CHRONIC PAIN-CAT were favorable. PERSPECTIVE: This report demonstrates that the CHRONIC PAIN-CAT is feasible for administration in a clinic. The application has the potential to improve pain assessment and help clinicians manage chronic pain.10a*Computers10a*Questionnaires10aActivities of Daily Living10aAdaptation, Psychological10aChronic Disease10aCohort Studies10aDisability Evaluation10aFemale10aHumans10aMale10aMiddle Aged10aModels, Psychological10aOutcome Assessment (Health Care)10aPain Measurement/*methods10aPain, Intractable/*diagnosis/psychology10aPsychometrics10aQuality of Life10aUser-Computer Interface1 aAnatchkova, M D1 aSaris-Baglama, R N1 aKosinski, M1 aBjorner, J B uhttp://www.iacat.org/content/development-and-preliminary-testing-computerized-adaptive-assessment-chronic-pain02881nas a2200493 4500008004100000020004100041245014100082210006900223250001500292260000800307300001100315490000700326520125100333653003001584653001001614653000901624653004601633653003301679653001101712653003101723653001101754653000901765653003301774653001601807653002401823653004601847653005501893653005501948653004602003653001902049653003102068653001402099100001602113700001502129700001302144700001402157700001502171700001702186700001502203700001702218700001502235700001302250856012402263 2009 eng d a0090-5550 (Print)0090-5550 (Linking)00aDevelopment of an item bank for the assessment of depression in persons with mental illnesses and physical diseases using Rasch analysis0 aDevelopment of an item bank for the assessment of depression in  a2009/05/28 cMay a186-970 v543 aOBJECTIVE: The calibration of item banks provides the basis for computerized adaptive testing that ensures high diagnostic precision and minimizes participants' test burden. The present study aimed at developing a new item bank that allows for assessing depression in persons with mental and persons with somatic diseases. METHOD: The sample consisted of 161 participants treated for a depressive syndrome, and 206 participants with somatic illnesses (103 cardiologic, 103 otorhinolaryngologic; overall mean age = 44.1 years, SD =14.0; 44.7% women) to allow for validation of the item bank in both groups. Persons answered a pool of 182 depression items on a 5-point Likert scale. RESULTS: Evaluation of Rasch model fit (infit < 1.3), differential item functioning, dimensionality, local independence, item spread, item and person separation (>2.0), and reliability (>.80) resulted in a bank of 79 items with good psychometric properties. CONCLUSIONS: The bank provides items with a wide range of content coverage and may serve as a sound basis for computerized adaptive testing applications. It might also be useful for researchers who wish to develop new fixed-length scales for the assessment of depression in specific rehabilitation settings.10aAdaptation, Psychological10aAdult10aAged10aDepressive Disorder/*diagnosis/psychology10aDiagnosis, Computer-Assisted10aFemale10aHeart Diseases/*psychology10aHumans10aMale10aMental Disorders/*psychology10aMiddle Aged10aModels, Statistical10aOtorhinolaryngologic Diseases/*psychology10aPersonality Assessment/statistics & numerical data10aPersonality Inventory/*statistics & numerical data10aPsychometrics/statistics & numerical data10aQuestionnaires10aReproducibility of Results10aSick Role1 aForkmann, T1 aBoecker, M1 aNorra, C1 aEberle, N1 aKircher, T1 aSchauerte, P1 aMischke, K1 aWesthofen, M1 aGauggel, S1 aWirtz, M uhttp://www.iacat.org/content/development-item-bank-assessment-depression-persons-mental-illnesses-and-physical-diseases00512nas a2200121 4500008003900000245011000039210006900149300001000218490000600228100001200234700002000246856012400266 2009 d00aDiagnostic classification models and multidimensional adaptive testing: A commentary on Rupp and Templin.0 aDiagnostic classification models and multidimensional adaptive t a58-610 v71 aFrey, A1 aCarstensen, C H uhttp://www.iacat.org/content/diagnostic-classification-models-and-multidimensional-adaptive-testing-commentary-rupp-and00480nas a2200121 4500008004100000245008700041210006900128300001200197490000700209100001500216700001900231856010800250 2009 eng d00a Direct and inverse problems of item pool design for computerized adaptive testing0 aDirect and inverse problems of item pool design for computerized a533-5470 v691 aBelov, D I1 aArmstrong, R D uhttp://www.iacat.org/content/direct-and-inverse-problems-item-pool-design-computerized-adaptive-testing01210nas a2200133 4500008003900000245008600039210006900125300001200194490000700206520076400213100002100977700002500998856005301023 2009 d00aDirect and Inverse Problems of Item Pool Design for Computerized Adaptive Testing0 aDirect and Inverse Problems of Item Pool Design for Computerized a533-5470 v693 a

The recent literature on computerized adaptive testing (CAT) has developed methods for creating CAT item pools from a large master pool. Each CAT pool is designed as a set of nonoverlapping forms reflecting the skill levels of an assumed population of test takers. This article presents a Monte Carlo method to obtain these CAT pools and discusses its advantages over existing methods. Also, a new problem is considered that finds a population ability density function best matching the master pool. An analysis of the solution to this new problem provides testing organizations with effective guidance for maintaining their master pools. Computer experiments with a pool of Law School Admission Test items and its assembly constraints are presented.

1 aBelov, Dmitry, I1 aArmstrong, Ronald, D uhttp://epm.sagepub.com/content/69/4/533.abstract00531nas a2200109 4500008004100000245008500041210006900126260009700195100001500292700001400307856010000321 2009 eng d00aEffect of early misfit in computerized adaptive testing on the recovery of theta0 aEffect of early misfit in computerized adaptive testing on the r aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aGuyer, R D1 aWeiss, DJ uhttp://www.iacat.org/content/effect-early-misfit-computerized-adaptive-testing-recovery-theta-000567nas a2200133 4500008004400000245013200044210007000176300001000246490000700256100001200263700001400275700001900289856012500308 2009 Germdn 00aEffekte des adaptiven Testens auf die Moti¬vation zur Testbearbeitung [Effects of adaptive testing on test taking motivation].0 aEffekte des adaptiven Testens auf die Moti¬vation zur Testbearbe a20-280 v551 aFrey, A1 aHartig, J1 aMoosbrugger, H uhttp://www.iacat.org/content/effekte-des-adaptiven-testens-auf-die-moti%C2%ACvation-zur-testbearbeitung-effects-adaptive02370nas a2200217 4500008004100000020002200041245010800063210006900171250001500240260001000255300001200265490000700277520166400284100001401948700001401962700001601976700001201992700001702004700001502021856011602036 2009 Eng d a1049-8931 (Print)00aEvaluation of a computer-adaptive test for the assessment of depression (D-CAT) in clinical application0 aEvaluation of a computeradaptive test for the assessment of depr a2009/02/06 cFeb 4 a233-2360 v183 aIn the past, a German Computerized Adaptive Test, based on Item Response Theory (IRT), was developed for purposes of assessing the construct depression [Computer-adaptive test for depression (D-CAT)]. This study aims at testing the feasibility and validity of the real computer-adaptive application.The D-CAT, supplied by a bank of 64 items, was administered on personal digital assistants (PDAs) to 423 consecutive patients suffering from psychosomatic and other medical conditions (78 with depression). Items were adaptively administered until a predetermined reliability (r >/= 0.90) was attained. For validation purposes, the Hospital Anxiety and Depression Scale (HADS), the Centre for Epidemiological Studies Depression (CES-D) scale, and the Beck Depression Inventory (BDI) were administered. Another sample of 114 patients was evaluated using standardized diagnostic interviews [Composite International Diagnostic Interview (CIDI)].The D-CAT was quickly completed (mean 74 seconds), well accepted by the patients and reliable after an average administration of only six items. In 95% of the cases, 10 items or less were needed for a reliable score estimate. Correlations between the D-CAT and the HADS, CES-D, and BDI ranged between r = 0.68 and r = 0.77. The D-CAT distinguished between diagnostic groups as well as established questionnaires do.The D-CAT proved an efficient, well accepted and reliable tool. Discriminative power was comparable to other depression measures, whereby the CAT is shorter and more precise. Item usage raises questions of balancing the item selection for content in the future. Copyright (c) 2009 John Wiley & Sons, Ltd.1 aFliege, H1 aBecker, J1 aWalter, O B1 aRose, M1 aBjorner, J B1 aKlapp, B F uhttp://www.iacat.org/content/evaluation-computer-adaptive-test-assessment-depression-d-cat-clinical-application00616nas a2200121 4500008004100000245012600041210006900167260009700236100001100333700001700344700001400361856011900375 2009 eng d00aAn evaluation of a new procedure for computing information functions for Bayesian scores from computerized adaptive tests0 aevaluation of a new procedure for computing information function aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aIto, K1 aPommerich, M1 aSegall, D uhttp://www.iacat.org/content/evaluation-new-procedure-computing-information-functions-bayesian-scores-computerized02751nas a2200433 4500008004100000020004600041245012800087210006900215250001500284300001200299490000700311520139300318653003401711653001501745653001001760653000901770653002201779653002501801653001101826653001101837653000901848653001601857653001501873653003801888653001901926653003101945653002801976653004802004653002202052100002002074700001202094700001402106700001602120700001402136700001702150700001502167700001502182856012002197 2009 eng d a1878-5921 (Electronic)0895-4356 (Linking)00aAn evaluation of patient-reported outcomes found computerized adaptive testing was efficient in assessing stress perception0 aevaluation of patientreported outcomes found computerized adapti a2008/07/22 a278-2870 v623 aOBJECTIVES: This study aimed to develop and evaluate a first computerized adaptive test (CAT) for the measurement of stress perception (Stress-CAT), in terms of the two dimensions: exposure to stress and stress reaction. STUDY DESIGN AND SETTING: Item response theory modeling was performed using a two-parameter model (Generalized Partial Credit Model). The evaluation of the Stress-CAT comprised a simulation study and real clinical application. A total of 1,092 psychosomatic patients (N1) were studied. Two hundred simulees (N2) were generated for a simulated response data set. Then the Stress-CAT was given to n=116 inpatients, (N3) together with established stress questionnaires as validity criteria. RESULTS: The final banks included n=38 stress exposure items and n=31 stress reaction items. In the first simulation study, CAT scores could be estimated with a high measurement precision (SE<0.32; rho>0.90) using 7.0+/-2.3 (M+/-SD) stress reaction items and 11.6+/-1.7 stress exposure items. The second simulation study reanalyzed real patients data (N1) and showed an average use of items of 5.6+/-2.1 for the dimension stress reaction and 10.0+/-4.9 for the dimension stress exposure. Convergent validity showed significantly high correlations. CONCLUSIONS: The Stress-CAT is short and precise, potentially lowering the response burden of patients in clinical decision making.10a*Diagnosis, Computer-Assisted10aAdolescent10aAdult10aAged10aAged, 80 and over10aConfidence Intervals10aFemale10aHumans10aMale10aMiddle Aged10aPerception10aQuality of Health Care/*standards10aQuestionnaires10aReproducibility of Results10aSickness Impact Profile10aStress, Psychological/*diagnosis/psychology10aTreatment Outcome1 aKocalevent, R D1 aRose, M1 aBecker, J1 aWalter, O B1 aFliege, H1 aBjorner, J B1 aKleiber, D1 aKlapp, B F uhttp://www.iacat.org/content/evaluation-patient-reported-outcomes-found-computerized-adaptive-testing-was-efficient01982nas a2200109 4500008004100000245006600041210006200107260009700169520149900266100001601765856009101781 2009 eng d00aAn examination of decision-theory adaptive testing procedures0 aexamination of decisiontheory adaptive testing procedures aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThis research examined three ways to adaptively select items using decision theory: a traditional decision theory sequential testing approach (expected minimum cost), information gain (modeled after Kullback-Leibler), and a maximum discrimination approach, and then compared them all against an approach using maximum IRT Fisher information. It also examined the use of Wald’s (1947) wellknown sequential probability ratio test, SPRT, as a test termination rule in this context. The minimum cost approach was notably better than the best-case possibility for IRT. Information gain, which is based on entropy and comes from information theory, was almost identical to minimum cost. The simple approach using the item that best discriminates between the two most likely classifications also fared better than IRT, but not as well as information gain or minimum cost. Through Wald’s SPRT, large percentages of examinees can be accurately classified with very few items. With only 25 sequentially selected items, for example, approximately 90% of the simulated NAEP examinees were classified with 86% accuracy. The advantages of the decision theory model are many—the model yields accurate mastery state classifications, can use a small item pool, is simple to implement, requires little pretesting, is applicable to criterion-referenced tests, can be used in diagnostic testing, can be adapted to yield classifications on multiple skills, and should be easy to explain to non-statisticians.1 aRudner, L M uhttp://www.iacat.org/content/examination-decision-theory-adaptive-testing-procedures-000633nas a2200181 4500008004100000245006000041210005700101260009700158100001200255700001100267700001600278700001500294700001300309700001600322700001300338700001600351856008400367 2009 eng d00aFeatures of J-CAT (Japanese Computerized Adaptive Test)0 aFeatures of JCAT Japanese Computerized Adaptive Test aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aImai, S1 aIto, S1 aNakamura, Y1 aKikuchi, K1 aAkagi, Y1 aNakasono, H1 aHonda, A1 aHiramura, T uhttp://www.iacat.org/content/features-j-cat-japanese-computerized-adaptive-test00459nas a2200109 4500008004100000245008900041210006900130300001400199490000700213100001400220856011500234 2009 eng d00aFirestar: Computerized adaptive testing simulation program for polytomous IRT models0 aFirestar Computerized adaptive testing simulation program for po a644–6450 v331 aChoi, S W uhttp://www.iacat.org/content/firestar-computerized-adaptive-testing-simulation-program-polytomous-irt-models-000562nas a2200145 4500008004100000020004600041245008900087210006900176250001500245260001000260300001200270490000700282100001400289856011300303 2009 Eng d a1552-3497 (Electronic)0146-6216 (Linking)00aFirestar: Computerized adaptive testing simulation program for polytomous IRT models0 aFirestar Computerized adaptive testing simulation program for po a2009/12/17 cNov 1 a644-6450 v331 aChoi, S W uhttp://www.iacat.org/content/firestar-computerized-adaptive-testing-simulation-program-polytomous-irt-models00541nas a2200097 4500008004100000245010000041210006900141260009700210100001300307856012300320 2009 eng d00aA gradual maximum information ratio approach to item selection in computerized adaptive testing0 agradual maximum information ratio approach to item selection in  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aHan, K T uhttp://www.iacat.org/content/gradual-maximum-information-ratio-approach-item-selection-computerized-adaptive-testing-000500nas a2200097 4500008004100000245009800041210006900139260006000208100001300268856012100281 2009 eng d00aGradual maximum information ratio approach to item selection in computerized adaptive testing0 aGradual maximum information ratio approach to item selection in  aMcLean, VA. USAbGraduate Management Admissions Council1 aHan, K T uhttp://www.iacat.org/content/gradual-maximum-information-ratio-approach-item-selection-computerized-adaptive-testing00572nas a2200109 4500008004100000245010200041210006900143260009700212100002200309700001100331856012000342 2009 eng d00aGuess what? Score differences with rapid replies versus omissions on a computerized adaptive test0 aGuess what Score differences with rapid replies versus omissions aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aTalento-Miller, E1 aGuo, F uhttp://www.iacat.org/content/guess-what-score-differences-rapid-replies-versus-omissions-computerized-adaptive-test00478nas a2200109 4500008004100000245006200041210006000103260009700163100001600260700001400276856007800290 2009 eng d00aA hybrid simulation procedure for the development of CATs0 ahybrid simulation procedure for the development of CATs aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aNydick, S W1 aWeiss, DJ uhttp://www.iacat.org/content/hybrid-simulation-procedure-development-cats01386nas a2200241 4500008004100000020002700041245005000068210005000118250001500168300001000183490000600193520067500199653002600874653001100900653004200911653002400953653001800977653002000995653001901015100001501034700001601049856007901065 2009 eng d a1548-5951 (Electronic)00aItem response theory and clinical measurement0 aItem response theory and clinical measurement a2008/11/04 a27-480 v53 aIn this review, we examine studies that use item response theory (IRT) to explore the psychometric properties of clinical measures. Next, we consider how IRT has been used in clinical research for: scale linking, computerized adaptive testing, and differential item functioning analysis. Finally, we consider the scale properties of IRT trait scores. We conclude that there are notable differences between cognitive and clinical measures that have relevance for IRT modeling. Future research should be directed toward a better understanding of the metric of the latent trait and the psychological processes that lead to individual differences in item response behaviors.10a*Psychological Theory10aHumans10aMental Disorders/diagnosis/psychology10aPsychological Tests10aPsychometrics10aQuality of Life10aQuestionnaires1 aReise, S P1 aWaller, N G uhttp://www.iacat.org/content/item-response-theory-and-clinical-measurement00556nas a2200121 4500008004100000245008100041210006900122260009700191100001700288700001400305700001600319856009900335 2009 eng d00aItem selection and hypothesis testing for the adaptive measurement of change0 aItem selection and hypothesis testing for the adaptive measureme aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aFinkelman, M1 aWeiss, DJ1 aKim-Kang, G uhttp://www.iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change01422nas a2200133 4500008004100000020001400041245005800055210005800113300001200171490000700183520099600190100001801186856008401204 2009 eng d a0013-164400aItem selection in computerized classification testing0 aItem selection in computerized classification testing a778-7930 v693 aSeveral alternatives for item selection algorithms based on item response theory in computerized classification testing (CCT) have been suggested, with no conclusive evidence on the substantial superiority of a single method. It is argued that the lack of sizable effect is because some of the methods actually assess items very similarly through different calculations and will usually select the same item. Consideration of methods that assess information across a wider range is often unnecessary under realistic conditions, although it might be advantageous to utilize them only early in a test. In addition, the efficiency of item selection approaches depend on the termination criteria that are used, which is demonstrated through didactic example and Monte Carlo simulation. Item selection at the cut score, which seems conceptually appropriate for CCT, is not always the most efficient option. A broad framework for item selection in CCT is presented that incorporates these points. 1 aThompson, N A uhttp://www.iacat.org/content/item-selection-computerized-classification-testing01377nas a2200121 4500008003900000245005800039210005800097300001200155490000700167520100400174100002401178856005301202 2009 d00aItem Selection in Computerized Classification Testing0 aItem Selection in Computerized Classification Testing a778-7930 v693 a

Several alternatives for item selection algorithms based on item response theory in computerized classification testing (CCT) have been suggested, with no conclusive evidence on the substantial superiority of a single method. It is argued that the lack of sizable effect is because some of the methods actually assess items very similarly through different calculations and will usually select the same item. Consideration of methods that assess information across a wider range is often unnecessary under realistic conditions, although it might be advantageous to utilize them only early in a test. In addition, the efficiency of item selection approaches depend on the termination criteria that are used, which is demonstrated through didactic example and Monte Carlo simulation. Item selection at the cut score, which seems conceptually appropriate for CCT, is not always the most efficient option. A broad framework for item selection in CCT is presented that incorporates these points.

1 aThompson, Nathan, A uhttp://epm.sagepub.com/content/69/5/778.abstract00516nas a2200145 4500008004100000245008100041210006900122300000900191490000600200100001700206700001200223700001500235700001400250856010600264 2009 eng d00aItem selection rules in computerized adaptive testing: Accuracy and security0 aItem selection rules in computerized adaptive testing Accuracy a a7-170 v51 aBarrada, J R1 aOlea, J1 aPonsoda, V1 aAbad, F J uhttp://www.iacat.org/content/item-selection-rules-computerized-adaptive-testing-accuracy-and-security00460nas a2200109 4500008004100000245005600041210005300097260009700150100001300247700001300260856007700273 2009 eng d00aItem selection with biased-coin up-and-down designs0 aItem selection with biasedcoin upanddown designs aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aSheng, Y1 aSheng, Z uhttp://www.iacat.org/content/item-selection-biased-coin-and-down-designs00488nas a2200121 4500008004100000245009800041210006900139300001100208490001000219100001200229700001300241856011200254 2009 eng d00aI've fallen and I can't get up: can high-ability students recover from early mistakes in CAT?0 aIve fallen and I cant get up can highability students recover fr a83-1010 v33(2)1 aRulison1 aLoken, E uhttp://www.iacat.org/content/ive-fallen-and-i-cant-get-can-high-ability-students-recover-early-mistakes-cat01482nas a2200133 4500008003900000245009800039210006900137300001100206490000700217520103400224100002201258700001601280856005201296 2009 d00aI've Fallen and I Can't Get Up: Can High-Ability Students Recover From Early Mistakes in CAT?0 aIve Fallen and I Cant Get Up Can HighAbility Students Recover Fr a83-1010 v333 a

A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimate initially drops and then ascends continuously until the test ends, suggesting that the true ability may be higher than implied by the final estimate. This study explains why this asymmetry occurs and shows that early mistakes by high-ability students can lead to considerable underestimation, even in tests with 45 items. The opposite response pattern, where low-ability students start with lucky guesses, leads to much less bias. The authors show that using Barton and Lord's four-parameter model (4PM) and a less informative prior can lower bias and root mean square error (RMSE) for high-ability students with a poor start, as the CAT algorithm ascends more quickly after initial underperformance. Results also show that the 4PM slightly outperforms a CAT in which less discriminating items are initially used. The practical implications and relevance for psychological measurement more generally are discussed.

1 aRulison, Kelly, L1 aLoken, Eric uhttp://apm.sagepub.com/content/33/2/83.abstract01482nas a2200133 4500008003900000245009800039210006900137300001100206490000700217520103400224100002201258700001601280856005201296 2009 d00aI've Fallen and I Can't Get Up: Can High-Ability Students Recover From Early Mistakes in CAT?0 aIve Fallen and I Cant Get Up Can HighAbility Students Recover Fr a83-1010 v333 a

A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimate initially drops and then ascends continuously until the test ends, suggesting that the true ability may be higher than implied by the final estimate. This study explains why this asymmetry occurs and shows that early mistakes by high-ability students can lead to considerable underestimation, even in tests with 45 items. The opposite response pattern, where low-ability students start with lucky guesses, leads to much less bias. The authors show that using Barton and Lord's four-parameter model (4PM) and a less informative prior can lower bias and root mean square error (RMSE) for high-ability students with a poor start, as the CAT algorithm ascends more quickly after initial underperformance. Results also show that the 4PM slightly outperforms a CAT in which less discriminating items are initially used. The practical implications and relevance for psychological measurement more generally are discussed.

1 aRulison, Kelly, L1 aLoken, Eric uhttp://apm.sagepub.com/content/33/2/83.abstract01413nas a2200121 4500008003900000245009000039210006900129300001200198490000700210520100200217100001501219856005701234 2009 d00aA Knowledge-Based Approach for Item Exposure Control in Computerized Adaptive Testing0 aKnowledgeBased Approach for Item Exposure Control in Computerize a530-5580 v343 a

The purpose of this study is to investigate a functional relation between item exposure parameters (IEPs) and item parameters (IPs) over parallel pools. This functional relation is approximated by a well-known tool in machine learning. Let P and Q be parallel item pools and suppose IEPs for P have been obtained via a Sympson and Hetter–type simulation. Based on these simulated parameters, a functional relation k = fP (a, b, c) relating IPs to IEPs of P is obtained by an artificial neural network and used to estimate IEPs of Q without tedious simulation. Extensive experiments using real and synthetic pools showed that this approach worked pretty well for many variants of the Sympson and Hetter procedure. It worked excellently for the conditional Stocking and Lewis multinomial selection procedure and the Chen and Lei item exposure and test overlap control procedure. This study provides the first step in an alternative means to estimate IEPs without iterative simulation.

1 aDoong, S H uhttp://jeb.sagepub.com/cgi/content/abstract/34/4/53002035nas a2200121 4500008004100000245009400041210006900135260009700204520146200301100001201763700001901775856011901794 2009 eng d00aKullback-Leibler information in multidimensional adaptive testing: theory and application0 aKullbackLeibler information in multidimensional adaptive testing aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aBuilt on multidimensional item response theory (MIRT), multidimensional adaptive testing (MAT) can, in principle, provide a promising choice to ensuring efficient estimation of each ability dimension in a multidimensional vector. Currently, two item selection procedures have been developed for MAT, one based on Fisher information embedded within a Bayesian framework, and the other powered by Kullback-Leibler (KL) information. It is well-known that in unidimensional IRT that the second derivative of KL information (also termed “global information”) is Fisher information evaluated atθ 0. This paper first generalizes the relationship between these two types of information in two ways—the analytical result is given as well as the graphical representation, to enhance interpretation and understanding. Second, a KL information index is constructed for MAT, which represents the integration of KL nformation over all of the ability dimensions. This paper further discusses how this index correlates with the item discrimination parameters. The analytical results would lay foundation for future development of item selection methods in MAT which can help equalize the item exposure rate. Finally, a simulation study is conducted to verify the above results. The connection between the item parameters, item KL information, and item exposure rate is demonstrated for empirical MAT delivered by an item bank calibrated under two-dimensional IRT.1 aWang, C1 aChang, Hua-Hua uhttp://www.iacat.org/content/kullback-leibler-information-multidimensional-adaptive-testing-theory-and-application00578nas a2200133 4500008004100000245007700041210006900118260011100187100001000298700001400308700001400322700001100336856009700347 2009 eng d00aLimiting item exposure for target difficulty ranges in a high-stakes CAT0 aLimiting item exposure for target difficulty ranges in a highsta aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing. {PDF File, 1.1 aLi, X1 aBecker, K1 aGorham, J1 aWoo, A uhttp://www.iacat.org/content/limiting-item-exposure-target-difficulty-ranges-high-stakes-cat01919nas a2200169 4500008004100000020002200041245011800063210006900181250001500250260000800265300001100273490000700284520130600291100001201597700001401609856012601623 2009 eng d a0962-9343 (Print)00aLogistics of collecting patient-reported outcomes (PROs) in clinical practice: an overview and practical examples0 aLogistics of collecting patientreported outcomes PROs in clinica a2009/01/20 cFeb a125-360 v183 aPURPOSE: Interest in collecting patient-reported outcomes (PROs), such as health-related quality of life (HRQOL), health status reports, and patient satisfaction is on the rise and practical aspects of collecting PROs in clinical practice are becoming more important. The purpose of this paper is to draw the attention to a number of issues relevant for a successful integration of PRO measures into the daily work flow of busy clinical settings. METHODS: The paper summarizes the results from a breakout session held at an ISOQOL special topic conference for PRO measures in clinical practice in 2007. RESULTS: Different methodologies of collecting PROs are discussed, and the support needed for each methodology is highlighted. The discussion is illustrated by practical real-life examples from early adaptors who administered paper-pencil, or electronic PRO assessments (ePRO) for more than a decade. The paper also reports about new experiences with more recent technological developments, such as SmartPens and Computer Adaptive Tests (CATs) in daily practice. CONCLUSIONS: Methodological and logistical issues determine the resources needed for a successful integration of PRO measures into daily work flow procedures and influence significantly the usefulness of PRO data for clinical practice.1 aRose, M1 aBezjak, A uhttp://www.iacat.org/content/logistics-collecting-patient-reported-outcomes-pros-clinical-practice-overview-and-practical01654nas a2200289 4500008004100000020004100041245011100082210006900193250001500262260000800277300001100285490000700296520053700303653004800840653006200888653005700950653001101007653002701018653002401045653005101069653004701120653003101167653001301198100001301211700001901224856012101243 2009 eng d a0007-1102 (Print)0007-1102 (Linking)00aThe maximum priority index method for severely constrained item selection in computerized adaptive testing0 amaximum priority index method for severely constrained item sele a2008/06/07 cMay a369-830 v623 aThis paper introduces a new heuristic approach, the maximum priority index (MPI) method, for severely constrained item selection in computerized adaptive testing. Our simulation study shows that it is able to accommodate various non-statistical constraints simultaneously, such as content balancing, exposure control, answer key balancing, and so on. Compared with the weighted deviation modelling method, it leads to fewer constraint violations and better exposure control while maintaining the same level of measurement precision.10aAptitude Tests/*statistics & numerical data10aDiagnosis, Computer-Assisted/*statistics & numerical data10aEducational Measurement/*statistics & numerical data10aHumans10aMathematical Computing10aModels, Statistical10aPersonality Tests/*statistics & numerical data10aPsychometrics/*statistics & numerical data10aReproducibility of Results10aSoftware1 aCheng, Y1 aChang, Hua-Hua uhttp://www.iacat.org/content/maximum-priority-index-method-severely-constrained-item-selection-computerized-adaptive03147nas a2200457 4500008004100000020004100041245015500082210006900237250001500306260000800321300001200329490000700341520174100348653002502089653001902114653002502133653003002158653001502188653003602203653001002239653002102249653003302270653001102303653001102314653000902325653001802334653001702352653001902369653001602388100001502404700001002419700001502429700002502444700001802469700001702487700001602504700001602520700001402536700001602550856012302566 2009 eng d a0962-9343 (Print)0962-9343 (Linking)00aMeasuring global physical health in children with cerebral palsy: Illustration of a multidimensional bi-factor model and computerized adaptive testing0 aMeasuring global physical health in children with cerebral palsy a2009/02/18 cApr a359-3700 v183 aPURPOSE: The purposes of this study were to apply a bi-factor model for the determination of test dimensionality and a multidimensional CAT using computer simulations of real data for the assessment of a new global physical health measure for children with cerebral palsy (CP). METHODS: Parent respondents of 306 children with cerebral palsy were recruited from four pediatric rehabilitation hospitals and outpatient clinics. We compared confirmatory factor analysis results across four models: (1) one-factor unidimensional; (2) two-factor multidimensional (MIRT); (3) bi-factor MIRT with fixed slopes; and (4) bi-factor MIRT with varied slopes. We tested whether the general and content (fatigue and pain) person score estimates could discriminate across severity and types of CP, and whether score estimates from a simulated CAT were similar to estimates based on the total item bank, and whether they correlated as expected with external measures. RESULTS: Confirmatory factor analysis suggested separate pain and fatigue sub-factors; all 37 items were retained in the analyses. From the bi-factor MIRT model with fixed slopes, the full item bank scores discriminated across levels of severity and types of CP, and compared favorably to external instruments. CAT scores based on 10- and 15-item versions accurately captured the global physical health scores. CONCLUSIONS: The bi-factor MIRT CAT application, especially the 10- and 15-item versions, yielded accurate global physical health scores that discriminated across known severity groups and types of CP, and correlated as expected with concurrent measures. The CATs have potential for collecting complex data on the physical health of children with CP in an efficient manner.10a*Computer Simulation10a*Health Status10a*Models, Statistical10aAdaptation, Psychological10aAdolescent10aCerebral Palsy/*physiopathology10aChild10aChild, Preschool10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMassachusetts10aPennsylvania10aQuestionnaires10aYoung Adult1 aHaley, S M1 aNi, P1 aDumas, H M1 aFragala-Pinkham, M A1 aHambleton, RK1 aMontpetit, K1 aBilodeau, N1 aGorton, G E1 aWatson, K1 aTucker, C A uhttp://www.iacat.org/content/measuring-global-physical-health-children-cerebral-palsy-illustration-multidimensional-bi01066nas a2200109 4500008004100000245010200041210006900143260009700212520051300309100001800822856011600840 2009 eng d00aThe MEDPRO project: An SBIR project for a comprehensive IRT and CAT software system: CAT software0 aMEDPRO project An SBIR project for a comprehensive IRT and CAT s aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aDevelopment of computerized adaptive tests (CAT) requires a number of appropriate software tools. This paper describes the development of two new CAT software programs. CATSIM has been designed specifically to conduct several different kinds of simulation studies, which are necessary for planning purposes as well as properly designing live CATs. FastCAT is a software system for banking items and publishing CAT tests as standalone files, to be administered anywhere. Both are available for public use.1 aThompson, N A uhttp://www.iacat.org/content/medpro-project-sbir-project-comprehensive-irt-and-cat-software-system-cat-software01207nas a2200109 4500008004100000245010200041210006900143260009700212520065700309100001500966856011600981 2009 eng d00aThe MEDPRO project: An SBIR project for a comprehensive IRT and CAT software system: IRT software0 aMEDPRO project An SBIR project for a comprehensive IRT and CAT s aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aIRTPRO (Item Response Theory for Patient-Reported Outcomes) is an entirely new application for item calibration and test scoring using IRT. IRTPRO implements algorithms for maximum likelihood estimation of item parameters (item calibration) for several unidimensional and multidimensional item response theory (IRT) models for dichotomous and polytomous item responses. In addition, the software provides computation of goodness-of-fit indices, statistics for the diagnosis of local dependence and for the detection of differential item functioning (DIF), and IRT scaled scores. This paper illustrates the use, and some capabilities, of the software.1 aThissen, D uhttp://www.iacat.org/content/medpro-project-sbir-project-comprehensive-irt-and-cat-software-system-irt-software01524nas a2200181 4500008004100000020001400041245007400055210006900129300001200198490000800210520093200218653001401150653002401164653002301188100001501211700001901226856009701245 2009 eng d a0377-221700aA mixed integer programming model for multiple stage adaptive testing0 amixed integer programming model for multiple stage adaptive test a342-3500 v1933 aThe last decade has seen paper-and-pencil (P&P) tests being replaced by computerized adaptive tests (CATs) within many testing programs. A CAT may yield several advantages relative to a conventional P&P test. A CAT can determine the questions or test items to administer, allowing each test form to be tailored to a test taker's skill level. Subsequent items can be chosen to match the capability of the test taker. By adapting to a test taker's ability, a CAT can acquire more information about a test taker while administering fewer items. A Multiple Stage Adaptive test (MST) provides a means to implement a CAT that allows review before the administration. The MST format is a hybrid between the conventional P&P and CAT formats. This paper presents mixed integer programming models for MST assembly problems. Computational results with commercial optimization software will be given and advantages of the models evaluated.10aEducation10aInteger programming10aLinear programming1 aEdmonds, J1 aArmstrong, R D uhttp://www.iacat.org/content/mixed-integer-programming-model-multiple-stage-adaptive-testing01383nas a2200145 4500008004100000020001300041245012000054210006900174300001000243490000700253520082700260100001201087700001501099856012301114 2009 eng d a0191491X00aMultidimensional adaptive testing in educational and psychological measurement: Current state and future challenges0 aMultidimensional adaptive testing in educational and psychologic a89-940 v353 aThe paper gives an overview of multidimensional adaptive testing (MAT) and evaluates its applicability in educational and psychological testing. The approach of Segall (1996) is described as a general framework for MAT. The main advantage of MAT is its capability to increase measurement efficiency. In simulation studies conceptualizing situations typical to large scale assessments, the number of presented items was reduced by MAT by about 30–50% compared to unidimensional adaptive testing and by about 70% compared to fixed item testing holding measurement precision constant. Empirical results underline these findings. Before MAT is used routinely some open questions should be answered first. After that, MAT represents a very promising approach to highly efficient simultaneous testing of multiple competencies.1 aFrey, A1 aSeitz, N-N uhttp://www.iacat.org/content/multidimensional-adaptive-testing-educational-and-psychological-measurement-current-state01903nas a2200169 4500008004100000020004100041245008600082210006900168250001500237260000800252300001200260490000700272520131100279100001401590700002301604856010601627 2009 Eng d a0033-3123 (Print)0033-3123 (Linking)00aMultidimensional Adaptive Testing with Optimal Design Criteria for Item Selection0 aMultidimensional Adaptive Testing with Optimal Design Criteria f a2010/02/02 cJun a273-2960 v743 aSeveral criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the abilities. Both the theoretical analyses and the studies of simulated data in this paper suggest that the criteria of A-optimality and D-optimality lead to the most accurate estimates when all abilities are intentional, with the former slightly outperforming the latter. The criterion of E-optimality showed occasional erratic behavior for this case of adaptive testing, and its use is not recommended. If some of the abilities are nuisances, application of the criterion of A(s)-optimality (or D(s)-optimality), which focuses on the subset of intentional abilities is recommended. For the measurement of a linear combination of abilities, the criterion of c-optimality yielded the best results. The preferences of each of these criteria for items with specific patterns of parameter values was also assessed. It was found that the criteria differed mainly in their preferences of items with different patterns of values for their discrimination parameters.1 aMulder, J1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-optimal-design-criteria-item-selection01773nas a2200145 4500008003900000245006900039210006900108300001000177490000700187520131500194100002501509700002501534700001601559856005201575 2009 d00aMultiple Maximum Exposure Rates in Computerized Adaptive Testing0 aMultiple Maximum Exposure Rates in Computerized Adaptive Testing a58-730 v333 a

Computerized adaptive testing is subject to security problems, as the item bank content remains operative over long periods and administration time is flexible for examinees. Spreading the content of a part of the item bank could lead to an overestimation of the examinees' trait level. The most common way of reducing this risk is to impose a maximum exposure rate (rmax) that no item should exceed. Several methods have been proposed with this aim. All of these methods establish a single value of rmax throughout the test. This study presents a new method, the multiple-rmax method, that defines as many values of rmax as the number of items presented in the test. In this way, it is possible to impose a high degree of randomness in item selection at the beginning of the test, leaving the administration of items with the best psychometric properties to the moment when the trait level estimation is most accurate. The implementation of the multiple-r max method is described and is tested in simulated item banks and in an operative bank. Compared with a single maximum exposure method, the new method has a more balanced usage of the item bank and delays the possible distortion of trait estimation due to security problems, with either no or only slight decrements of measurement accuracy.

1 aBarrada, Juan Ramón1 aVeldkamp, Bernard, P1 aOlea, Julio uhttp://apm.sagepub.com/content/33/1/58.abstract02048nas a2200133 4500008004100000245006100041210005500102260010000157520152600257100001701783700001601800700001601816856008201832 2009 eng d00aThe nine lives of CAT-ASVAB: Innovations and revelations0 anine lives of CATASVAB Innovations and revelations aIn D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThe Armed Services Vocational Aptitude Battery (ASVAB) is administered annually to more than one million military applicants and high school students. ASVAB scores are used to determine enlistment eligibility, assign applicants to military occupational specialties, and aid students in career exploration. The ASVAB is administered as both a paper-and-pencil (P&P) test and a computerized adaptive test (CAT). CAT-ASVAB holds the distinction of being the first large-scale adaptive test battery to be administered in a high-stakes setting. Approximately two-thirds of military applicants currently take CAT-ASVAB; long-term plans are to replace P&P-ASVAB with CAT-ASVAB at all test sites. Given CAT-ASVAB’s pedigree—approximately 20 years in development and 20 years in operational administration—much can be learned from revisiting some of the major highlights of CATASVAB history. This paper traces the progression of CAT-ASVAB through nine major phases of development including: research and evelopment of the CAT-ASVAB prototype, the initial development of psychometric procedures and item pools, initial and full-scale operational implementation, the introduction of new item pools, the introduction of Windows administration, the introduction of Internet administration, and research and development of the next generation CATASVAB. A background and history is provided for each phase, including discussions of major research and operational issues, innovative approaches and practices, and lessons learned.1 aPommerich, M1 aSegall, D O1 aMoreno, K E uhttp://www.iacat.org/content/nine-lives-cat-asvab-innovations-and-revelations00544nas a2200121 4500008004100000245007000041210006900111260009700180100001200277700001900289700001500308856009900323 2009 eng d00aObtaining reliable diagnostic information through constrained CAT0 aObtaining reliable diagnostic information through constrained CA aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aWang, C1 aChang, Hua-Hua1 aDouglas, J uhttp://www.iacat.org/content/obtaining-reliable-diagnostic-information-through-constrained-cat00581nas a2200109 4500008004100000245011800041210006900159260009700228100001700325700001300342856011600355 2009 eng d00aOptimizing item exposure control algorithms for polytomous computerized adaptive tests with restricted item banks0 aOptimizing item exposure control algorithms for polytomous compu aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aChajewski, M1 aLewis, C uhttp://www.iacat.org/content/optimizing-item-exposure-control-algorithms-polytomous-computerized-adaptive-tests00518nas a2200109 4500008004100000245013200041210006900173490001000242100001500252700001500267856012600282 2009 eng d00aa posteriori estimation in adaptive testing: Adaptive a priori, adaptive correction for bias, and adaptive integration interval0 aposteriori estimation in adaptive testing Adaptive a priori adap0 v10(2)1 aRaîche, G1 aBlais, J-G uhttp://www.iacat.org/content/posteriori-estimation-adaptive-testing-adaptive-priori-adaptive-correction-bias-and-adaptive00538nas a2200121 4500008004100000245007800041210006900119260009700188100001500285700001200300700001100312856009300323 2009 eng d00aPractical issues concerning the application of the DINA model to CAT data0 aPractical issues concerning the application of the DINA model to aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aHuebner, A1 aWang, B1 aLee, S uhttp://www.iacat.org/content/practical-issues-concerning-application-dina-model-cat-data01013nas a2200121 4500008003900000245005800039210005800097300001000155490000700165520064800172100001900820856005200839 2009 d00aPredictive Control of Speededness in Adaptive Testing0 aPredictive Control of Speededness in Adaptive Testing a25-410 v333 a

An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the responses on these items as an additional source of information. In a simulation study with an adaptive test modeled after a test from the Armed Services Vocational Aptitude Battery, the effectiveness of the methods in removing differential speededness from the test was evaluated.

1 aLinden, Wim, J uhttp://apm.sagepub.com/content/33/1/25.abstract02904nas a2200289 4500008004100000020004100041245011100082210006900193250001500262260000800277300001400285490000700299520193300306653002702239653003802266653004102304653001902345653001102364653001402375653003102389100001502420700001302435700001202448700001602460700001302476856012502489 2009 eng d a0315-162X (Print)0315-162X (Linking)00aProgress in assessing physical function in arthritis: PROMIS short forms and computerized adaptive testing0 aProgress in assessing physical function in arthritis PROMIS shor a2009/09/10 cSep a2061-20660 v363 aOBJECTIVE: Assessing self-reported physical function/disability with the Health Assessment Questionnaire Disability Index (HAQ) and other instruments has become central in arthritis research. Item response theory (IRT) and computerized adaptive testing (CAT) techniques can increase reliability and statistical power. IRT-based instruments can improve measurement precision substantially over a wider range of disease severity. These modern methods were applied and the magnitude of improvement was estimated. METHODS: A 199-item physical function/disability item bank was developed by distilling 1865 items to 124, including Legacy Health Assessment Questionnaire (HAQ) and Physical Function-10 items, and improving precision through qualitative and quantitative evaluation in over 21,000 subjects, which included about 1500 patients with rheumatoid arthritis and osteoarthritis. Four new instruments, (A) Patient-Reported Outcomes Measurement Information (PROMIS) HAQ, which evolved from the original (Legacy) HAQ; (B) "best" PROMIS 10; (C) 20-item static (short) forms; and (D) simulated PROMIS CAT, which sequentially selected the most informative item, were compared with the HAQ. RESULTS: Online and mailed administration modes yielded similar item and domain scores. The HAQ and PROMIS HAQ 20-item scales yielded greater information content versus other scales in patients with more severe disease. The "best" PROMIS 20-item scale outperformed the other 20-item static forms over a broad range of 4 standard deviations. The 10-item simulated PROMIS CAT outperformed all other forms. CONCLUSION: Improved items and instruments yielded better information. The PROMIS HAQ is currently available and considered validated. The new PROMIS short forms, after validation, are likely to represent further improvement. CAT-based physical function/disability assessment offers superior performance over static forms of equal length.10a*Disability Evaluation10a*Outcome Assessment (Health Care)10aArthritis/diagnosis/*physiopathology10aHealth Surveys10aHumans10aPrognosis10aReproducibility of Results1 aFries, J F1 aCella, D1 aRose, M1 aKrishnan, E1 aBruce, B uhttp://www.iacat.org/content/progress-assessing-physical-function-arthritis-promis-short-forms-and-computerized-adaptive00703nas a2200109 4500008004100000245020500041210006900246260011100315100002400426700001700450856012600467 2009 eng d00aProposta para a construo de um Teste Adaptativo Informatizado baseado na Teoria da Resposta ao Item (Proposal for the construction of a Computerized Adaptive Testing based on the Item Response Theory)0 aProposta para a construo de um Teste Adaptativo Informatizado ba aPoster session presented at the Congresso Brasileiro de Teoria da Resposta ao Item, Florianpolis SC Brazil1 aMoreira Junior, F J1 aAndrade, D F uhttp://www.iacat.org/content/proposta-para-construo-de-um-teste-adaptativo-informatizado-baseado-na-teoria-da-resposta-ao00431nas a2200097 4500008004100000245005500041210005500096260009700151100001100248856007400259 2009 eng d00aQuantifying the impact of compromised items in CAT0 aQuantifying the impact of compromised items in CAT aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aGuo, F uhttp://www.iacat.org/content/quantifying-impact-compromised-items-cat02597nas a2200337 4500008004100000020004600041245012800087210006900215250001500284300000700299490000600306520149200312653003201804653002301836653002501859653003401884653001101918653001101929653000901940653002601949653003101975653002702006653001102033653001802044100001502062700001202077700001402089700001802103700001202121856012602133 2009 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aReduction in patient burdens with graphical computerized adaptive testing on the ADL scale: tool development and simulation0 aReduction in patient burdens with graphical computerized adaptiv a2009/05/07 a390 v73 aBACKGROUND: The aim of this study was to verify the effectiveness and efficacy of saving time and reducing burden for patients, nurses, and even occupational therapists through computer adaptive testing (CAT). METHODS: Based on an item bank of the Barthel Index (BI) and the Frenchay Activities Index (FAI) for assessing comprehensive activities of daily living (ADL) function in stroke patients, we developed a visual basic application (VBA)-Excel CAT module, and (1) investigated whether the averaged test length via CAT is shorter than that of the traditional all-item-answered non-adaptive testing (NAT) approach through simulation, (2) illustrated the CAT multimedia on a tablet PC showing data collection and response errors of ADL clinical functional measures in stroke patients, and (3) demonstrated the quality control of endorsing scale with fit statistics to detect responding errors, which will be further immediately reconfirmed by technicians once patient ends the CAT assessment. RESULTS: The results show that endorsed items could be shorter on CAT (M = 13.42) than on NAT (M = 23) at 41.64% efficiency in test length. However, averaged ability estimations reveal insignificant differences between CAT and NAT. CONCLUSION: This study found that mobile nursing services, placed at the bedsides of patients could, through the programmed VBA-Excel CAT module, reduce the burden to patients and save time, more so than the traditional NAT paper-and-pencil testing appraisals.10a*Activities of Daily Living10a*Computer Graphics10a*Computer Simulation10a*Diagnosis, Computer-Assisted10aFemale10aHumans10aMale10aPoint-of-Care Systems10aReproducibility of Results10aStroke/*rehabilitation10aTaiwan10aUnited States1 aChien, T W1 aWu, H M1 aWang, W-C1 aCastillo, R V1 aChou, W uhttp://www.iacat.org/content/reduction-patient-burdens-graphical-computerized-adaptive-testing-adl-scale-tool-development02435nas a2200385 4500008004100000020004100041245009300082210006900175250001500244260000800259300001100267490000700278520128100285653003201566653002701598653002001625653002901645653001001674653000901684653001901693653003401712653001101746653001101757653000901768653001601777653004601793100001501839700001001854700001501864700001101879700001201890700001401902700001601916856011701932 2009 eng d a0962-9343 (Print)0962-9343 (Linking)00aReplenishing a computerized adaptive test of patient-reported daily activity functioning0 aReplenishing a computerized adaptive test of patientreported dai a2009/03/17 cMay a461-710 v183 aPURPOSE: Computerized adaptive testing (CAT) item banks may need to be updated, but before new items can be added, they must be linked to the previous CAT. The purpose of this study was to evaluate 41 pretest items prior to including them into an operational CAT. METHODS: We recruited 6,882 patients with spine, lower extremity, upper extremity, and nonorthopedic impairments who received outpatient rehabilitation in one of 147 clinics across 13 states of the USA. Forty-one new Daily Activity (DA) items were administered along with the Activity Measure for Post-Acute Care Daily Activity CAT (DA-CAT-1) in five separate waves. We compared the scoring consistency with the full item bank, test information function (TIF), person standard errors (SEs), and content range of the DA-CAT-1 to the new CAT (DA-CAT-2) with the pretest items by real data simulations. RESULTS: We retained 29 of the 41 pretest items. Scores from the DA-CAT-2 were more consistent (ICC = 0.90 versus 0.96) than DA-CAT-1 when compared with the full item bank. TIF and person SEs were improved for persons with higher levels of DA functioning, and ceiling effects were reduced from 16.1% to 6.1%. CONCLUSIONS: Item response theory and online calibration methods were valuable in improving the DA-CAT.10a*Activities of Daily Living10a*Disability Evaluation10a*Questionnaires10a*User-Computer Interface10aAdult10aAged10aCohort Studies10aComputer-Assisted Instruction10aFemale10aHumans10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods1 aHaley, S M1 aNi, P1 aJette, A M1 aTao, W1 aMoed, R1 aMeyers, D1 aLudlow, L H uhttp://www.iacat.org/content/replenishing-computerized-adaptive-test-patient-reported-daily-activity-functioning01380nas a2200133 4500008003900000245013100039210006900170300001200239490000700251520087800258100002701136700003001163856005301193 2009 d00aStudying the Equivalence of Computer-Delivered and Paper-Based Administrations of the Raven Standard Progressive Matrices Test0 aStudying the Equivalence of ComputerDelivered and PaperBased Adm a855-8670 v693 a

This study investigates the effect of mode of administration of the Raven Standard Progressive Matrices test on distribution, accuracy, and meaning of raw scores. A random sample of high school students take counterbalanced paper-and-pencil and computer-based administrations of the test and answer a questionnaire surveying preferences for computer-delivered test administrations. Administration mode effect is studied with repeated measures multivariate analysis of variance, internal consistency reliability estimates, and confirmatory factor analysis approaches. Results show a lack of test mode effect on distribution, accuracy, and meaning of raw scores. Participants indicate their preferences for the computer-delivered administration of the test. The article discusses findings in light of previous studies of the Raven Standard Progressive Matrices test.

1 aArce-Ferrer, Alvaro, J1 aMartínez Guzmán, Elvira uhttp://epm.sagepub.com/content/69/5/855.abstract00557nas a2200109 4500008003900000245009400039210006900133260009800202100001500300700001400315856011800329 2009 d00aTermination criteria in computerized adaptive tests: Variable-length CATs are not biased.0 aTermination criteria in computerized adaptive tests Variableleng a D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aBabcock, B1 aWeiss, DJ uhttp://www.iacat.org/content/termination-criteria-computerized-adaptive-tests-variable-length-cats-are-not-biased00587nas a2200133 4500008004100000245008400041210006900125260009700194100001700291700001200308700001500320700001400335856010400349 2009 eng d00aTest overlap rate and item exposure rate as indicators of test security in CATs0 aTest overlap rate and item exposure rate as indicators of test s aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aBarrada, J R1 aOlea, J1 aPonsoda, V1 aAbad, F J uhttp://www.iacat.org/content/test-overlap-rate-and-item-exposure-rate-indicators-test-security-cats00525nas a2200121 4500008004100000245006800041210006800109260009700177100001100274700001300285700001500298856009000313 2009 eng d00aUsing automatic item generation to address item demands for CAT0 aUsing automatic item generation to address item demands for CAT aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aLai, H1 aAlves, C1 aGierl, M J uhttp://www.iacat.org/content/using-automatic-item-generation-address-item-demands-cat02021nas a2200109 4500008004100000245007400041210006900115260009700184520151800281100001801799856009401817 2009 eng d00aUtilizing the generalized likelihood ratio as a termination criterion0 aUtilizing the generalized likelihood ratio as a termination crit aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aComputer-based testing can be used to classify examinees into mutually exclusive groups. Currently, the predominant psychometric algorithm for designing computerized classification tests (CCTs) is the sequential probability ratio test (SPRT; Reckase, 1983) based on item response theory (IRT). The SPRT has been shown to be more efficient than confidence intervals around θ estimates as a method for CCT delivery (Spray & Reckase, 1996; Rudner, 2002). More recently, it was demonstrated that the SPRT, which only uses fixed values, is less efficient than a generalized form which tests whether a given examinee’s θ is below θ1or above θ2 (Thompson, 2007). This formulation allows the indifference region to vary based on observed data. Moreover, this composite hypothesis formulation better represents the conceptual purpose of the test, which is to test whether θ is above or below the cutscore. The purpose of this study was to explore the specifications of the new generalized likelihood ratio (GLR; Huang, 2004). As with the SPRT, the efficiency of the procedure depends on the nominal error rates and the distance between θ1 and θ2 (Eggen, 1999). This study utilized a monte-carlo approach, with 10,000 examinees simulated under each condition, to evaluate differences in efficiency and accuracy due to hypothesis structure, nominal error rate, and indifference region size. The GLR was always at least as efficient as the fixed-point SPRT while maintaining equivalent levels of accuracy. 1 aThompson, N A uhttp://www.iacat.org/content/utilizing-generalized-likelihood-ratio-termination-criterion01674nas a2200157 4500008004100000020001400041245010500055210006900160300001200229490000600241520109700247100001601344700002001360700001601380856012001396 2009 eng d a1939-148X00aValidation of the MMPI-2 computerized adaptive version (MMPI-2-CA) in a correctional intake facility0 aValidation of the MMPI2 computerized adaptive version MMPI2CA in a279-2920 v63 aComputerized adaptive testing in personality assessment can improve efficiency by significantly reducing the number of items administered to answer an assessment question. The time savings afforded by this technique could be of particular benefit in settings where large numbers of psychological screenings are conducted, such as correctional facilities. In the current study, item and time savings, as well as the test–retest and extratest correlations associated with an audio augmented administration of all the scales of the Minnesota Multiphasic Personality Inventory (MMPI)-2 Computerized Adaptive (MMPI-2-CA) are reported. Participants include 366 men, ages 18 to 62 years (M = 33.04, SD = 10.40), undergoing intake into a large Midwestern state correctional facility. Results of the current study indicate considerable item and corresponding time savings for the MMPI-2-CA compared to conventional administration of the test, as well as comparability in terms of test–retest and correlations with external measures. Future directions of adaptive personality testing are discussed.1 aForbey, J D1 aBen-Porath, Y S1 aGartland, D uhttp://www.iacat.org/content/validation-mmpi-2-computerized-adaptive-version-mmpi-2-ca-correctional-intake-facility00426nas a2200109 4500008004100000245007300041210006900114300001200183490000700195100001300202856010100215 2009 eng d00aWhen cognitive diagnosis meets computerized adaptive testing: CD-CAT0 aWhen cognitive diagnosis meets computerized adaptive testing CDC a619-6320 v741 aCheng, Y uhttp://www.iacat.org/content/when-cognitive-diagnosis-meets-computerized-adaptive-testing-cd-cat00375nas a2200121 4500008004100000245004600041210004600087300001000133490000800143100001600151700001400167856007200181 2008 eng d00aAdaptive measurement of individual change0 aAdaptive measurement of individual change a49-580 v2161 aKim-Kang, G1 aWeiss, DJ uhttp://www.iacat.org/content/adaptive-measurement-individual-change00351nas a2200109 4500008003900000245004500039210004500084300000800129490000800137100002300145856007300168 2008 d00aAdaptive Models of Psychological Testing0 aAdaptive Models of Psychological Testing a1-20 v2161 avan der Linden, WJ uhttp://www.iacat.org/content/adaptive-models-psychological-testing-000357nas a2200109 4500008004100000245004500041210004500086300001100131490001100142100002300153856007100176 2008 eng d00aAdaptive models of psychological testing0 aAdaptive models of psychological testing a3–110 v216(1)1 avan der Linden, WJ uhttp://www.iacat.org/content/adaptive-models-psychological-testing02865nas a2200325 4500008004100000020002700041245007400068210006900142250001500211260000800226300001100234490000700245520188300252653003202135653003202167653002502199653002302224653004802247653001102295653001102306653000902317653001602326653001902342653002702361100001502388700001502403700001002418700001202428856009902440 2008 eng d a1537-7385 (Electronic)00aAdaptive short forms for outpatient rehabilitation outcome assessment0 aAdaptive short forms for outpatient rehabilitation outcome asses a2008/09/23 cOct a842-520 v873 aOBJECTIVE: To develop outpatient Adaptive Short Forms for the Activity Measure for Post-Acute Care item bank for use in outpatient therapy settings. DESIGN: A convenience sample of 11,809 adults with spine, lower limb, upper limb, and miscellaneous orthopedic impairments who received outpatient rehabilitation in 1 of 127 outpatient rehabilitation clinics in the United States. We identified optimal items for use in developing outpatient Adaptive Short Forms based on the Basic Mobility and Daily Activities domains of the Activity Measure for Post-Acute Care item bank. Patient scores were derived from the Activity Measure for Post-Acute Care computerized adaptive testing program. Items were selected for inclusion on the Adaptive Short Forms based on functional content, range of item coverage, measurement precision, item exposure rate, and data collection burden. RESULTS: Two outpatient Adaptive Short Forms were developed: (1) an 18-item Basic Mobility Adaptive Short Form and (2) a 15-item Daily Activities Adaptive Short Form, derived from the same item bank used to develop the Activity Measure for Post-Acute Care computerized adaptive testing program. Both Adaptive Short Forms achieved acceptable psychometric properties. CONCLUSIONS: In outpatient postacute care settings where computerized adaptive testing outcome applications are currently not feasible, item response theory-derived Adaptive Short Forms provide the efficient capability to monitor patients' functional outcomes. The development of Adaptive Short Form functional outcome instruments linked by a common, calibrated item bank has the potential to create a bridge to outcome monitoring across postacute care settings and can facilitate the eventual transformation from Adaptive Short Forms to computerized adaptive testing applications easier and more acceptable to the rehabilitation community.10a*Activities of Daily Living10a*Ambulatory Care Facilities10a*Mobility Limitation10a*Treatment Outcome10aDisabled Persons/psychology/*rehabilitation10aFemale10aHumans10aMale10aMiddle Aged10aQuestionnaires10aRehabilitation Centers1 aJette, A M1 aHaley, S M1 aNi, P1 aMoed, R uhttp://www.iacat.org/content/adaptive-short-forms-outpatient-rehabilitation-outcome-assessment00717nas a2200229 4500008004100000020004100041245005200082210005100134250001500185260000800200300000800208490000700216653003400223653005000257653001100307653003200318653001300350100001500363700001500378700001800393856007600411 2008 eng d a1075-2730 (Print)1075-2730 (Linking)00aAre we ready for computerized adaptive testing?0 aAre we ready for computerized adaptive testing a2008/04/02 cApr a3690 v5910a*Attitude of Health Personnel10a*Diagnosis, Computer-Assisted/instrumentation10aHumans10aMental Disorders/*diagnosis10aSoftware1 aUnick, G J1 aShumway, M1 aHargreaves, W uhttp://www.iacat.org/content/are-we-ready-computerized-adaptive-testing03436nas a2200481 4500008004100000020004600041245013800087210006900225250001500294260000800309300001200317490000700329520191400336653002702250653002302277653003102300653001502331653001602346653001002362653002102372653002402393653002302417653003802440653001102478653002202489653001102511653001102522653000902533653003702542653002102579653003102600653002602631653001702657653003202674653001602706653002802722100001602750700001502766700001002781700001502791700002502806856012302831 2008 eng d a1532-821X (Electronic)0003-9993 (Linking)00aAssessing self-care and social function using a computer adaptive testing version of the pediatric evaluation of disability inventory0 aAssessing selfcare and social function using a computer adaptive a2008/04/01 cApr a622-6290 v893 aOBJECTIVE: To examine score agreement, validity, precision, and response burden of a prototype computer adaptive testing (CAT) version of the self-care and social function scales of the Pediatric Evaluation of Disability Inventory compared with the full-length version of these scales. DESIGN: Computer simulation analysis of cross-sectional and longitudinal retrospective data; cross-sectional prospective study. SETTING: Pediatric rehabilitation hospital, including inpatient acute rehabilitation, day school program, outpatient clinics; community-based day care, preschool, and children's homes. PARTICIPANTS: Children with disabilities (n=469) and 412 children with no disabilities (analytic sample); 38 children with disabilities and 35 children without disabilities (cross-validation sample). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Summary scores from prototype CAT applications of each scale using 15-, 10-, and 5-item stopping rules; scores from the full-length self-care and social function scales; time (in seconds) to complete assessments and respondent ratings of burden. RESULTS: Scores from both computer simulations and field administration of the prototype CATs were highly consistent with scores from full-length administration (r range, .94-.99). Using computer simulation of retrospective data, discriminant validity, and sensitivity to change of the CATs closely approximated that of the full-length scales, especially when the 15- and 10-item stopping rules were applied. In the cross-validation study the time to administer both CATs was 4 minutes, compared with over 16 minutes to complete the full-length scales. CONCLUSIONS: Self-care and social function score estimates from CAT administration are highly comparable with those obtained from full-length scale administration, with small losses in validity and precision and substantial decreases in administration time.10a*Disability Evaluation10a*Social Adjustment10aActivities of Daily Living10aAdolescent10aAge Factors10aChild10aChild, Preschool10aComputer Simulation10aCross-Over Studies10aDisabled Children/*rehabilitation10aFemale10aFollow-Up Studies10aHumans10aInfant10aMale10aOutcome Assessment (Health Care)10aReference Values10aReproducibility of Results10aRetrospective Studies10aRisk Factors10aSelf Care/*standards/trends10aSex Factors10aSickness Impact Profile1 aCoster, W J1 aHaley, S M1 aNi, P1 aDumas, H M1 aFragala-Pinkham, M A uhttp://www.iacat.org/content/assessing-self-care-and-social-function-using-computer-adaptive-testing-version-pediatric01224nas a2200133 4500008003900000245008800039210006900127260000900196300001400205520072100219100002000940700002000960856011000980 2008 d00aAn Automated Decision System for Computer Adaptive Testing Using Genetic Algorithms0 aAutomated Decision System for Computer Adaptive Testing Using Ge bIEEE a655–6603 aThis paper proposes an approach to solve the triangle decision tree problem for computer adaptive testing (CAT) using genetic algorithms (GAs). In this approach, item response theory (IRT) parameters composed of discrimination, difficulty, and guess are firstly obtained and stored in an item bank. Then a fitness function, which is based on IRT parameters, of GAs for obtaining an optimal solution is set up. Finally, the GAs is applied to the parameters of the item bank so that an optimal decision tree is generated. Based on a six-level triangle-decision tree for examination items, the experimental results show that the optimal decision tree can be generated correctly when compared with the standard patterns.1 aPhankokkruad, M1 aWoraratpanya, K uhttp://www.iacat.org/content/automated-decision-system-computer-adaptive-testing-using-genetic-algorithms02711nas a2200217 4500008004100000020004100041245010800082210006900190250001500259300001100274490000600285520189600291653003802187653002902225653005702254653001102311653001302322653002402335100001302359856012102372 2008 eng d a1529-7713 (Print)1529-7713 (Linking)00aBinary items and beyond: a simulation of computer adaptive testing using the Rasch partial credit model0 aBinary items and beyond a simulation of computer adaptive testin a2008/01/09 a81-1040 v93 aPast research on Computer Adaptive Testing (CAT) has focused almost exclusively on the use of binary items and minimizing the number of items to be administrated. To address this situation, extensive computer simulations were performed using partial credit items with two, three, four, and five response categories. Other variables manipulated include the number of available items, the number of respondents used to calibrate the items, and various manipulations of respondents' true locations. Three item selection strategies were used, and the theoretically optimal Maximum Information method was compared to random item selection and Bayesian Maximum Falsification approaches. The Rasch partial credit model proved to be quite robust to various imperfections, and systematic distortions did occur mainly in the absence of sufficient numbers of items located near the trait or performance levels of interest. The findings further indicate that having small numbers of items is more problematic in practice than having small numbers of respondents to calibrate these items. Most importantly, increasing the number of response categories consistently improved CAT's efficiency as well as the general quality of the results. In fact, increasing the number of response categories proved to have a greater positive impact than did the choice of item selection method, as the Maximum Information approach performed only slightly better than the Maximum Falsification approach. Accordingly, issues related to the efficiency of item selection methods are far less important than is commonly suggested in the literature. However, being based on computer simulations only, the preceding presumes that actual respondents behave according to the Rasch model. CAT research could thus benefit from empirical studies aimed at determining whether, and if so, how, selection strategies impact performance.10a*Data Interpretation, Statistical10a*User-Computer Interface10aEducational Measurement/*statistics & numerical data10aHumans10aIllinois10aModels, Statistical1 aLange, R uhttp://www.iacat.org/content/binary-items-and-beyond-simulation-computer-adaptive-testing-using-rasch-partial-credit00450nas a2200133 4500008003900000245006000039210005800099300001000157490000600167100002100173700001800194700001900212856008500231 2008 d00aCAT-MD: Computerized adaptive testing on mobile devices0 aCATMD Computerized adaptive testing on mobile devices a13-200 v31 aTriantafillou, E1 aGeorgiadou, E1 aEconomides, AA uhttp://www.iacat.org/content/cat-md-computerized-adaptive-testing-mobile-devices02582nas a2200241 4500008004100000020002200041245009000063210006900153250001500222260000800237300001100245490000700256520178300263653001502046653001502061653002502076653002902101653005002130653001102180100001602191700001902207856011402226 2008 eng d a1554-351X (Print)00aCombining computer adaptive testing technology with cognitively diagnostic assessment0 aCombining computer adaptive testing technology with cognitively  a2008/08/14 cAug a808-210 v403 aA major advantage of computerized adaptive testing (CAT) is that it allows the test to home in on an examinee's ability level in an interactive manner. The aim of the new area of cognitive diagnosis is to provide information about specific content areas in which an examinee needs help. The goal of this study was to combine the benefit of specific feedback from cognitively diagnostic assessment with the advantages of CAT. In this study, three approaches to combining these were investigated: (1) item selection based on the traditional ability level estimate (theta), (2) item selection based on the attribute mastery feedback provided by cognitively diagnostic assessment (alpha), and (3) item selection based on both the traditional ability level estimate (theta) and the attribute mastery feedback provided by cognitively diagnostic assessment (alpha). The results from these three approaches were compared for theta estimation accuracy, attribute mastery estimation accuracy, and item exposure control. The theta- and alpha-based condition outperformed the alpha-based condition regarding theta estimation, attribute mastery pattern estimation, and item exposure control. Both the theta-based condition and the theta- and alpha-based condition performed similarly with regard to theta estimation, attribute mastery estimation, and item exposure control, but the theta- and alpha-based condition has an additional advantage in that it uses the shadow test method, which allows the administrator to incorporate additional constraints in the item selection process, such as content balancing, item type constraints, and so forth, and also to select items on the basis of both the current theta and alpha estimates, which can be built on top of existing 3PL testing programs.10a*Cognition10a*Computers10a*Models, Statistical10a*User-Computer Interface10aDiagnosis, Computer-Assisted/*instrumentation10aHumans1 aMcGlohen, M1 aChang, Hua-Hua uhttp://www.iacat.org/content/combining-computer-adaptive-testing-technology-cognitively-diagnostic-assessment01669nas a2200169 4500008003900000245009500039210007100134300000900205490000700214520113900221100001701360700001401377700002201391700001901413700001601432856005101448 2008 d00aComparability of Computer-Based and Paper-and-Pencil Testing in K–12 Reading Assessments0 aComparability of ComputerBased and PaperandPencil Testing in K–1 a5-240 v683 a

In recent years, computer-based testing (CBT) has grown in popularity, is increasingly being implemented across the United States, and will likely become the primary mode for delivering tests in the future. Although CBT offers many advantages over traditional paper-and-pencil testing, assessment experts, researchers, practitioners, and users have expressed concern about the comparability of scores between the two test administration modes. To help provide an answer to this issue, a meta-analysis was conducted to synthesize the administration mode effects of CBTs and paper-and-pencil tests on K—12 student reading assessments. Findings indicate that the administration mode had no statistically significant effect on K—12 student reading achievement scores. Four moderator variables—study design, sample size, computer delivery algorithm, and computer practice—made statistically significant contributions to predicting effect size. Three moderator variables—grade level, type of test, and computer delivery method—did not affect the differences in reading scores between test modes.

1 aShudong Wang1 aHong Jiao1 aYoung, Michael, J1 aBrooks, Thomas1 aOlson, John uhttp://epm.sagepub.com/content/68/1/5.abstract01435nas a2200169 4500008003900000245009000039210006900129300001000198490000800208520081300216653002901029653003601058653003001094100001501124700001201139856011401151 2008 d00aComputer Adaptive-Attribute Testing A New Approach to Cognitive Diagnostic Assessment0 aComputer AdaptiveAttribute Testing A New Approach to Cognitive D a29-390 v2163 a

The influence of interdisciplinary forces stemming from developments in cognitive science,mathematical statistics, educational
psychology, and computing science are beginning to appear in educational and psychological assessment. Computer adaptive-attribute testing (CA-AT) is one example. The concepts and procedures in CA-AT can be found at the intersection between computer adaptive testing and cognitive diagnostic assessment. CA-AT allows us to fuse the administrative benefits of computer adaptive testing with the psychological benefits of cognitive diagnostic assessment to produce an innovative psychologically-based adaptive testing approach. We describe the concepts behind CA-AT as well as illustrate how it can be used to promote formative, computer-based, classroom assessment.

10acognition and assessment10acognitive diagnostic assessment10acomputer adaptive testing1 aGierl, M J1 aZhou, J uhttp://www.iacat.org/content/computer-adaptive-attribute-testing-new-approach-cognitive-diagnostic-assessment01113nas a2200133 4500008003900000245011000039210006900149300001200218490000700230520065500237100001700892700001700909856005300926 2008 d00aComputer-Based and Paper-and-Pencil Administration Mode Effects on a Statewide End-of-Course English Test0 aComputerBased and PaperandPencil Administration Mode Effects on  a554-5700 v683 a

The current study compared student performance between paper-and-pencil testing (PPT) and computer-based testing (CBT) on a large-scale statewide end-of-course English examination. Analyses were conducted at both the item and test levels. The overall results suggest that scores obtained from PPT and CBT were comparable. However, at the content domain level, a rather large difference in the reading comprehension section suggests that reading comprehension test may be more affected by the test administration mode. Results from the confirmatory factor analysis suggest that the administration mode did not alter the construct of the test.

1 aKim, Do-Hong1 aHuynh, Huynh uhttp://epm.sagepub.com/content/68/4/554.abstract03041nas a2200481 4500008004100000020004600041245012200087210006900209250001500278260000800293300001200301490000700313520155700320653003201877653003101909653002201940653002001962653001001982653000901992653002202001653002802023653003302051653001102084653001102095653002502106653000902131653001602140653004602156653002202202653002402224653003002248653002902278100001502307700001402322700001502336700002402351700001802375700001102393700001602404700001002420700001502430856011402445 2008 eng d a1532-821X (Electronic)0003-9993 (Linking)00aComputerized adaptive testing for follow-up after discharge from inpatient rehabilitation: II. Participation outcomes0 aComputerized adaptive testing for followup after discharge from  a2008/01/30 cFeb a275-2830 v893 aOBJECTIVES: To measure participation outcomes with a computerized adaptive test (CAT) and compare CAT and traditional fixed-length surveys in terms of score agreement, respondent burden, discriminant validity, and responsiveness. DESIGN: Longitudinal, prospective cohort study of patients interviewed approximately 2 weeks after discharge from inpatient rehabilitation and 3 months later. SETTING: Follow-up interviews conducted in patient's home setting. PARTICIPANTS: Adults (N=94) with diagnoses of neurologic, orthopedic, or medically complex conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Participation domains of mobility, domestic life, and community, social, & civic life, measured using a CAT version of the Participation Measure for Postacute Care (PM-PAC-CAT) and a 53-item fixed-length survey (PM-PAC-53). RESULTS: The PM-PAC-CAT showed substantial agreement with PM-PAC-53 scores (intraclass correlation coefficient, model 3,1, .71-.81). On average, the PM-PAC-CAT was completed in 42% of the time and with only 48% of the items as compared with the PM-PAC-53. Both formats discriminated across functional severity groups. The PM-PAC-CAT had modest reductions in sensitivity and responsiveness to patient-reported change over a 3-month interval as compared with the PM-PAC-53. CONCLUSIONS: Although continued evaluation is warranted, accurate estimates of participation status and responsiveness to change for group-level analyses can be obtained from CAT administrations, with a sizeable reduction in respondent burden.10a*Activities of Daily Living10a*Adaptation, Physiological10a*Computer Systems10a*Questionnaires10aAdult10aAged10aAged, 80 and over10aChi-Square Distribution10aFactor Analysis, Statistical10aFemale10aHumans10aLongitudinal Studies10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPatient Discharge10aProspective Studies10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aGandek, B1 aSiebens, H1 aBlack-Schaffer, R M1 aSinclair, S J1 aTao, W1 aCoster, W J1 aNi, P1 aJette, A M uhttp://www.iacat.org/content/computerized-adaptive-testing-follow-after-discharge-inpatient-rehabilitation-ii00581nas a2200145 4500008004100000245012000041210006900161300001400230490000700244100001400251700001400265700001900279700001800298856011900316 2008 eng d00aComputerized adaptive testing for patients with knee inpairments produced valid and responsive measures of function0 aComputerized adaptive testing for patients with knee inpairments a1113-11240 v611 aHart, D L1 aWang, Y-C1 aStratford, P W1 aMioduski, J E uhttp://www.iacat.org/content/computerized-adaptive-testing-patients-knee-inpairments-produced-valid-and-responsive03313nas a2200433 4500008004100000020004600041245007700087210006900164250001500233260001100248300001200259490000700271520203200278653002702310653003002337653002102367653001002388653000902398653001502407653003602422653002102458653004402479653002402523653001102547653001102558653001302569653000902582653001602591653003002607653003002637653003102667100001502698700001302713700001502726700001402741700001502755700001402770856009502784 2008 eng d a1528-1159 (Electronic)0362-2436 (Linking)00aComputerized adaptive testing in back pain: Validation of the CAT-5D-QOL0 aComputerized adaptive testing in back pain Validation of the CAT a2008/05/23 cMay 20 a1384-900 v333 aSTUDY DESIGN: We have conducted an outcome instrument validation study. OBJECTIVE: Our objective was to develop a computerized adaptive test (CAT) to measure 5 domains of health-related quality of life (HRQL) and assess its feasibility, reliability, validity, and efficiency. SUMMARY OF BACKGROUND DATA: Kopec and colleagues have recently developed item response theory based item banks for 5 domains of HRQL relevant to back pain and suitable for CAT applications. The domains are Daily Activities (DAILY), Walking (WALK), Handling Objects (HAND), Pain or Discomfort (PAIN), and Feelings (FEEL). METHODS: An adaptive algorithm was implemented in a web-based questionnaire administration system. The questionnaire included CAT-5D-QOL (5 scales), Modified Oswestry Disability Index (MODI), Roland-Morris Disability Questionnaire (RMDQ), SF-36 Health Survey, and standard clinical and demographic information. Participants were outpatients treated for mechanical back pain at a referral center in Vancouver, Canada. RESULTS: A total of 215 patients completed the questionnaire and 84 completed a retest. On average, patients answered 5.2 items per CAT-5D-QOL scale. Reliability ranged from 0.83 (FEEL) to 0.92 (PAIN) and was 0.92 for the MODI, RMDQ, and Physical Component Summary (PCS-36). The ceiling effect was 0.5% for PAIN compared with 2% for MODI and 5% for RMQ. The CAT-5D-QOL scales correlated as anticipated with other measures of HRQL and discriminated well according to the level of satisfaction with current symptoms, duration of the last episode, sciatica, and disability compensation. The average relative discrimination index was 0.87 for PAIN, 0.67 for DAILY and 0.62 for WALK, compared with 0.89 for MODI, 0.80 for RMDQ, and 0.59 for PCS-36. CONCLUSION: The CAT-5D-QOL is feasible, reliable, valid, and efficient in patients with back pain. This methodology can be recommended for use in back pain research and should improve outcome assessment, facilitate comparisons across studies, and reduce patient burden.10a*Disability Evaluation10a*Health Status Indicators10a*Quality of Life10aAdult10aAged10aAlgorithms10aBack Pain/*diagnosis/psychology10aBritish Columbia10aDiagnosis, Computer-Assisted/*standards10aFeasibility Studies10aFemale10aHumans10aInternet10aMale10aMiddle Aged10aPredictive Value of Tests10aQuestionnaires/*standards10aReproducibility of Results1 aKopec, J A1 aBadii, M1 aMcKenna, M1 aLima, V D1 aSayre, E C1 aDvorak, M uhttp://www.iacat.org/content/computerized-adaptive-testing-back-pain-validation-cat-5d-qol01876nas a2200205 4500008003900000245005600039210005600095300001000151490000800161520124900169653002101418653003001439653002501469653001801494653002501512100001301537700001701550700002101567856008201588 2008 d00aComputerized Adaptive Testing of Personality Traits0 aComputerized Adaptive Testing of Personality Traits a12-210 v2163 a

A computerized adaptive testing (CAT) procedure was simulated with ordinal polytomous personality data collected using a
conventional paper-and-pencil testing format. An adapted Dutch version of the dominance scale of Gough and Heilbrun’s Adjective
Check List (ACL) was used. This version contained Likert response scales with five categories. Item parameters were estimated using Samejima’s graded response model from the responses of 1,925 subjects. The CAT procedure was simulated using the responses of 1,517 other subjects. The value of the required standard error in the stopping rule of the CAT was manipulated. The relationship between CAT latent trait estimates and estimates based on all dominance items was studied. Additionally, the pattern of relationships between the CAT latent trait estimates and the other ACL scales was compared to that between latent trait estimates based on the entire item pool and the other ACL scales. The CAT procedure resulted in latent trait estimates qualitatively equivalent to latent trait estimates based on all items, while a substantial reduction of the number of used items could be realized (at the stopping rule of 0.4 about 33% of the 36 items was used).

10aAdaptive Testing10acmoputer-assisted testing10aItem Response Theory10aLikert scales10aPersonality Measures1 aHol, A M1 aVorst, H C M1 aMellenbergh, G J uhttp://www.iacat.org/content/computerized-adaptive-testing-personality-traits01922nas a2200217 4500008004100000020004100041245009100082210006900173250001500242260000800257300001100265490000700276520119200283653004001475653002701515653001101542100001401553700001301567700001401580856011001594 2008 eng d a0007-1102 (Print)0007-1102 (Linking)00aControlling item exposure and test overlap on the fly in computerized adaptive testing0 aControlling item exposure and test overlap on the fly in compute a2007/07/26 cNov a471-920 v613 aThis paper proposes an on-line version of the Sympson and Hetter procedure with test overlap control (SHT) that can provide item exposure control at both the item and test levels on the fly without iterative simulations. The on-line procedure is similar to the SHT procedure in that exposure parameters are used for simultaneous control of item exposure rates and test overlap rate. The exposure parameters for the on-line procedure, however, are updated sequentially on the fly, rather than through iterative simulations conducted prior to operational computerized adaptive tests (CATs). Unlike the SHT procedure, the on-line version can control item exposure rate and test overlap rate without time-consuming iterative simulations even when item pools or examinee populations have been changed. Moreover, the on-line procedure was found to perform better than the SHT procedure in controlling item exposure and test overlap for examinees who take tests earlier. Compared with two other on-line alternatives, this proposed on-line method provided the best all-around test security control. Thus, it would be an efficient procedure for controlling item exposure and test overlap in CATs.10a*Decision Making, Computer-Assisted10a*Models, Psychological10aHumans1 aChen, S-Y1 aLei, P W1 aLiao, W H uhttp://www.iacat.org/content/controlling-item-exposure-and-test-overlap-fly-computerized-adaptive-testing00682nas a2200157 4500008004100000245017700041210006900218260003100287100001600318700001200334700001300346700001500359700001400374700001300388856012300401 2008 eng d00aDeveloping a progressive approach to using the GAIN in order to reduce the duration and cost of assessment with the GAIN short screener, Quick and computer adaptive testing0 aDeveloping a progressive approach to using the GAIN in order to  aWashington D.C., USAc20081 aDennis, M L1 aFunk, R1 aTitus, J1 aRiley, B B1 aHosman, S1 aKinne, S uhttp://www.iacat.org/content/developing-progressive-approach-using-gain-order-reduce-duration-and-cost-assessment-gain01728nas a2200181 4500008004100000245011200041210006900153300001100222490000700233520107200240653003401312653001701346653001901363100001601382700001801398700001501416856011501431 2008 eng d00aThe D-optimality item selection criterion in the early stage of CAT: A study with the graded response model0 aDoptimality item selection criterion in the early stage of CAT A a88-1100 v333 aDuring the early stage of computerized adaptive testing (CAT), item selection criteria based on Fisher’s information often produce less stable latent trait estimates than the Kullback-Leibler global information criterion. Robustness against early stage instability has been reported for the D-optimality criterion in a polytomous CAT with the Nominal Response Model and is shown herein to be reproducible for the Graded Response Model. For comparative purposes, the A-optimality and the global information criteria are also applied. Their item selection is investigated as a function of test progression and item bank composition. The results indicate how the selection of specific item parameters underlies the criteria performances evaluated via accuracy and precision of estimation. In addition, the criteria item exposure rates are compared, without the use of any exposure controlling measure. On the account of stability, precision, accuracy, numerical simplicity, and less evidently, item exposure rate, the D-optimality criterion can be recommended for CAT.10acomputerized adaptive testing10aD optimality10aitem selection1 aPassos, V L1 aBerger, M P F1 aTan, F E S uhttp://www.iacat.org/content/d-optimality-item-selection-criterion-early-stage-cat-study-graded-response-model00483nam a2200097 4500008004100000245008500041210006900126260007700195100001500272856009800287 2008 eng d00aEffect of early misfit in computerized adaptive testing on the recovery of theta0 aEffect of early misfit in computerized adaptive testing on the r aUnpublished Ph.D. dissertation, University of Minnesota, Minneapolis MN.1 aGuyer, R D uhttp://www.iacat.org/content/effect-early-misfit-computerized-adaptive-testing-recovery-theta02560nas a2200313 4500008004100000020004100041245011500082210006900197250001500266300001100281490000700292520149300299653002701792653001001819653001401829653005301843653001501896653001101911653003701922653001801959653003101977653002602008653001402034653003202048100001502080700001002095700001502105856012602120 2008 eng d a0963-8288 (Print)0963-8288 (Linking)00aEfficiency and sensitivity of multidimensional computerized adaptive testing of pediatric physical functioning0 aEfficiency and sensitivity of multidimensional computerized adap a2008/02/26 a479-840 v303 aPURPOSE: Computerized adaptive tests (CATs) have efficiency advantages over fixed-length tests of physical functioning but may lose sensitivity when administering extremely low numbers of items. Multidimensional CATs may efficiently improve sensitivity by capitalizing on correlations between functional domains. Using a series of empirical simulations, we assessed the efficiency and sensitivity of multidimensional CATs compared to a longer fixed-length test. METHOD: Parent responses to the Pediatric Evaluation of Disability Inventory before and after intervention for 239 children at a pediatric rehabilitation hospital provided the data for this retrospective study. Reliability, effect size, and standardized response mean were compared between full-length self-care and mobility subscales and simulated multidimensional CATs with stopping rules at 40, 30, 20, and 10 items. RESULTS: Reliability was lowest in the 10-item CAT condition for the self-care (r = 0.85) and mobility (r = 0.79) subscales; all other conditions had high reliabilities (r > 0.94). All multidimensional CAT conditions had equivalent levels of sensitivity compared to the full set condition for both domains. CONCLUSIONS: Multidimensional CATs efficiently retain the sensitivity of longer fixed-length measures even with 5 items per dimension (10-item CAT condition). Measuring physical functioning with multidimensional CATs could enhance sensitivity following intervention while minimizing response burden.10a*Disability Evaluation10aChild10aComputers10aDisabled Children/*classification/rehabilitation10aEfficiency10aHumans10aOutcome Assessment (Health Care)10aPsychometrics10aReproducibility of Results10aRetrospective Studies10aSelf Care10aSensitivity and Specificity1 aAllen, D D1 aNi, P1 aHaley, S M uhttp://www.iacat.org/content/efficiency-and-sensitivity-multidimensional-computerized-adaptive-testing-pediatric-physical02390nas a2200205 4500008004100000020001400041245008800055210006900143300001400212490000700226520173800233100001401971700001401985700002001999700001702019700001202036700001602048700001502064856010502079 2008 eng d a1520-639400aFunctioning and validity of a computerized adaptive test to measure anxiety (A CAT)0 aFunctioning and validity of a computerized adaptive test to meas aE182-E1940 v253 aBackground: The aim of this study was to evaluate the Computerized Adaptive Test to measure anxiety (A-CAT), a patient-reported outcome questionnaire that uses computerized adaptive testing to measure anxiety. Methods: The A-CAT builds on an item bank of 50 items that has been built using conventional item analyses and item response theory analyses. The A-CAT was administered on Personal Digital Assistants to n=357 patients diagnosed and treated at the department of Psychosomatic Medicine and Psychotherapy, Charité Berlin, Germany. For validation purposes, two subgroups of patients (n=110 and 125) answered the A-CAT along with established anxiety and depression questionnaires. Results: The A-CAT was fast to complete (on average in 2 min, 38 s) and a precise item response theory based CAT score (reliability>.9) could be estimated after 4–41 items. On average, the CAT displayed 6 items (SD=4.2). Convergent validity of the A-CAT was supported by correlations to existing tools (Hospital Anxiety and Depression Scale-A, Beck Anxiety Inventory, Berliner Stimmungs-Fragebogen A/D, and State Trait Anxiety Inventory: r=.56–.66); discriminant validity between diagnostic groups was higher for the A-CAT than for other anxiety measures. Conclusions: The German A-CAT is an efficient, reliable, and valid tool for assessing anxiety in patients suffering from anxiety disorders and other conditions with significant potential for initial assessment and long-term treatment monitoring. Future research directions are to explore content balancing of the item selection algorithm of the CAT, to norm the tool to a healthy sample, and to develop practical cutoff scores. Depression and Anxiety, 2008. © 2008 Wiley-Liss, Inc.1 aBecker, J1 aFliege, H1 aKocalevent, R D1 aBjorner, J B1 aRose, M1 aWalter, O B1 aKlapp, B F uhttp://www.iacat.org/content/functioning-and-validity-computerized-adaptive-test-measure-anxiety-cat02194nas a2200145 4500008004100000245009900041210006900140300001000209490000800219520163900227653003401866100001901900700001601919856011301935 2008 eng d00aICAT: An adaptive testing procedure for the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure for the identification of idi a40-480 v2163 a

Traditional adaptive tests provide an efficient method for estimating student achievements levels, by adjusting the characteristicsof the test questions to match the performance of each student. These traditional adaptive tests are not designed to identify diosyncraticknowledge patterns. As students move through their education, they learn content in any number of different ways related to their learning style and cognitive development. This may result in a student having different achievement levels from one content area to another within a domain of content. This study investigates whether such idiosyncratic knowledge patterns exist. It discusses the differences between idiosyncratic knowledge patterns and multidimensionality. Finally, it proposes an adaptive testing procedure that can be used to identify a student’s areas of strength and weakness more efficiently than current adaptive testing approaches. The findings of the study indicate that a fairly large number of students may have test results that are influenced by their idiosyncratic knowledge patterns. The findings suggest that these patterns persist across time for a large number of students, and that the differences in student performance between content areas within a subject domain are large enough to allow them to be useful in instruction. Given the existence of idiosyncratic patterns of knowledge, the proposed testing procedure may enable us to provide more useful information to teachers. It should also allow us to differentiate between idiosyncratic patterns or knowledge, and important mutidimensionality in the testing data.

10acomputerized adaptive testing1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/icat-adaptive-testing-procedure-identification-idiosyncratic-knowledge-patterns00504nas a2200121 4500008004100000245009900041210006900140300001200209490001100221100001900232700001600251856011500267 2008 eng d00aICAT: An adaptive testing procedure for the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure for the identification of idi a40–480 v216(1)1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/icat-adaptive-testing-procedure-identification-idiosyncratic-knowledge-patterns-001188nas a2200157 4500008004500000245009300045210006900138300001200207490000600219520062800225100001600853700001900869700001400888700001500902856011300917 2008 Engldsh 00aImpact of altering randomization intervals on precision of measurement and item exposure0 aImpact of altering randomization intervals on precision of measu a160-1670 v93 a

This paper reports on the use of simulation when a randomization procedure is used to control item exposure in a computerized adaptive test for certification. We present a method to determine the optimum width of the interval from which items are selected and we report on the impact of relaxing the interval width on measurement precision and item exposure. Results indicate that, if the item bank is well targeted, it may be possible to widen the randomization interval and thus reduce item exposure, without seriously impacting the error of measure for test takers whose ability estimate is near the pass point.

1 aMuckle, T J1 aBergstrom, B A1 aBecker, K1 aStahl, J A uhttp://www.iacat.org/content/impact-altering-randomization-intervals-precision-measurement-and-item-exposure00469nas a2200121 4500008003900000245011200039210006900151300001200220490000600232100002500238700001900263856006500282 2008 d00aImplementing Sympson-Hetter Item-Exposure Control in a Shadow-Test Approach to Constrained Adaptive Testing0 aImplementing SympsonHetter ItemExposure Control in a ShadowTest  a272-2890 v81 aVeldkamp, Bernard, P1 aLinden, Wim, J uhttp://www.tandfonline.com/doi/abs/10.1080/1530505080226223300546nas a2200145 4500008004100000245009900041210006900140300001200209490000700221100001700228700001200245700001500257700001400272856011400286 2008 eng d00aIncorporating randomness in the Fisher information for improving item-exposure control in CATs0 aIncorporating randomness in the Fisher information for improving a493-5130 v611 aBarrada, J R1 aOlea, J1 aPonsoda, V1 aAbad, F J uhttp://www.iacat.org/content/incorporating-randomness-fisher-information-improving-item-exposure-control-cats03056nas a2200205 4500008004100000020002700041245012200068210006900190250001500259260001100274300000800285490000600293520234600299100001502645700001402660700001402674700002102688700001502709856012602724 2008 Eng d a1471-2474 (Electronic)00aAn initial application of computerized adaptive testing (CAT) for measuring disability in patients with low back pain0 ainitial application of computerized adaptive testing CAT for mea a2008/12/20 cDec 18 a1660 v93 aABSTRACT: BACKGROUND: Recent approaches to outcome measurement involving Computerized Adaptive Testing (CAT) offer an approach for measuring disability in low back pain (LBP) in a way that can reduce the burden upon patient and professional. The aim of this study was to explore the potential of CAT in LBP for measuring disability as defined in the International Classification of Functioning, Disability and Health (ICF) which includes impairments, activity limitation, and participation restriction. METHODS: 266 patients with low back pain answered questions from a range of widely used questionnaires. An exploratory factor analysis (EFA) was used to identify disability dimensions which were then subjected to Rasch analysis. Reliability was tested by internal consistency and person separation index (PSI). Discriminant validity of disability levels were evaluated by Spearman correlation coefficient (r), intraclass correlation coefficient [ICC(2,1)] and the Bland-Altman approach. A CAT was developed for each dimension, and the results checked against simulated and real applications from a further 133 patients. RESULTS: Factor analytic techniques identified two dimensions named "body functions" and "activity-participation". After deletion of some items for failure to fit the Rasch model, the remaining items were mostly free of Differential Item Functioning (DIF) for age and gender. Reliability exceeded 0.90 for both dimensions. The disability levels generated using all items and those obtained from the real CAT application were highly correlated (i.e. >0.97 for both dimensions). On average, 19 and 14 items were needed to estimate the precise disability levels using the initial CAT for the first and second dimension. However, a marginal increase in the standard error of the estimate across successive iterations substantially reduced the number of items required to make an estimate. CONCLUSIONS: Using a combination approach of EFA and Rasch analysis this study has shown that it is possible to calibrate items onto a single metric in a way that can be used to provide the basis of a CAT application. Thus there is an opportunity to obtain a wide variety of information to evaluate the biopsychosocial model in its more complex forms, without necessarily increasing the burden of information collection for patients.1 aElhan, A H1 aOztuna, D1 aKutlay, S1 aKucukdeveci, A A1 aTennant, A uhttp://www.iacat.org/content/initial-application-computerized-adaptive-testing-cat-measuring-disability-patients-low-back00462nas a2200121 4500008004100000245008400041210006900125300000900194490000700203100001300210700001400223856010300237 2008 eng d00aInvestigating item exposure control on the fly in computerized adaptive testing0 aInvestigating item exposure control on the fly in computerized a a1-320 v551 aWu, M -L1 aChen, S-Y uhttp://www.iacat.org/content/investigating-item-exposure-control-fly-computerized-adaptive-testing00441nas a2200121 4500008004100000245007200041210006900113300001200182490000700194100000800201700001400209856009600223 2008 eng d00aItem exposure control in a-stratified computerized adaptive testing0 aItem exposure control in astratified computerized adaptive testi a793-8110 v551 aJhu1 aChen, S-Y uhttp://www.iacat.org/content/item-exposure-control-stratified-computerized-adaptive-testing03232nas a2200397 4500008004100000020002700041245014200068210006900210250001500279260001100294300001200305490000700317520193600324653002702260653003002287653001002317653000902327653002202336653003602358653001602394653002402410653004402434653001102478653001602489653002602505653003002531653003002561653003102591100001302622700001402635700001502649700001402664700001702678700001502695856012402710 2008 eng d a1528-1159 (Electronic)00aLetting the CAT out of the bag: Comparing computer adaptive tests and an 11-item short form of the Roland-Morris Disability Questionnaire0 aLetting the CAT out of the bag Comparing computer adaptive tests a2008/05/23 cMay 20 a1378-830 v333 aSTUDY DESIGN: A post hoc simulation of a computer adaptive administration of the items of a modified version of the Roland-Morris Disability Questionnaire. OBJECTIVE: To evaluate the effectiveness of adaptive administration of back pain-related disability items compared with a fixed 11-item short form. SUMMARY OF BACKGROUND DATA: Short form versions of the Roland-Morris Disability Questionnaire have been developed. An alternative to paper-and-pencil short forms is to administer items adaptively so that items are presented based on a person's responses to previous items. Theoretically, this allows precise estimation of back pain disability with administration of only a few items. MATERIALS AND METHODS: Data were gathered from 2 previously conducted studies of persons with back pain. An item response theory model was used to calibrate scores based on all items, items of a paper-and-pencil short form, and several computer adaptive tests (CATs). RESULTS: Correlations between each CAT condition and scores based on a 23-item version of the Roland-Morris Disability Questionnaire ranged from 0.93 to 0.98. Compared with an 11-item short form, an 11-item CAT produced scores that were significantly more highly correlated with scores based on the 23-item scale. CATs with even fewer items also produced scores that were highly correlated with scores based on all items. For example, scores from a 5-item CAT had a correlation of 0.93 with full scale scores. Seven- and 9-item CATs correlated at 0.95 and 0.97, respectively. A CAT with a standard-error-based stopping rule produced scores that correlated at 0.95 with full scale scores. CONCLUSION: A CAT-based back pain-related disability measure may be a valuable tool for use in clinical and research contexts. Use of CAT for other common measures in back pain research, such as other functional scales or measures of psychological distress, may offer similar advantages.10a*Disability Evaluation10a*Health Status Indicators10aAdult10aAged10aAged, 80 and over10aBack Pain/*diagnosis/psychology10aCalibration10aComputer Simulation10aDiagnosis, Computer-Assisted/*standards10aHumans10aMiddle Aged10aModels, Psychological10aPredictive Value of Tests10aQuestionnaires/*standards10aReproducibility of Results1 aCook, KF1 aChoi, S W1 aCrane, P K1 aDeyo, R A1 aJohnson, K L1 aAmtmann, D uhttp://www.iacat.org/content/letting-cat-out-bag-comparing-computer-adaptive-tests-and-11-item-short-form-roland-morris01442nas a2200145 4500008003900000022001400039245007100053210006900124300001400193490000700207520098500214100002001199700002201219856005501241 2008 d a1745-398400aLocal Dependence in an Operational CAT: Diagnosis and Implications0 aLocal Dependence in an Operational CAT Diagnosis and Implication a201–2230 v453 a

The accuracy of CAT scores can be negatively affected by local dependence if the CAT utilizes parameters that are misspecified due to the presence of local dependence and/or fails to control for local dependence in responses during the administration stage. This article evaluates the existence and effect of local dependence in a test of Mathematics Knowledge. Diagnostic tools were first used to evaluate the existence of local dependence in items that were calibrated under a 3PL model. A simulation study was then used to evaluate the effect of local dependence on the precision of examinee CAT scores when the 3PL model was used for selection and scoring. The diagnostic evaluation showed strong evidence for local dependence. The simulation suggested that local dependence in parameters had a minimal effect on CAT score precision, while local dependence in responses had a substantial effect on score precision, depending on the degree of local dependence present.

1 aPommerich, Mary1 aSegall, Daniel, O uhttp://dx.doi.org/10.1111/j.1745-3984.2008.00061.x03428nas a2200385 4500008004100000020004100041245010600082210006900188250001500257260001200272300001000284490000700294520220300301653002702504653001502531653001002546653002102556653002402577653002802601653003802629653001102667653001102678653001102689653003902700653000902739653002402748653003102772653004002803100001802843700001502861700001302876700001702889700001402906856012202920 2008 eng d a0271-6798 (Print)0271-6798 (Linking)00aMeasuring physical functioning in children with spinal impairments with computerized adaptive testing0 aMeasuring physical functioning in children with spinal impairmen a2008/03/26 cApr-May a330-50 v283 aBACKGROUND: The purpose of this study was to assess the utility of measuring current physical functioning status of children with scoliosis and kyphosis by applying computerized adaptive testing (CAT) methods. Computerized adaptive testing uses a computer interface to administer the most optimal items based on previous responses, reducing the number of items needed to obtain a scoring estimate. METHODS: This was a prospective study of 77 subjects (0.6-19.8 years) who were seen by a spine surgeon during a routine clinic visit for progress spine deformity. Using a multidimensional version of the Pediatric Evaluation of Disability Inventory CAT program (PEDI-MCAT), we evaluated content range, accuracy and efficiency, known-group validity, concurrent validity with the Pediatric Outcomes Data Collection Instrument, and test-retest reliability in a subsample (n = 16) within a 2-week interval. RESULTS: We found the PEDI-MCAT to have sufficient item coverage in both self-care and mobility content for this sample, although most patients tended to score at the higher ends of both scales. Both the accuracy of PEDI-MCAT scores as compared with a fixed format of the PEDI (r = 0.98 for both mobility and self-care) and test-retest reliability were very high [self-care: intraclass correlation (3,1) = 0.98, mobility: intraclass correlation (3,1) = 0.99]. The PEDI-MCAT took an average of 2.9 minutes for the parents to complete. The PEDI-MCAT detected expected differences between patient groups, and scores on the PEDI-MCAT correlated in expected directions with scores from the Pediatric Outcomes Data Collection Instrument domains. CONCLUSIONS: Use of the PEDI-MCAT to assess the physical functioning status, as perceived by parents of children with complex spinal impairments, seems to be feasible and achieves accurate and efficient estimates of self-care and mobility function. Additional item development will be needed at the higher functioning end of the scale to avoid ceiling effects for older children. LEVEL OF EVIDENCE: This is a level II prospective study designed to establish the utility of computer adaptive testing as an evaluation method in a busy pediatric spine practice.10a*Disability Evaluation10aAdolescent10aChild10aChild, Preschool10aComputer Simulation10aCross-Sectional Studies10aDisabled Children/*rehabilitation10aFemale10aHumans10aInfant10aKyphosis/*diagnosis/rehabilitation10aMale10aProspective Studies10aReproducibility of Results10aScoliosis/*diagnosis/rehabilitation1 aMulcahey, M J1 aHaley, S M1 aDuffy, T1 aPengsheng, N1 aBetz, R R uhttp://www.iacat.org/content/measuring-physical-functioning-children-spinal-impairments-computerized-adaptive-testing01081nas a2200145 4500008004100000245008400041210006900125300001200194490000700206520056600213100001600779700001700795700001300812856011000825 2008 eng d00aModern sequential analysis and its application to computerized adaptive testing0 aModern sequential analysis and its application to computerized a a473-4860 v733 aAfter a brief review of recent advances in sequential analysis involving sequential generalized likelihood ratio tests, we discuss their use in psychometric testing and extend the asymptotic optimality theory of these sequential tests to the case of sequentially generated experiments, of particular interest in computerized adaptive testing.We then show how these methods can be used to design adaptive mastery tests, which are asymptotically optimal and are also shown to provide substantial improvements over currently used sequential and fixed length tests.1 aBartroff, J1 aFinkelman, M1 aLai, T L uhttp://www.iacat.org/content/modern-sequential-analysis-and-its-application-computerized-adaptive-testing01234nas a2200145 4500008003900000245007300039210006900112300001200181490000700193520076500200100002100965700002500986700002401011856005301035 2008 d00aA Monte Carlo Approach for Adaptive Testing With Content Constraints0 aMonte Carlo Approach for Adaptive Testing With Content Constrain a431-4460 v323 a

This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the item pool, and (c) more robust ability estimates. Computer simulations with Law School Admission Test items demonstrated that the new algorithm (a) produces similar ability estimates as shadow CAT but with half the maximum item exposure rate and 100% pool utilization and (b) produces more robust estimates when a high- (or low-) ability examinee performs poorly (or well) at the beginning of the test.

1 aBelov, Dmitry, I1 aArmstrong, Ronald, D1 aWeissman, Alexander uhttp://apm.sagepub.com/content/32/6/431.abstract00475nas a2200133 4500008003900000245007300039210006900112300001200181490000700193100001500200700001900215700001600234856009100250 2008 d00aA monte carlo approach for adaptive testing with content constraints0 amonte carlo approach for adaptive testing with content constrain a431-4460 v321 aBelov, D I1 aArmstrong, R D1 aWeissman, A uhttp://www.iacat.org/content/monte-carlo-approach-adaptive-testing-content-constraints00472nas a2200109 4500008003900000245009600039210006900135300001400204490000700218100002600225856011100251 2008 d00aA Monte Carlo approach to the design, assembly, and evaluation of multistage adaptive tests0 aMonte Carlo approach to the design assembly and evaluation of mu a119–1370 v321 aBelov, Armstrong, R D uhttp://www.iacat.org/content/monte-carlo-approach-design-assembly-and-evaluation-multistage-adaptive-tests01426nas a2200133 4500008003900000245009600039210006900135300001200204490000700216520097000223100002101193700002501214856005301239 2008 d00aA Monte Carlo Approach to the Design, Assembly, and Evaluation of Multistage Adaptive Tests0 aMonte Carlo Approach to the Design Assembly and Evaluation of Mu a119-1370 v323 a

This article presents an application of Monte Carlo methods for developing and assembling multistage adaptive tests (MSTs). A major advantage of the Monte Carlo assembly over other approaches (e.g., integer programming or enumerative heuristics) is that it provides a uniform sampling from all MSTs (or MST paths) available from a given item pool. The uniform sampling allows a statistically valid analysis for MST design and evaluation. Given an item pool, MST model, and content constraints for test assembly, three problems are addressed in this study. They are (a) the construction of item response theory (IRT) targets for each MST path, (b) the assembly of an MST such that each path satisfies content constraints and IRT constraints, and (c) an analysis of the pool and constraints to increase the number of nonoverlapping MSTs that can be assembled from the pool. The primary intent is to produce reliable measurements and enhance pool utilization.

1 aBelov, Dmitry, I1 aArmstrong, Ronald, D uhttp://apm.sagepub.com/content/32/2/119.abstract02141nas a2200289 4500008004100000020004600041245007200087210006400159250001500223260001100238300000700249490000700256520118400263653002901447653003501476653002601511653002601537653001101563653006101574653001801635653004501653653001301698100001601711700001301727700001801740856009301758 2008 eng d a1553-6467 (Electronic)0002-9459 (Linking)00aThe NAPLEX: evolution, purpose, scope, and educational implications0 aNAPLEX evolution purpose scope and educational implications a2008/05/17 cApr 15 a330 v723 aSince 2004, passing the North American Pharmacist Licensure Examination (NAPLEX) has been a requirement for earning initial pharmacy licensure in all 50 United States. The creation and evolution from 1952-2005 of the particular pharmacy competency testing areas and quantities of questions are described for the former paper-and-pencil National Association of Boards of Pharmacy Licensure Examination (NABPLEX) and the current candidate-specific computer adaptive NAPLEX pharmacy licensure examinations. A 40% increase in the weighting of NAPLEX Blueprint Area 2 in May 2005, compared to that in the preceding 1997-2005 Blueprint, has implications for candidates' NAPLEX performance and associated curricular content and instruction. New pharmacy graduates' scores on the NAPLEX are neither intended nor validated to serve as a criterion for assessing or judging the quality or effectiveness of pharmacy curricula and instruction. The newest cycle of NAPLEX Blueprint revision, a continual process to ensure representation of nationwide contemporary practice, began in early 2008. It may take up to 2 years, including surveying several thousand national pharmacists, to complete.10a*Educational Measurement10aEducation, Pharmacy/*standards10aHistory, 20th Century10aHistory, 21st Century10aHumans10aLicensure, Pharmacy/history/*legislation & jurisprudence10aNorth America10aPharmacists/*legislation & jurisprudence10aSoftware1 aNewton, D W1 aBoyle, M1 aCatizone, C A uhttp://www.iacat.org/content/naplex-evolution-purpose-scope-and-educational-implications01947nas a2200277 4500008004100000020004100041245007300082210006900155250001500224260000800239300001000247490000700257520099700264653001601261653002901277653004801306653006201354653001101416653002401427653004601451653003101497653001301528100001401541700001501555856009901570 2008 eng d a0007-1102 (Print)0007-1102 (Linking)00aPredicting item exposure parameters in computerized adaptive testing0 aPredicting item exposure parameters in computerized adaptive tes a2008/05/17 cMay a75-910 v613 aThe purpose of this study is to find a formula that describes the relationship between item exposure parameters and item parameters in computerized adaptive tests by using genetic programming (GP) - a biologically inspired artificial intelligence technique. Based on the formula, item exposure parameters for new parallel item pools can be predicted without conducting additional iterative simulations. Results show that an interesting formula between item exposure parameters and item parameters in a pool can be found by using GP. The item exposure parameters predicted based on the found formula were close to those observed from the Sympson and Hetter (1985) procedure and performed well in controlling item exposure rates. Similar results were observed for the Stocking and Lewis (1998) multinomial model for item selection and the Sympson and Hetter procedure with content balancing. The proposed GP approach has provided a knowledge-based solution for finding item exposure parameters.10a*Algorithms10a*Artificial Intelligence10aAptitude Tests/*statistics & numerical data10aDiagnosis, Computer-Assisted/*statistics & numerical data10aHumans10aModels, Statistical10aPsychometrics/statistics & numerical data10aReproducibility of Results10aSoftware1 aChen, S-Y1 aDoong, S H uhttp://www.iacat.org/content/predicting-item-exposure-parameters-computerized-adaptive-testing00517nas a2200133 4500008004100000020002700041245009500068210006900163250001500232300000600247490000600253100001100259856011300270 2008 eng d a1975-5937 (Electronic)00aPreparing the implementation of computerized adaptive testing for high-stakes examinations0 aPreparing the implementation of computerized adaptive testing fo a2009/02/19 a10 v51 aHuh, S uhttp://www.iacat.org/content/preparing-implementation-computerized-adaptive-testing-high-stakes-examinations02174nas a2200301 4500008004100000020001400041245010200055210006900157250001500226300001200241490000700253520109000260653001501350653001501365653002101380653004801401653002401449653002801473653006201501653005701563653001101620653002701631653004601658100001701704700001201721700001401733856012501747 2008 eng d a1138-741600aRotating item banks versus restriction of maximum exposure rates in computerized adaptive testing0 aRotating item banks versus restriction of maximum exposure rates a2008/11/08 a618-6250 v113 a

If examinees were to know, beforehand, part of the content of a computerized adaptive test, their estimated trait levels would then have a marked positive bias. One of the strategies to avoid this consists of dividing a large item bank into several sub-banks and rotating the sub-bank employed (Ariel, Veldkamp & van der Linden, 2004). This strategy permits substantial improvements in exposure control at little cost to measurement accuracy, However, we do not know whether this option provides better results than using the master bank with greater restriction in the maximum exposure rates (Sympson & Hetter, 1985). In order to investigate this issue, we worked with several simulated banks of 2100 items, comparing them, for RMSE and overlap rate, with the same banks divided in two, three... up to seven sub-banks. By means of extensive manipulation of the maximum exposure rate in each bank, we found that the option of rotating banks slightly outperformed the option of restricting maximum exposure rate of the master bank by means of the Sympson-Hetter method.

10a*Character10a*Databases10a*Software Design10aAptitude Tests/*statistics & numerical data10aBias (Epidemiology)10aComputing Methodologies10aDiagnosis, Computer-Assisted/*statistics & numerical data10aEducational Measurement/*statistics & numerical data10aHumans10aMathematical Computing10aPsychometrics/statistics & numerical data1 aBarrada, J R1 aOlea, J1 aAbad, F J uhttp://www.iacat.org/content/rotating-item-banks-versus-restriction-maximum-exposure-rates-computerized-adaptive-testing01559nas a2200145 4500008003900000245009000039210006900129300001200198490000700210520109400217100001201311700001801323700001901341856005301360 2008 d00aSeverity of Organized Item Theft in Computerized Adaptive Testing: A Simulation Study0 aSeverity of Organized Item Theft in Computerized Adaptive Testin a543-5580 v323 a

Criteria had been proposed for assessing the severity of possible test security violations for computerized tests with high-stakes outcomes. However, these criteria resulted from theoretical derivations that assumed uniformly randomized item selection. This study investigated potential damage caused by organized item theft in computerized adaptive testing (CAT) for two realistic item selection methods, maximum item information and a-stratified with content blocking, using the randomized method as a baseline for comparison. Damage caused by organized item theft was evaluated by the number of compromised items each examinee could encounter and the impact of the compromised items on examinees' ability estimates. Severity of test security violation was assessed under self-organized and organized item theft simulation scenarios. Results indicated that though item theft could cause severe damage to CAT with either item selection method, the maximum item information method was more vulnerable to the organized item theft simulation than was the a-stratified method.

1 aQing Yi1 aJinming Zhang1 aChang, Hua-Hua uhttp://apm.sagepub.com/content/32/7/543.abstract01293nas a2200133 4500008004100000245005700041210005700098300000900155490000800164520084700172653003401019100002301053856008301076 2008 eng d00aSome new developments in adaptive testing technology0 aSome new developments in adaptive testing technology a3-110 v2163 a

In an ironic twist of history, modern psychological testing has returned to an adaptive format quite common when testing was not yet standardized. Important stimuli to the renewed interest in adaptive testing have been the development of item-response theory in psychometrics, which models the responses on test items using separate parameters for the items and test takers, and the use of computers in test administration, which enables us to estimate the parameter for a test taker and select the items in real time. This article reviews a selection from the latest developments in the technology of adaptive testing, such as constrained adaptive item selection, adaptive testing using rule-based item generation, multidimensional adaptive testing, adaptive use of test batteries, and the use of response times in adaptive testing.

10acomputerized adaptive testing1 avan der Linden, WJ uhttp://www.iacat.org/content/some-new-developments-adaptive-testing-technology01832nas a2200229 4500008004100000020004100041245010800082210006900190250001500259300000900274490000600283520101700289653001601306653001501322653005701337653001101394653003001405653001801435100001401453700001401467856012101481 2008 eng d a1529-7713 (Print)1529-7713 (Linking)00aStrategies for controlling item exposure in computerized adaptive testing with the partial credit model0 aStrategies for controlling item exposure in computerized adaptiv a2008/01/09 a1-170 v93 aExposure control research with polytomous item pools has determined that randomization procedures can be very effective for controlling test security in computerized adaptive testing (CAT). The current study investigated the performance of four procedures for controlling item exposure in a CAT under the partial credit model. In addition to a no exposure control baseline condition, the Kingsbury-Zara, modified-within-.10-logits, Sympson-Hetter, and conditional Sympson-Hetter procedures were implemented to control exposure rates. The Kingsbury-Zara and the modified-within-.10-logits procedures were implemented with 3 and 6 item candidate conditions. The results show that the Kingsbury-Zara and modified-within-.10-logits procedures with 6 item candidates performed as well as the conditional Sympson-Hetter in terms of exposure rates, overlap rates, and pool utilization. These two procedures are strongly recommended for use with partial credit CATs due to their simplicity and strength of their results.10a*Algorithms10a*Computers10a*Educational Measurement/statistics & numerical data10aHumans10aQuestionnaires/*standards10aUnited States1 aDavis, LL1 aDodd, B G uhttp://www.iacat.org/content/strategies-controlling-item-exposure-computerized-adaptive-testing-partial-credit-model01614nas a2200145 4500008003900000245009500039210006900134300001200203490000700215520113800222100001801360700001801378700001901396856005301415 2008 d00aA Strategy for Controlling Item Exposure in Multidimensional Computerized Adaptive Testing0 aStrategy for Controlling Item Exposure in Multidimensional Compu a215-2320 v683 a

Although computerized adaptive tests have enjoyed tremendous growth, solutions for important problems remain unavailable. One problem is the control of item exposure rate. Because adaptive algorithms are designed to select optimal items, they choose items with high discriminating power. Thus, these items are selected more often than others, leading to both overexposure and underutilization of some parts of the item pool. Overused items are often compromised, creating a security problem that could threaten the validity of a test. Building on a previously proposed stratification scheme to control the exposure rate for one-dimensional tests, the authors extend their method to multidimensional tests. A strategy is proposed based on stratification in accordance with a functional of the vector of the discrimination parameter, which can be implemented with minimal computational overhead. Both theoretical and empirical validation studies are provided. Empirical results indicate significant improvement over the commonly used method of controlling exposure rate that requires only a reasonable sacrifice in efficiency.

1 aLee, Yi-Hsuan1 aIp, Edward, H1 aFuh, Cheng-Der uhttp://epm.sagepub.com/content/68/2/215.abstract01427nas a2200133 4500008003900000245008900039210006900128300001200197490000700209520094400216100001601160700001201176856010501188 2008 d00aTo Weight Or Not To Weight? Balancing Influence Of Initial Items In Adaptive Testing0 aTo Weight Or Not To Weight Balancing Influence Of Initial Items  a441-4500 v733 a

It has been widely reported that in computerized adaptive testing some examinees may get much lower scores than they would normally if an alternative paper-and-pencil version were given. The main purpose of this investigation is to quantitatively reveal the cause for the underestimation phenomenon. The logistic models, including the 1PL, 2PL, and 3PL models, are used to demonstrate our assertions. Our analytical derivation shows that, under the maximum information item selection strategy, if an examinee failed a few items at the beginning of the test, easy but more discriminating items are likely to be administered. Such items are ineffective to move the estimate close to the true theta, unless the test is sufficiently long or a variable-length test is used. Our results also indicate that a certain weighting mechanism is necessary to make the algorithm rely less on the items administered at the beginning of the test.

1 aChang, H -H1 aYing, Z uhttp://www.iacat.org/content/weight-or-not-weight-balancing-influence-initial-items-adaptive-testing00469nas a2200121 4500008004100000245008100041210006900122300001200191490001100203100001600214700001500230856010200245 2008 eng d00aTransitioning from fixed-length questionnaires to computer-adaptive versions0 aTransitioning from fixedlength questionnaires to computeradaptiv a22–280 v216(1)1 aWalter, O B1 aHolling, H uhttp://www.iacat.org/content/transitioning-fixed-length-questionnaires-computer-adaptive-versions03157nas a2200493 4500008004100000020002200041245008900063210006900152250001500221260000800236300001000244490000700254520169600261653003401957653002001991653001502011653001002026653000902036653002602045653003202071653003102103653001102134653001102145653000902156653003202165653001602197653002902213653004402242653002902286653003102315653003102346653001702377100001702394700001402411700001602425700001302441700001702454700002202471700001702493700001402510700001402524700001702538856010802555 2008 eng d a1075-2730 (Print)00aUsing computerized adaptive testing to reduce the burden of mental health assessment0 aUsing computerized adaptive testing to reduce the burden of ment a2008/04/02 cApr a361-80 v593 aOBJECTIVE: This study investigated the combination of item response theory and computerized adaptive testing (CAT) for psychiatric measurement as a means of reducing the burden of research and clinical assessments. METHODS: Data were from 800 participants in outpatient treatment for a mood or anxiety disorder; they completed 616 items of the 626-item Mood and Anxiety Spectrum Scales (MASS) at two times. The first administration was used to design and evaluate a CAT version of the MASS by using post hoc simulation. The second confirmed the functioning of CAT in live testing. RESULTS: Tests of competing models based on item response theory supported the scale's bifactor structure, consisting of a primary dimension and four group factors (mood, panic-agoraphobia, obsessive-compulsive, and social phobia). Both simulated and live CAT showed a 95% average reduction (585 items) in items administered (24 and 30 items, respectively) compared with administration of the full MASS. The correlation between scores on the full MASS and the CAT version was .93. For the mood disorder subscale, differences in scores between two groups of depressed patients--one with bipolar disorder and one without--on the full scale and on the CAT showed effect sizes of .63 (p<.003) and 1.19 (p<.001) standard deviation units, respectively, indicating better discriminant validity for CAT. CONCLUSIONS: Instead of using small fixed-length tests, clinicians can create item banks with a large item pool, and a small set of the items most relevant for a given individual can be administered with no loss of information, yielding a dramatic reduction in administration time and patient and clinician burden.10a*Diagnosis, Computer-Assisted10a*Questionnaires10aAdolescent10aAdult10aAged10aAgoraphobia/diagnosis10aAnxiety Disorders/diagnosis10aBipolar Disorder/diagnosis10aFemale10aHumans10aMale10aMental Disorders/*diagnosis10aMiddle Aged10aMood Disorders/diagnosis10aObsessive-Compulsive Disorder/diagnosis10aPanic Disorder/diagnosis10aPhobic Disorders/diagnosis10aReproducibility of Results10aTime Factors1 aGibbons, R D1 aWeiss, DJ1 aKupfer, D J1 aFrank, E1 aFagiolini, A1 aGrochocinski, V J1 aBhaumik, D K1 aStover, A1 aBock, R D1 aImmekus, J C uhttp://www.iacat.org/content/using-computerized-adaptive-testing-reduce-burden-mental-health-assessment02410nas a2200193 4500008004100000020002200041245011700063210006900180250001500249300001100264490000600275520172700281100001502008700001702023700001602040700001802056700001802074856012402092 2008 eng d a1740-7745 (Print)00aUsing item banks to construct measures of patient reported outcomes in clinical trials: investigator perceptions0 aUsing item banks to construct measures of patient reported outco a2008/11/26 a575-860 v53 aBACKGROUND: Item response theory (IRT) promises more sensitive and efficient measurement of patient-reported outcomes (PROs) than traditional approaches; however, the selection and use of PRO measures from IRT-based item banks differ from current methods of using PRO measures. PURPOSE: To anticipate barriers to the adoption of IRT item banks into clinical trials. METHODS: We conducted semistructured telephone or in-person interviews with 42 clinical researchers who published results from clinical trials in the Journal of the American Medical Association, the New England Journal of Medicine, or other leading clinical journals from July 2005 through May 2006. Interviews included a brief tutorial on IRT item banks. RESULTS: After the tutorial, 39 of 42 participants understood the novel products available from an IRT item bank, namely customized short forms and computerized adaptive testing. Most participants (38/42) thought that item banks could be useful in their clinical trials, but they mentioned several potential barriers to adoption, including economic and logistical constraints, concerns about whether item banks are better than current PRO measures, concerns about how to convince study personnel or statisticians to use item banks, concerns about FDA or sponsor acceptance, and the lack of availability of item banks validated in specific disease populations. LIMITATIONS: Selection bias might have led to more positive responses to the concept of item banks in clinical trials. CONCLUSIONS: Clinical investigators are open to a new method of PRO measurement offered in IRT item banks, but bank developers must address investigator and stakeholder concerns before widespread adoption can be expected.1 aFlynn, K E1 aDombeck, C B1 aDeWitt, E M1 aSchulman, K A1 aWeinfurt, K P uhttp://www.iacat.org/content/using-item-banks-construct-measures-patient-reported-outcomes-clinical-trials-investigator00406nas a2200109 4500008004100000245006400041210006400105300001100169490000700180100002300187856008600210 2008 eng d00aUsing response times for item selection in adaptive testing0 aUsing response times for item selection in adaptive testing a5–200 v331 avan der Linden, WJ uhttp://www.iacat.org/content/using-response-times-item-selection-adaptive-testing00442nas a2200109 4500008004100000245008600041210006900127300000800196490000700204100001900211856010200230 2008 eng d00aOn using stochastic curtailment to shorten the SPRT in sequential mastery testing0 ausing stochastic curtailment to shorten the SPRT in sequential m a4420 v331 aFinkelman, M D uhttp://www.iacat.org/content/using-stochastic-curtailment-shorten-sprt-sequential-mastery-testing01939nas a2200157 4500008004100000245011600041210006900157300001200226490000700238520135500245100001601600700001201616700001601628700001401644856012301658 2008 eng d00aUtilizing Rasch measurement models to develop a computer adaptive self-report of walking, climbing, and running0 aUtilizing Rasch measurement models to develop a computer adaptiv a458-4670 v303 aPurpose.The purpose of this paper is to show how the Rasch model can be used to develop a computer adaptive self-report of walking, climbing, and running.Method.Our instrument development work on the walking/climbing/running construct of the ICF Activity Measure was used to show how to develop a computer adaptive test (CAT). Fit of the items to the Rasch model and validation of the item difficulty hierarchy was accomplished using Winsteps software. Standard error was used as a stopping rule for the CAT. Finally, person abilities were connected to items difficulties using Rasch analysis ‘maps’.Results.All but the walking one mile item fit the Rasch measurement model. A CAT was developed which selectively presented items based on the last calibrated person ability measure and was designed to stop when standard error decreased to a pre-set criterion. Finally, person ability measures were connected to the ability to perform specific walking/climbing/running activities using Rasch maps.Conclusions.Rasch measurement models can be useful in developing CAT measures for rehabilitation and disability. In addition to CATs reducing respondent burden, the connection of person measures to item difficulties may be important for the clinical interpretation of measures.Read More: http://informahealthcare.com/doi/abs/10.1080/096382807016173171 aVelozo, C A1 aWang, Y1 aLehman, L A1 aWang, J H uhttp://www.iacat.org/content/utilizing-rasch-measurement-models-develop-computer-adaptive-self-report-walking-climbing00433nas a2200109 4500008004100000245007500041210007100116300001200187490000700199100001700206856010000223 2008 eng d00aThe Wald–Wolfowitz Theorem Is Violated in Sequential Mastery Testing0 aWald–Wolfowitz Theorem Is Violated in Sequential Mastery Testing a293-3030 v271 aFinkelman, M uhttp://www.iacat.org/content/wald%E2%80%93wolfowitz-theorem-violated-sequential-mastery-testing00544nas a2200121 4500008004100000245007500041210006900116260009700185100001500282700001500297700001300312856009700325 2007 eng d00aAdaptive estimators of trait level in adaptive testing: Some proposals0 aAdaptive estimators of trait level in adaptive testing Some prop aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aRaîche, G1 aBlais, J G1 aMagis, D uhttp://www.iacat.org/content/adaptive-estimators-trait-level-adaptive-testing-some-proposals00526nas a2200109 4500008004100000245007700041210006900118260009700187100001300284700002200297856009700319 2007 eng d00aAdaptive testing with the multi-unidimensional pairwise preference model0 aAdaptive testing with the multiunidimensional pairwise preferenc aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aStark, S1 aChernyshenko, O S uhttp://www.iacat.org/content/adaptive-testing-multi-unidimensional-pairwise-preference-model02337nas a2200145 4500008004100000020002200041245011100063210006900174250001500243300001200258490000700270520177800277100001602055856012002071 2007 eng d a0962-9343 (Print)00aApplying item response theory and computer adaptive testing: The challenges for health outcomes assessment0 aApplying item response theory and computer adaptive testing The  a2007/04/10 a187-1940 v163 aOBJECTIVES: We review the papers presented at the NCI/DIA conference, to identify areas of controversy and uncertainty, and to highlight those aspects of item response theory (IRT) and computer adaptive testing (CAT) that require theoretical or empirical research in order to justify their application to patient reported outcomes (PROs). BACKGROUND: IRT and CAT offer exciting potential for the development of a new generation of PRO instruments. However, most of the research into these techniques has been in non-healthcare settings, notably in education. Educational tests are very different from PRO instruments, and consequently problematic issues arise when adapting IRT and CAT to healthcare research. RESULTS: Clinical scales differ appreciably from educational tests, and symptoms have characteristics distinctly different from examination questions. This affects the transferring of IRT technology. Particular areas of concern when applying IRT to PROs include inadequate software, difficulties in selecting models and communicating results, insufficient testing of local independence and other assumptions, and a need of guidelines for estimating sample size requirements. Similar concerns apply to differential item functioning (DIF), which is an important application of IRT. Multidimensional IRT is likely to be advantageous only for closely related PRO dimensions. CONCLUSIONS: Although IRT and CAT provide appreciable potential benefits, there is a need for circumspection. Not all PRO scales are necessarily appropriate targets for this methodology. Traditional psychometric methods, and especially qualitative methods, continue to have an important role alongside IRT. Research should be funded to address the specific concerns that have been identified.1 aFayers, P M uhttp://www.iacat.org/content/applying-item-response-theory-and-computer-adaptive-testing-challenges-health-outcomes01430nas a2200133 4500008003900000245009900039210006900138300000900207490000700216520097800223100002301201700002101224856005101245 2007 d00aAutomated Simultaneous Assembly of Multistage Testlets for a High-Stakes Licensing Examination0 aAutomated Simultaneous Assembly of Multistage Testlets for a Hig a5-200 v673 a

Many challenges exist for high-stakes testing programs offering continuous computerized administration. The automated assembly of test questions to exactly meet content and other requirements, provide uniformity, and control item exposure can be modeled and solved by mixed-integer programming (MIP) methods. A case study of the computerized licensing examination of the American Institute of Certified Public Accountants is offered as one application of MIP techniques for test assembly. The solution illustrates assembly for a computer-adaptive multistage testing design. However, the general form of the constraint-based solution can be modified to generate optimal test designs for paper-based or computerized administrations, regardless of the specific psychometric model. An extension of this methodology allows for long-term planning for the production and use of test content on the basis of an exact psychometric test designs and administration schedules.

1 aBreithaupt, Krista1 aHare, Donovan, R uhttp://epm.sagepub.com/content/67/1/5.abstract00460nas a2200121 4500008003900000245009100039210007600130300001200206490000600218100002800224700002100252856006500273 2007 d00aA “Rearrangement Procedure” For Scoring Adaptive Tests with Review Options0 a“Rearrangement Procedure†For Scoring Adaptive Tests with Rev a387-4070 v71 aPapanastasiou, Elena, C1 aReckase, Mark, D uhttp://www.tandfonline.com/doi/abs/10.1080/1530505070163226200522nas a2200109 4500008004100000245007700041210006900118260009700187100001500284700001400299856009900313 2007 eng d00aBundle models for computerized adaptive testing in e-learning assessment0 aBundle models for computerized adaptive testing in elearning ass aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aScalise, K1 aWilson, M uhttp://www.iacat.org/content/bundle-models-computerized-adaptive-testing-e-learning-assessment00423nas a2200097 4500008004100000245004900041210004600090260009700136100001100233856008100244 2007 eng d00aCAT Security: A practitioner’s perspective0 aCAT Security A practitioner s perspective aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aGuo, F uhttp://www.iacat.org/content/cat-security-practitioner%E2%80%99s-perspective00460nas a2200097 4500008004100000245006400041210006400105260009700169100001600266856008000282 2007 eng d00aChoices in CAT models in the context of educational testing0 aChoices in CAT models in the context of educational testing aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aEggen, Theo uhttp://www.iacat.org/content/choices-cat-models-context-educational-testing00436nas a2200097 4500008004100000245006500041210006500106260007000171100001600241856008100257 2007 eng d00aChoices in CAT models in the context of educattional testing0 aChoices in CAT models in the context of educattional testing aSt. Paul, MNbGraduate Management Admission CouncilcJune 7, 20071 aEggen, Theo uhttp://www.iacat.org/content/choices-cat-models-context-educattional-testing00573nas a2200109 4500008004100000245010200041210006900143260009700212100001600309700001400325856012400339 2007 eng d00aComparison of computerized adaptive testing and classical methods for measuring individual change0 aComparison of computerized adaptive testing and classical method aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aKim-Kang, G1 aWeiss, DJ uhttp://www.iacat.org/content/comparison-computerized-adaptive-testing-and-classical-methods-measuring-individual-change00494nas a2200109 4500008004100000245011700041210006900158300001200227490000700239100001400246856012400260 2007 eng d00aThe comparison of maximum likelihood estimation and expected a posteriori in CAT using the graded response model0 acomparison of maximum likelihood estimation and expected a poste a339-3710 v191 aChen, S-K uhttp://www.iacat.org/content/comparison-maximum-likelihood-estimation-and-expected-posteriori-cat-using-graded-response00516nam a2200097 4500008004100000245010500041210006900146260006300215100001800278856012200296 2007 eng d00aA comparison of two methods of polytomous computerized classification testing for multiple cutscores0 acomparison of two methods of polytomous computerized classificat aUnpublished doctoral dissertation, University of Minnesota1 aThompson, N A uhttp://www.iacat.org/content/comparison-two-methods-polytomous-computerized-classification-testing-multiple-cutscores02308nas a2200301 4500008004100000020002200041245011900063210006900182250001500251260000800266300001000274490000700284520125000291653001501541653001001556653006201566653001101628653001101639653000901650653003801659653005601697653004601753653002101799653003101820100001601851700002001867856011901887 2007 eng d a1040-3590 (Print)00aComputerized adaptive personality testing: A review and illustration with the MMPI-2 Computerized Adaptive Version0 aComputerized adaptive personality testing A review and illustrat a2007/03/21 cMar a14-240 v193 aComputerized adaptive testing in personality assessment can improve efficiency by significantly reducing the number of items administered to answer an assessment question. Two approaches have been explored for adaptive testing in computerized personality assessment: item response theory and the countdown method. In this article, the authors review the literature on each and report the results of an investigation designed to explore the utility, in terms of item and time savings, and validity, in terms of correlations with external criterion measures, of an expanded countdown method-based research version of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2), the MMPI-2 Computerized Adaptive Version (MMPI-2-CA). Participants were 433 undergraduate college students (170 men and 263 women). Results indicated considerable item savings and corresponding time savings for the adaptive testing modalities compared with a conventional computerized MMPI-2 administration. Furthermore, computerized adaptive administration yielded comparable results to computerized conventional administration of the MMPI-2 in terms of both test scores and their validity. Future directions for computerized adaptive personality testing are discussed.10aAdolescent10aAdult10aDiagnosis, Computer-Assisted/*statistics & numerical data10aFemale10aHumans10aMale10aMMPI/*statistics & numerical data10aPersonality Assessment/*statistics & numerical data10aPsychometrics/statistics & numerical data10aReference Values10aReproducibility of Results1 aForbey, J D1 aBen-Porath, Y S uhttp://www.iacat.org/content/computerized-adaptive-personality-testing-review-and-illustration-mmpi-2-computerized01477nas a2200241 4500008004100000020002200041245007800063210006900141250001500210260001100225300001200236490000700248520069100255653002300946653002500969653002100994653006201015653001101077653001601088100001701104700001401121856010001135 2007 eng d a0277-6715 (Print)00aComputerized adaptive testing for measuring development of young children0 aComputerized adaptive testing for measuring development of young a2006/11/30 cJun 15 a2629-380 v263 aDevelopmental indicators that are used for routine measurement in The Netherlands are usually chosen to optimally identify delayed children. Measurements on the majority of children without problems are therefore quite imprecise. This study explores the use of computerized adaptive testing (CAT) to monitor the development of young children. CAT is expected to improve the measurement precision of the instrument. We do two simulation studies - one with real data and one with simulated data - to evaluate the usefulness of CAT. It is shown that CAT selects developmental indicators that maximally match the individual child, so that all children can be measured to the same precision.10a*Child Development10a*Models, Statistical10aChild, Preschool10aDiagnosis, Computer-Assisted/*statistics & numerical data10aHumans10aNetherlands1 aJacobusse, G1 aBuuren, S uhttp://www.iacat.org/content/computerized-adaptive-testing-measuring-development-young-children01415nas a2200145 4500008003900000245012900039210006900168300001200237490000700249520089000256100002001146700002301166700002701189856005301216 2007 d00aComputerized Adaptive Testing for Polytomous Motivation Items: Administration Mode Effects and a Comparison With Short Forms0 aComputerized Adaptive Testing for Polytomous Motivation Items Ad a412-4290 v313 a

In a randomized experiment (n = 515), a computerized and a computerized adaptive test (CAT) are compared. The item pool consists of 24 polytomous motivation items. Although items are carefully selected, calibration data show that Samejima's graded response model did not fit the data optimally. A simulation study is done to assess possible consequences of model misfit. CAT efficiency was studied by a systematic comparison of the CAT with two types of conventional fixed length short forms, which are created to be good CAT competitors. Results showed no essential administration mode effects. Efficiency analyses show that CAT outperformed the short forms in almost all aspects when results are aggregated along the latent trait scale. The real and the simulated data results are very similar, which indicate that the real data results are not affected by model misfit.

1 aHol, Michiel, A1 aVorst, Harrie, C M1 aMellenbergh, Gideon, J uhttp://apm.sagepub.com/content/31/5/412.abstract01948nas a2200301 4500008004500000020001400045245012900059210006900188300001200257490000700269520093500276653002501211653002101236653002501257653003001282653003001312653001001342653001501352653002601367653002501393653002401418653001501442653001501457100001301472700001701485700002101502856012301523 2007 Engldsh  a0146-621600aComputerized adaptive testing for polytomous motivation items: Administration mode effects and a comparison with short forms0 aComputerized adaptive testing for polytomous motivation items Ad a412-4290 v313 aIn a randomized experiment (n=515), a computerized and a computerized adaptive test (CAT) are compared. The item pool consists of 24 polytomous motivation items. Although items are carefully selected, calibration data show that Samejima's graded response model did not fit the data optimally. A simulation study is done to assess possible consequences of model misfit. CAT efficiency was studied by a systematic comparison of the CAT with two types of conventional fixed length short forms, which are created to be good CAT competitors. Results showed no essential administration mode effects. Efficiency analyses show that CAT outperformed the short forms in almost all aspects when results are aggregated along the latent trait scale. The real and the simulated data results are very similar, which indicate that the real data results are not affected by model misfit. (PsycINFO Database Record (c) 2007 APA ) (journal abstract)10a2220 Tests & Testing10aAdaptive Testing10aAttitude Measurement10acomputer adaptive testing10aComputer Assisted Testing10aitems10aMotivation10apolytomous motivation10aStatistical Validity10aTest Administration10aTest Forms10aTest Items1 aHol, A M1 aVorst, H C M1 aMellenbergh, G J uhttp://www.iacat.org/content/computerized-adaptive-testing-polytomous-motivation-items-administration-mode-effects-and00473nas a2200109 4500008004100000245005800041210005800099260009700157100001400254700001700268856007800285 2007 eng d00aComputerized adaptive testing with the bifactor model0 aComputerized adaptive testing with the bifactor model aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aWeiss, DJ1 aGibbons, R D uhttp://www.iacat.org/content/computerized-adaptive-testing-bifactor-model00608nas a2200121 4500008004100000245012500041210006900166260009700235100001200332700001500344700001100359856011600370 2007 eng d00aComputerized attribute-adaptive testing: A new computerized adaptive testing approach incorporating cognitive psychology0 aComputerized attributeadaptive testing A new computerized adapti aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aZhou, J1 aGierl, M J1 aCui, Y uhttp://www.iacat.org/content/computerized-attribute-adaptive-testing-new-computerized-adaptive-testing-approach00504nas a2200121 4500008004100000245006600041210006600107260005700173653003400230100001800264700001000282856009000292 2007 eng d00aComputerized classification testing with composite hypotheses0 aComputerized classification testing with composite hypotheses aSt. Paul, MNbGraduate Management Admissions Council10acomputerized adaptive testing1 aThompson, N A1 aRo, S uhttp://www.iacat.org/content/computerized-classification-testing-composite-hypotheses00500nas a2200109 4500008004100000245006600041210006600107260009700173100001800270700001000288856009200298 2007 eng d00aComputerized classification testing with composite hypotheses0 aComputerized classification testing with composite hypotheses aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aThompson, N A1 aRo, S uhttp://www.iacat.org/content/computerized-classification-testing-composite-hypotheses-001052nas a2200145 4500008003900000245005000039210005000089300001200139490000700151520063300158100002100791700002200812700001900834856005300853 2007 d00aComputerizing Organizational Attitude Surveys0 aComputerizing Organizational Attitude Surveys a658-6780 v673 a

Two quasi-experimental field studies were conducted to evaluate the psychometric equivalence of computerized and paper-and-pencil job satisfaction measures. The present research extends previous work in the area by providing better control of common threats to validity in quasi-experimental research on test mode effects and by evaluating a more comprehensive measurement model for job attitudes. Results of both studies demonstrated substantial equivalence of the computerized measure with the paper-and-pencil version. Implications for the practical use of computerized organizational attitude surveys are discussed.

1 aMueller, Karsten1 aLiebig, Christian1 aHattrup, Keith uhttp://epm.sagepub.com/content/67/4/658.abstract01361nas a2200133 4500008003900000245009700039210006900136300001200205490000700217520090200224100001901126700002501145856005701170 2007 d00aConditional Item-Exposure Control in Adaptive Testing Using Item-Ineligibility Probabilities0 aConditional ItemExposure Control in Adaptive Testing Using ItemI a398-4180 v323 a

Two conditional versions of the exposure-control method with item-ineligibility constraints for adaptive testing in van der Linden and Veldkamp (2004) are presented. The first version is for unconstrained item selection, the second for item selection with content constraints imposed by the shadow-test approach. In both versions, the exposure rates of the items are controlled using probabilities of item ineligibility given θ that adapt the exposure rates automatically to a goal value for the items in the pool. In an extensive empirical study with an adaptive version of the Law School Admission Test, the authors show how the method can be used to drive conditional exposure rates below goal values as low as 0.025. Obviously, the price to be paid for minimal exposure rates is a decrease in the accuracy of the ability estimates. This trend is illustrated with empirical data.

1 aLinden, Wim, J1 aVeldkamp, Bernard, P uhttp://jeb.sagepub.com/cgi/content/abstract/32/4/39800469nas a2200109 4500008004100000245008900041210006900130260001700199100001000216700001800226856011500244 2007 eng d00aCutscore location and classification accuracy in computerized classification testing0 aCutscore location and classification accuracy in computerized cl aTokyo, Japan1 aRo, S1 aThompson, N A uhttp://www.iacat.org/content/cutscore-location-and-classification-accuracy-computerized-classification-testing00473nas a2200121 4500008003900000245008000039210006900119490000800188100002100196700001800217700001900235856009700254 2007 d00aThe design and evaluation of a computerized adaptive test on mobile devices0 adesign and evaluation of a computerized adaptive test on mobile 0 v49.1 aTriantafillou, E1 aGeorgiadou, E1 aEconomides, AA uhttp://www.iacat.org/content/design-and-evaluation-computerized-adaptive-test-mobile-devices00499nas a2200097 4500008004100000245007100041210006600112260011700178100001700295856008900312 2007 eng d00aThe design of p-optimal item banks for computerized adaptive tests0 adesign of poptimal item banks for computerized adaptive tests aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing. {PDF file, 211 KB}.1 aReckase, M D uhttp://www.iacat.org/content/design-p-optimal-item-banks-computerized-adaptive-tests00567nas a2200109 4500008004100000245010200041210006900143260009600212100001000308700001700318856012200335 2007 eng d00aDesigning optimal item pools for computerized adaptive tests with Sympson-Hetter exposure control0 aDesigning optimal item pools for computerized adaptive tests wit aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing1 aGu, L1 aReckase, M D uhttp://www.iacat.org/content/designing-optimal-item-pools-computerized-adaptive-tests-sympson-hetter-exposure-control00495nas a2200109 4500008004100000245006400041210006400105260009700169100001800266700001600284856008500300 2007 eng d00aDesigning templates based on a taxonomy of innovative items0 aDesigning templates based on a taxonomy of innovative items aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aParshall, C G1 aHarmes, J C uhttp://www.iacat.org/content/designing-templates-based-taxonomy-innovative-items01549nas a2200169 4500008003900000022001400039245006100053210006100114300001400175490000700189520104600196100001901242700002301261700002201284700001801306856005501324 2007 d a1745-398400aDetecting Differential Speededness in Multistage Testing0 aDetecting Differential Speededness in Multistage Testing a117–1300 v443 a

A potential undesirable effect of multistage testing is differential speededness, which happens if some of the test takers run out of time because they receive subtests with items that are more time intensive than others. This article shows how a probabilistic response-time model can be used for estimating differences in time intensities and speed between subtests and test takers and detecting differential speededness. An empirical data set for a multistage test in the computerized CPA Exam was used to demonstrate the procedures. Although the more difficult subtests appeared to have items that were more time intensive than the easier subtests, an analysis of the residual response times did not reveal any significant differential speededness because the time limit appeared to be appropriate. In a separate analysis, within each of the subtests, we found minor but consistent patterns of residual times that are believed to be due to a warm-up effect, that is, use of more time on the initial items than they actually need.

1 aLinden, Wim, J1 aBreithaupt, Krista1 aChuah, Siang Chee1 aZhang, Yanwei uhttp://dx.doi.org/10.1111/j.1745-3984.2007.00030.x02418nas a2200325 4500008004100000020002200041245008700063210006900150250001500219300001100234490000700245520140100252653001901653653003001672653001901702653003801721653002101759653002001780653001401800653001501814653003301829653001101862653002401873653001801897100001701915700001501932700001501947700001501962856011501977 2007 eng d a0962-9343 (Print)00aDeveloping tailored instruments: item banking and computerized adaptive assessment0 aDeveloping tailored instruments item banking and computerized ad a2007/05/29 a95-1080 v163 aItem banks and Computerized Adaptive Testing (CAT) have the potential to greatly improve the assessment of health outcomes. This review describes the unique features of item banks and CAT and discusses how to develop item banks. In CAT, a computer selects the items from an item bank that are most relevant for and informative about the particular respondent; thus optimizing test relevance and precision. Item response theory (IRT) provides the foundation for selecting the items that are most informative for the particular respondent and for scoring responses on a common metric. The development of an item bank is a multi-stage process that requires a clear definition of the construct to be measured, good items, a careful psychometric analysis of the items, and a clear specification of the final CAT. The psychometric analysis needs to evaluate the assumptions of the IRT model such as unidimensionality and local independence; that the items function the same way in different subgroups of the population; and that there is an adequate fit between the data and the chosen item response models. Also, interpretation guidelines need to be established to help the clinical application of the assessment. Although medical research can draw upon expertise from educational testing in the development of item banks and CAT, the medical field also encounters unique opportunities and challenges.10a*Health Status10a*Health Status Indicators10a*Mental Health10a*Outcome Assessment (Health Care)10a*Quality of Life10a*Questionnaires10a*Software10aAlgorithms10aFactor Analysis, Statistical10aHumans10aModels, Statistical10aPsychometrics1 aBjorner, J B1 aChang, C-H1 aThissen, D1 aReeve, B B uhttp://www.iacat.org/content/developing-tailored-instruments-item-banking-and-computerized-adaptive-assessment00599nas a2200169 4500008004100000245009100041210006900132300001200201490000700213100001600220700001400236700001700250700001400267700001500281700001200296856012100308 2007 eng d00aDevelopment and evaluation of a computer adaptive test for “Anxiety” (Anxiety-CAT)0 aDevelopment and evaluation of a computer adaptive test for Anxie a143-1550 v161 aWalter, O B1 aBecker, J1 aBjorner, J B1 aFliege, H1 aKlapp, B F1 aRose, M uhttp://www.iacat.org/content/development-and-evaluation-computer-adaptive-test-%E2%80%9Canxiety%E2%80%9D-anxiety-cat00496nas a2200109 4500008004100000245006600041210006200107260009700169100002000266700001800286856008200304 2007 eng d00aThe development of a computerized adaptive test for integrity0 adevelopment of a computerized adaptive test for integrity aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aEgberink, I J L1 aVeldkamp, B P uhttp://www.iacat.org/content/development-computerized-adaptive-test-integrity00638nas a2200145 4500008004100000245009700041210006900138260009700207100001600304700001200320700001900332700001300351700001300364856011500377 2007 eng d00aDevelopment of a multiple-component CAT for measuring foreign language proficiency (SIMTEST)0 aDevelopment of a multiplecomponent CAT for measuring foreign lan aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aSumbling, M1 aSanz, P1 aViladrich, M C1 aDoval, E1 aRiera, L uhttp://www.iacat.org/content/development-multiple-component-cat-measuring-foreign-language-proficiency-simtest01798nas a2200217 4500008004100000020004600041245017800087210006900265260002500334300001200359490000700371520094900378653001201327653004301339653001801382653000901400100001701409700001501426700001501441856012401456 2007 eng d a1062-7197 (Print); 1532-6977 (Electronic)00aThe effect of including pretest items in an operational computerized adaptive test: Do different ability examinees spend different amounts of time on embedded pretest items?0 aeffect of including pretest items in an operational computerized bLawrence Erlbaum: US a161-1730 v123 aThe purpose of this study was to examine the effect of pretest items on response time in an operational, fixed-length, time-limited computerized adaptive test (CAT). These pretest items are embedded within the CAT, but unlike the operational items, are not tailored to the examinee's ability level. If examinees with higher ability levels need less time to complete these items than do their counterparts with lower ability levels, they will have more time to devote to the operational test questions. Data were from a graduate admissions test that was administered worldwide. Data from both quantitative and verbal sections of the test were considered. For the verbal section, examinees in the lower ability groups spent systematically more time on their pretest items than did those in the higher ability groups, though for the quantitative section the differences were less clear. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aability10aoperational computerized adaptive test10apretest items10atime1 aFerdous, A A1 aPlake, B S1 aChang, S-R uhttp://www.iacat.org/content/effect-including-pretest-items-operational-computerized-adaptive-test-do-different-ability02156nas a2200133 4500008004100000245012000041210006900161300000900230490000600239520162500245653001701870100001701887856011801904 2007 eng d00aThe effect of using item parameters calibrated from paper administrations in computer adaptive test administrations0 aeffect of using item parameters calibrated from paper administra a1-290 v53 aComputer administered tests are becoming increasingly prevalent as computer technology becomes more readily available on a large scale. For testing programs that utilize both computer and paper administrations, mode effects are problematic in that they can result in examinee scores that are artificially inflated or deflated. As such, researchers have engaged in extensive studies of whether scores differ across paper and computer presentations of the same tests. The research generally seems to indicate that the more complicated it is to present or take a test on computer, the greater the possibility of mode effects. In a computer adaptive test, mode effects may be a particular concern if items are calibrated using item responses obtained from one administration mode (i.e., paper), and those parameters are then used operationally in a different administration mode (i.e., computer). This paper studies the suitability of using parameters calibrated from a paper administration for item selection and scoring in a computer adaptive administration, for two tests with lengthy passages that required navigation in the computer administration. The results showed that the use of paper calibrated parameters versus computer calibrated parameters in computer adaptive administrations had small to moderate effects on the reliability of examinee scores, at fairly short test lengths. This effect was generally diminished for longer test lengths. However, the results suggest that in some cases, some loss in reliability might be inevitable if paper-calibrated parameters are used in computer adaptive administrations.10aMode effects1 aPommerich, M uhttp://www.iacat.org/content/effect-using-item-parameters-calibrated-paper-administrations-computer-adaptive-test02153nas a2200109 4500008003900000245012000039210006900159490000600228520167200234100001701906856012001923 2007 d00aThe Effect of Using Item Parameters Calibrated from Paper Administrations in Computer Adaptive Test Administrations0 aEffect of Using Item Parameters Calibrated from Paper Administra0 v53 a

Computer administered tests are becoming increasingly prevalent as computer technology becomes more readily available on a large scale. For testing programs that utilize both computer and paper administrations, mode effects are problematic in that they can
result in examinee scores that are artificially inflated or deflated. As such, researchers have engaged in extensive studies of whether scores differ across paper and computer presentations of the same tests. The research generally seems to indicate that the more
complicated it is to present or take a test on computer, the greater the possibility of mode effects. In a computer adaptive test, mode effects may be a particular concern if items are calibrated using item responses obtained from one administration mode (i.e., paper), and those parameters are then used operationally in a different administration mode (i.e., computer). This paper studies the suitability of using parameters calibrated from a paper administration for item selection and scoring in a computer adaptive administration, for two tests with lengthy passages that required navigation in the computer administration. The results showed that the use of paper calibrated parameters versus computer calibrated parameters in computer adaptive administrations had small to
moderate effects on the reliability of examinee scores, at fairly short test lengths. This effect was generally diminished for longer test lengths. However, the results suggest that in some cases, some loss in reliability might be inevitable if paper-calibrated parameters
are used in computer adaptive administrations. 

1 aPommerich, M uhttp://www.iacat.org/content/effect-using-item-parameters-calibrated-paper-administrations-computer-adaptive-test-001517nas a2200121 4500008003900000245015300039210006900192300001200261490000700273520103700280100002501317856005301342 2007 d00aEstimating the Standard Error of the Maximum Likelihood Ability Estimator in Adaptive Testing Using the Posterior-Weighted Test Information Function0 aEstimating the Standard Error of the Maximum Likelihood Ability  a958-9750 v673 a

The standard error of the maximum likelihood ability estimator is commonly estimated by evaluating the test information function at an examinee's current maximum likelihood estimate (a point estimate) of ability. Because the test information function evaluated at the point estimate may differ from the test information function evaluated at an examinee's true ability value, the estimated standard error may be biased under certain conditions. This is of particular concern in adaptive testing because the height of the test information function is expected to be higher at the current estimate of ability than at the actual value of ability. This article proposes using the posterior-weighted test information function in computing the standard error of the maximum likelihood ability estimator for adaptive test sessions. A simulation study showed that the proposed approach provides standard error estimates that are less biased and more efficient than those provided by the traditional point estimate approach.

1 aPenfield, Randall, D uhttp://epm.sagepub.com/content/67/6/958.abstract01877nas a2200193 4500008004100000020004600041245005200087210005200139260001900191300001000210490000600220520125500226653003801481653003001519653002301549100001901572700001401591856007801605 2007 eng d a1548-1093 (Print); 1548-1107 (Electronic)00aEvaluation of computer adaptive testing systems0 aEvaluation of computer adaptive testing systems bIGI Global: US a70-870 v23 aMany educational organizations are trying to reduce the cost of the exams, the workload and delay of scoring, and the human errors. Also, they try to increase the accuracy and efficiency of the testing. Recently, most examination organizations use computer adaptive testing (CAT) as the method for large scale testing. This article investigates the current state of CAT systems and identifies their strengths and weaknesses. It evaluates 10 CAT systems using an evaluation framework of 15 domains categorized into three dimensions: educational, technical, and economical. The results show that the majority of the CAT systems give priority to security, reliability, and maintainability. However, they do not offer to the examinee any advanced support and functionalities. Also, the feedback to the examinee is limited and the presentation of the items is poor. Recommendations are made in order to enhance the overall quality of a CAT system. For example, alternative multimedia items should be available so that the examinee would choose a preferred media type. Feedback could be improved by providing more information to the examinee or providing information anytime the examinee wished. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputer adaptive testing systems10aexamination organizations10asystems evaluation1 aEconomides, AA1 aRoupas, C uhttp://www.iacat.org/content/evaluation-computer-adaptive-testing-systems04076nas a2200133 4500008004100000245009300041210006900134300001200203490000700215520357800222100001503800700001603815856011103831 2007 eng d00aAn exploration and realization of computerized adaptive testing with cognitive diagnosis0 aexploration and realization of computerized adaptive testing wit a747-7530 v393 a An increased attention paid to “cognitive bugs behavior,” appears to lead to an increased research interests in diagnostic testing based on Item Response Theory(IRT)that combines cognitive psychology and psychometrics. The study of cognitive diagnosis were applied mainly to Paper-and-Pencil (P&P) testing. Rarely has it been applied to computerized adaptive testing CAT), To our knowledge, no research on CAT with cognitive diagnosis has been conducted in China. Since CAT is more efficient and accurate than P&P testing, there is important to develop an application technique for cognitive diagnosis suitable for CAT. This study attempts to construct a preliminary CAT system for cognitive diagnosis.With the help of the methods for “ Diagnosis first, Ability estimation second ”, the knowledge state conversion diagram was used to describe all the possible knowledge states in a domain of interest and the relation among the knowledge states at the diagnosis stage, where a new strategy of item selection based-on the algorithm of Depth First Search was proposed. On the other hand, those items that contain attributes which the examinee has not mastered were removed in ability estimation. At the stage of accurate ability estimation, all the items answered by each examinee not only matched his/her ability estimated value, but also were limited to those items whose attributes have been mastered by the examinee.We used Monte Carlo Simulation to simulate all the data of the three different structures of cognitive attributes in this study. These structures were tree-shaped, forest-shaped, and some isolated vertices (that are related to simple Q-matrix). Both tree-shaped and isolated vertices structure were derived from actual cases, while forest-shaped structure was a generalized simulation. 3000 examinees and 3000 items were simulated in the experiment of tree-shaped, 2550 examinees and 3100 items in forest-shaped, and 2000 examinees and 2500 items in isolated vertices. The maximum test length was all assumed as 30 items for all those experiments. The difficulty parameters and the logarithm of the discrimination were drawn from the standard normal distribution N(0,1). There were 100 examinees of each attribute pattern in the experiment of tree-shaped and 50 examinees of each attribute pattern in forest-shaped. In isolated vertices, 2000 examinees are students come from actual case.To assess the behaviors of the proposed diagnostic approach, three assessment indices were used. They are attribute pattern classification agreement rate (abr.APCAR), the Recovery (the average of the absolute deviation between the estimated value and the true value) and the average test length (abr. Length).Parts of results of Monte Carlo study were as follows.For the attribute structure of tree-shaped, APCAR is 84.27%,Recovery is 0.17,Length is 24.80.For the attribute structure of forest-shaped, APCAR is 84.02%,Recovery is 0.172,Length is 23.47.For the attribute structure of isolated vertices, APCAR is 99.16%,Recorvery is 0.256,Length is 27.32.As show the above, we can conclude that the results are favorable. The rate of cognitive diagnosis accuracy has exceeded 80% in each experiment, and the Recovery is also good. Therefore, it should be an acceptable idea to construct an initiatory CAT system for cognitive diagnosis, if we use the methods for “Diagnosis first, Ability estimation second ” with the help of both knowledge state conversion diagram and the new strategy of item selection based-on the algorithm of Depth First Search1 aHaijing, L1 aShuliang, D uhttp://www.iacat.org/content/exploration-and-realization-computerized-adaptive-testing-cognitive-diagnosis00584nas a2200109 4500008004100000245011200041210006900153260009700222100001700319700001500336856012300351 2007 eng d00aExploring potential designs for multi-form structure computerized adaptive tests with uniform item exposure0 aExploring potential designs for multiform structure computerized aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aEdwards, M C1 aThissen, D uhttp://www.iacat.org/content/exploring-potential-designs-multi-form-structure-computerized-adaptive-tests-uniform-item02893nas a2200169 4500008004100000020001400041245011300055210006900168300001200237490000700249520229000256100001302546700001602559700001302575700001402588856012102602 2007 eng d a0962-934300aThe future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment0 afuture of outcomes measurement item banking tailored shortforms  a133-1410 v163 aThe use of item banks and computerized adaptive testing (CAT) begins with clear definitions of important outcomes, and references those definitions to specific questions gathered into large and well-studied pools, or “banks” of items. Items can be selected from the bank to form customized short scales, or can be administered in a sequence and length determined by a computer programmed for precision and clinical relevance. Although far from perfect, such item banks can form a common definition and understanding of human symptoms and functional problems such as fatigue, pain, depression, mobility, social function, sensory function, and many other health concepts that we can only measure by asking people directly. The support of the National Institutes of Health (NIH), as witnessed by its cooperative agreement with measurement experts through the NIH Roadmap Initiative known as PROMIS (www.nihpromis.org), is a big step in that direction. Our approach to item banking and CAT is practical; as focused on application as it is on science or theory. From a practical perspective, we frequently must decide whether to re-write and retest an item, add more items to fill gaps (often at the ceiling of the measure), re-test a bank after some modifications, or split up a bank into units that are more unidimensional, yet less clinically relevant or complete. These decisions are not easy, and yet they are rarely unforgiving. We encourage people to build practical tools that are capable of producing multiple short form measures and CAT administrations from common banks, and to further our understanding of these banks with various clinical populations and ages, so that with time the scores that emerge from these many activities begin to have not only a common metric and range, but a shared meaning and understanding across users. In this paper, we provide an overview of item banking and CAT, discuss our approach to item banking and its byproducts, describe testing options, discuss an example of CAT for fatigue, and discuss models for long term sustainability of an entity such as PROMIS. Some barriers to success include limitations in the methods themselves, controversies and disagreements across approaches, and end-user reluctance to move away from the familiar. 1 aCella, D1 aGershon, RC1 aLai, J-S1 aChoi, S W uhttp://www.iacat.org/content/future-outcomes-measurement-item-banking-tailored-short-forms-and-computerized-adaptive00600nas a2200121 4500008004400000245019900044210006900243300001200312490000600324100001200330700001300342856012300355 2007 Germdn 00aHypothetischer Einsatz adaptiven Testens bei der Messung von Bildungsstandards in Mathematik [Hypothetical use of adaptive testing for the measurement of educational standards in mathematics] . 0 aHypothetischer Einsatz adaptiven Testens bei der Messung von Bil a169-1840 v81 aFrey, A1 aEhmke, T uhttp://www.iacat.org/content/hypothetischer-einsatz-adaptiven-testens-bei-der-messung-von-bildungsstandards-mathematik00575nas a2200109 4500008004100000245010400041210006900145260009700214100001900311700001600330856011900346 2007 eng d00aICAT: An adaptive testing procedure to allow the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure to allow the identification o aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/icat-adaptive-testing-procedure-allow-identification-idiosyncratic-knowledge-patterns00521nas a2200097 4500008004100000245008500041210007000126260009700196100001600293856011400309 2007 eng d00aImplementing the Graduate Management Admission Test® computerized adaptive test0 aImplementing the Graduate Management Admission Test® computerize aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aRudner, L M uhttp://www.iacat.org/content/implementing-graduate-management-admission-test%C2%AE-computerized-adaptive-test02875nas a2200313 4500008004100000020002200041245010100063210006900164250001500233260000800248300001200256490000700268520179500275653005102070653002002121653003702141653002602178653001902204653001102223653003002234653004602264653003502310653002802345653001302373100002102386700001702407700001502424856012202439 2007 eng d a0315-162X (Print)00aImproving patient reported outcomes using item response theory and computerized adaptive testing0 aImproving patient reported outcomes using item response theory a a2007/06/07 cJun a1426-310 v343 aOBJECTIVE: Patient reported outcomes (PRO) are considered central outcome measures for both clinical trials and observational studies in rheumatology. More sophisticated statistical models, including item response theory (IRT) and computerized adaptive testing (CAT), will enable critical evaluation and reconstruction of currently utilized PRO instruments to improve measurement precision while reducing item burden on the individual patient. METHODS: We developed a domain hierarchy encompassing the latent trait of physical function/disability from the more general to most specific. Items collected from 165 English-language instruments were evaluated by a structured process including trained raters, modified Delphi expert consensus, and then patient evaluation. Each item in the refined data bank will undergo extensive analysis using IRT to evaluate response functions and measurement precision. CAT will allow for real-time questionnaires of potentially smaller numbers of questions tailored directly to each individual's level of physical function. RESULTS: Physical function/disability domain comprises 4 subdomains: upper extremity, trunk, lower extremity, and complex activities. Expert and patient review led to consensus favoring use of present-tense "capability" questions using a 4- or 5-item Likert response construct over past-tense "performance"items. Floor and ceiling effects, attribution of disability, and standardization of response categories were also addressed. CONCLUSION: By applying statistical techniques of IRT through use of CAT, existing PRO instruments may be improved to reduce questionnaire burden on the individual patients while increasing measurement precision that may ultimately lead to reduced sample size requirements for costly clinical trials.10a*Rheumatic Diseases/physiopathology/psychology10aClinical Trials10aData Interpretation, Statistical10aDisability Evaluation10aHealth Surveys10aHumans10aInternational Cooperation10aOutcome Assessment (Health Care)/*methods10aPatient Participation/*methods10aResearch Design/*trends10aSoftware1 aChakravarty, E F1 aBjorner, J B1 aFries, J F uhttp://www.iacat.org/content/improving-patient-reported-outcomes-using-item-response-theory-and-computerized-adaptive02412nas a2200361 4500008004500000020001400045245011100059210006900170300001200239490000700251520135900258653001601617653002001633653001301653653002401666653002501690653001101715653001401726653001301740653001801753653002701771653001001798653001101808100001501819700001201834700001601846700001201862700001601874700001301890700001301903700001401916856012001930 2007 Engldsh  a1057-924900aThe initial development of an item bank to assess and screen for psychological distress in cancer patients0 ainitial development of an item bank to assess and screen for psy a724-7320 v163 aPsychological distress is a common problem among cancer patients. Despite the large number of instruments that have been developed to assess distress, their utility remains disappointing. This study aimed to use Rasch models to develop an item-bank which would provide the basis for better means of assessing psychological distress in cancer patients. An item bank was developed from eight psychological distress questionnaires using Rasch analysis to link common items. Items from the questionnaires were added iteratively with common items as anchor points and misfitting items (infit mean square > 1.3) removed, and unidimensionality assessed. A total of 4914 patients completed the questionnaires providing an initial pool of 83 items. Twenty items were removed resulting in a final pool of 63 items. Good fit was demonstrated and no additional factor structure was evident from the residuals. However, there was little overlap between item locations and person measures, since items mainly targeted higher levels of distress. The Rasch analysis allowed items to be pooled and generated a unidimensional instrument for measuring psychological distress in cancer patients. Additional items are required to more accurately assess patients across the whole continuum of psychological distress. (PsycINFO Database Record (c) 2007 APA ) (journal abstract)10a3293 Cancer10acancer patients10aDistress10ainitial development10aItem Response Theory10aModels10aNeoplasms10aPatients10aPsychological10apsychological distress10aRasch10aStress1 aSmith, A B1 aRush, R1 aVelikova, G1 aWall, L1 aWright, E P1 aStark, D1 aSelby, P1 aSharpe, M uhttp://www.iacat.org/content/initial-development-item-bank-assess-and-screen-psychological-distress-cancer-patients00514nas a2200109 4500008004100000245007300041210006900114260010000183100001600283700001300299856009200312 2007 eng d00aInvestigating CAT designs to achieve comparability with a paper test0 aInvestigating CAT designs to achieve comparability with a paper  aIn D. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aThompson, T1 aWay, W D uhttp://www.iacat.org/content/investigating-cat-designs-achieve-comparability-paper-test03104nas a2200445 4500008004100000020002200041245007100063210006900134250001500203300001200218490000700230520183100237653003802068653001902106653002102125653002002146653001402166653001102180653003002191653001102221653000902232653002502241653004602266653001802312653002602330100001302356700001402369700001702383700001302400700001502413700001502428700001702443700001402460700001802474700002302492700001602515700001602531700001502547856009602562 2007 eng d a0962-9343 (Print)00aIRT health outcomes data analysis project: an overview and summary0 aIRT health outcomes data analysis project an overview and summar a2007/03/14 a121-1320 v163 aBACKGROUND: In June 2004, the National Cancer Institute and the Drug Information Association co-sponsored the conference, "Improving the Measurement of Health Outcomes through the Applications of Item Response Theory (IRT) Modeling: Exploration of Item Banks and Computer-Adaptive Assessment." A component of the conference was presentation of a psychometric and content analysis of a secondary dataset. OBJECTIVES: A thorough psychometric and content analysis was conducted of two primary domains within a cancer health-related quality of life (HRQOL) dataset. RESEARCH DESIGN: HRQOL scales were evaluated using factor analysis for categorical data, IRT modeling, and differential item functioning analyses. In addition, computerized adaptive administration of HRQOL item banks was simulated, and various IRT models were applied and compared. SUBJECTS: The original data were collected as part of the NCI-funded Quality of Life Evaluation in Oncology (Q-Score) Project. A total of 1,714 patients with cancer or HIV/AIDS were recruited from 5 clinical sites. MEASURES: Items from 4 HRQOL instruments were evaluated: Cancer Rehabilitation Evaluation System-Short Form, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Functional Assessment of Cancer Therapy and Medical Outcomes Study Short-Form Health Survey. RESULTS AND CONCLUSIONS: Four lessons learned from the project are discussed: the importance of good developmental item banks, the ambiguity of model fit results, the limits of our knowledge regarding the practical implications of model misfit, and the importance in the measurement of HRQOL of construct definition. With respect to these lessons, areas for future research are suggested. The feasibility of developing item banks for broad definitions of health is discussed.10a*Data Interpretation, Statistical10a*Health Status10a*Quality of Life10a*Questionnaires10a*Software10aFemale10aHIV Infections/psychology10aHumans10aMale10aNeoplasms/psychology10aOutcome Assessment (Health Care)/*methods10aPsychometrics10aStress, Psychological1 aCook, KF1 aTeal, C R1 aBjorner, J B1 aCella, D1 aChang, C-H1 aCrane, P K1 aGibbons, L E1 aHays, R D1 aMcHorney, C A1 aOcepek-Welikson, K1 aRaczek, A E1 aTeresi, J A1 aReeve, B B uhttp://www.iacat.org/content/irt-health-outcomes-data-analysis-project-overview-and-summary00386nas a2200097 4500008004100000245005800041210005800099260002700157100001800184856008600202 2007 eng d00aItem selection in computerized classification testing0 aItem selection in computerized classification testing aUniversity of Nebraska1 aThompson, N A uhttp://www.iacat.org/content/item-selection-computerized-classification-testing-001119nas a2200169 4500008004100000020002300041245008300064210006900147300001400216490000700230520054200237100001500779700001500794700001700809700001500826856010800841 2007 eng d a0962-93431573-264900aMethodological issues for building item banks and computerized adaptive scales0 aMethodological issues for building item banks and computerized a a109-119, 0 v163 aAbstract This paper reviews important methodological considerations for developing item banks and computerized adaptive scales (commonly called computerized adaptive tests in the educational measurement literature, yielding the acronym CAT), including issues of the reference population, dimensionality, dichotomous versus polytomous response scales, differential item functioning (DIF) and conditional scoring, mode effects, the impact of local dependence, and innovative approaches to assessment using CATs in health outcomes research.1 aThissen, D1 aReeve, B B1 aBjorner, J B1 aChang, C-H uhttp://www.iacat.org/content/methodological-issues-building-item-banks-and-computerized-adaptive-scales02212nas a2200229 4500008004100000020004600041245008500087210006900172260004500241300001000286490000600296520140300302653003401705653002301739653002601762653001701788653002601805100001701831700001201848700001501860856010701875 2007 eng d a1614-1881 (Print); 1614-2241 (Electronic)00aMethods for restricting maximum exposure rate in computerized adaptative testing0 aMethods for restricting maximum exposure rate in computerized ad bHogrefe & Huber Publishers GmbH: Germany a14-230 v33 aThe Sympson-Hetter (1985) method provides a means of controlling maximum exposure rate of items in Computerized Adaptive Testing. Through a series of simulations, control parameters are set that mark the probability of administration of an item on being selected. This method presents two main problems: it requires a long computation time for calculating the parameters and the maximum exposure rate is slightly above the fixed limit. Van der Linden (2003) presented two alternatives which appear to solve both of the problems. The impact of these methods in the measurement accuracy has not been tested yet. We show how these methods over-restrict the exposure of some highly discriminating items and, thus, the accuracy is decreased. It also shown that, when the desired maximum exposure rate is near the minimum possible value, these methods offer an empirical maximum exposure rate clearly above the goal. A new method, based on the initial estimation of the probability of administration and the probability of selection of the items with the restricted method (Revuelta & Ponsoda, 1998), is presented in this paper. It can be used with the Sympson-Hetter method and with the two van der Linden's methods. This option, when used with Sympson-Hetter, speeds the convergence of the control parameters without decreasing the accuracy. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aitem bank security10aitem exposure control10aoverlap rate10aSympson-Hetter method1 aBarrada, J R1 aOlea, J1 aPonsoda, V uhttp://www.iacat.org/content/methods-restricting-maximum-exposure-rate-computerized-adaptative-testing00588nas a2200109 4500008004100000245011500041210006900156260010200225100001300327700001900340856011900359 2007 eng d00aThe modified maximum global discrimination index method for cognitive diagnostic computerized adaptive testing0 amodified maximum global discrimination index method for cognitiv a  D. J. Weiss (Ed.).  Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aCheng, Y1 aChang, Hua-Hua uhttp://www.iacat.org/content/modified-maximum-global-discrimination-index-method-cognitive-diagnostic-computerized00559nas a2200121 4500008004100000245011100041210006900152260003400221100001800255700002500273700001600298856012300314 2007 eng d00aA multiple objective test assembly approach for exposure control problems in computerized adaptive testing0 amultiple objective test assembly approach for exposure control p aArnhem, The NetherlandsbCito1 aVeldkamp, B P1 aVerschoor, Angela, J1 aEggen, Theo uhttp://www.iacat.org/content/multiple-objective-test-assembly-approach-exposure-control-problems-computerized-adaptive01310nas a2200121 4500008003900000245007300039210006900112300001000181490000700191520091400198100002401112856005201136 2007 d00aMutual Information Item Selection in Adaptive Classification Testing0 aMutual Information Item Selection in Adaptive Classification Tes a41-580 v673 a

A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local- and global-information measures in the multiple-category classification setting. Results from simulation studies using three item selection methods, Fisher information (FI), posterior-weighted FI (FIP), and MI, are provided for an adaptive four-category classification test. Both across and within the four classification categories, it is shown that in general, MI item selection classifies the highest proportion of examinees correctly and yields the shortest test lengths. The next best performance is observed for FIP item selection, followed by FI.

1 aWeissman, Alexander uhttp://epm.sagepub.com/content/67/1/41.abstract00375nas a2200109 4500008004100000245005500041210005200096300001000148490001000158100001900168856007800187 2007 eng d00aAn NCME instructional module on multistage testing0 aNCME instructional module on multistage testing a44-520 v26(2)1 aHendrickson, A uhttp://www.iacat.org/content/ncme-instructional-module-multistage-testing00371nas a2200097 4500008004100000245003400041210003200075260009700107100001200204856005700216 2007 eng d00aA new delivery system for CAT0 anew delivery system for CAT aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aPark, J uhttp://www.iacat.org/content/new-delivery-system-cat00408nas a2200097 4500008004100000245004200041210004200083260009800125100001600223856007100239 2007 eng d00aNonparametric online item calibration0 aNonparametric online item calibration aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing. 1 aSamejima, F uhttp://www.iacat.org/content/nonparametric-online-item-calibration00506nas a2200121 4500008004100000245006000041210006000101260009700161100001900258700000700277700001500284856008500299 2007 eng d00aPartial order knowledge structures for CAT applications0 aPartial order knowledge structures for CAT applications aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aDesmarais, M C1 aPu1 aBlais, J-G uhttp://www.iacat.org/content/partial-order-knowledge-structures-cat-applications00655nas a2200121 4500008004100000245015200041210006900193260009700262100001700359700001700376700001400393856012600407 2007 eng d00aPatient-reported outcomes measurement and computerized adaptive testing: An application of post-hoc simulation to a diagnostic screening instrument0 aPatientreported outcomes measurement and computerized adaptive t aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aImmekus, J C1 aGibbons, R D1 aRush, J A uhttp://www.iacat.org/content/patient-reported-outcomes-measurement-and-computerized-adaptive-testing-application-post-hoc01799nas a2200265 4500008004100000020004100041245010400082210006900186250001500255300001100270490001500281520085700296653001901153653003801172653002101210653001401231653002901245653005601274653001101330653002501341653001901366653001801385100001501403856011501418 2007 eng d a0962-9343 (Print)0962-9343 (Linking)00aPatient-reported outcomes measurement and management with innovative methodologies and technologies0 aPatientreported outcomes measurement and management with innovat a2007/05/29 a157-660 v16 Suppl 13 aSuccessful integration of modern psychometrics and advanced informatics in patient-reported outcomes (PRO) measurement and management can potentially maximize the value of health outcomes research and optimize the delivery of quality patient care. Unlike the traditional labor-intensive paper-and-pencil data collection method, item response theory-based computerized adaptive testing methodologies coupled with novel technologies provide an integrated environment to collect, analyze and present ready-to-use PRO data for informed and shared decision-making. This article describes the needs, challenges and solutions for accurate, efficient and cost-effective PRO data acquisition and dissemination means in order to provide critical and timely PRO information necessary to actively support and enhance routine patient care in busy clinical settings.10a*Health Status10a*Outcome Assessment (Health Care)10a*Quality of Life10a*Software10aComputer Systems/*trends10aHealth Insurance Portability and Accountability Act10aHumans10aPatient Satisfaction10aQuestionnaires10aUnited States1 aChang, C-H uhttp://www.iacat.org/content/patient-reported-outcomes-measurement-and-management-innovative-methodologies-and01227nas a2200229 4500008004100000245014700041210006900188300001100257490000700268520046800275100001300743700001300756700001600769700001600785700001300801700001300814700001200827700001500839700001300854700001200867856011800879 2007 eng d00aThe Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH Roadmap cooperative group during its first two years0 aPatientReported Outcomes Measurement Information System PROMIS p aS3-S110 v453 aThe National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System (PROMIS) Roadmap initiative (www.nihpromis.org) is a 5-year cooperative group program of research designed to develop, validate, and standardize item banks to measure patient-reported outcomes (PROs) relevant across common medical conditions. In this article, we will summarize the organization and scientific activity of the PROMIS network during its first 2 years.1 aCella, D1 aYount, S1 aRothrock, N1 aGershon, RC1 aCook, KF1 aReeve, B1 aAder, D1 aFries, J F1 aBruce, B1 aRose, M uhttp://www.iacat.org/content/patient-reported-outcomes-measurement-information-system-promis-progress-nih-roadmap00453nas a2200109 4500008003900000245008500039210006900124300000900193490000700202100001800209856011600227 2007 d00aA Practitioner’s Guide for Variable-length Computerized Classification Testing0 aPractitioner s Guide for Variablelength Computerized Classificat a1-130 v121 aThompson, N A uhttp://www.iacat.org/content/practitioner%E2%80%99s-guide-variable-length-computerized-classification-testing-101457nas a2200181 4500008004100000245008200041210006900123260001300192490000800205520080800213653000801021653001901029653003001048653003401078653004001112100001801152856010501170 2007 eng d00aA practitioner's guide to variable-length computerized classification testing0 apractitioners guide to variablelength computerized classificatio c7/1/20090 v12 3 aVariable-length computerized classification tests, CCTs, (Lin & Spray, 2000; Thompson, 2006) are a powerful and efficient approach to testing for the purpose of classifying examinees into groups. CCTs are designed by the specification of at least five technical components: psychometric model, calibrated item bank, starting point, item selection algorithm, and termination criterion. Several options exist for each of these CCT components, creating a myriad of possible designs. Confusion among designs is exacerbated by the lack of a standardized nomenclature. This article outlines the components of a CCT, common options for each component, and the interaction of options for different components, so that practitioners may more efficiently design CCTs. It also offers a suggestion of nomenclature. 10aCAT10aclassification10acomputer adaptive testing10acomputerized adaptive testing10aComputerized classification testing1 aThompson, N A uhttp://www.iacat.org/content/practitioners-guide-variable-length-computerized-classification-testing00579nas a2200181 4500008004100000245008300041210006900124300001200193490000700205100001000212700001300222700001100235700001000246700001200256700001400268700001300282856010200295 2007 eng d00aProspective evaluation of the am-pac-cat in outpatient rehabilitation settings0 aProspective evaluation of the ampaccat in outpatient rehabilitat a385-3980 v871 aJette1 aHaley, S1 aTao, W1 aNi, P1 aMoed, R1 aMeyers, D1 aZurek, M uhttp://www.iacat.org/content/prospective-evaluation-am-pac-cat-outpatient-rehabilitation-settings02744nas a2200541 4500008004100000020002200041245017000063210006900233250001500302260000800317300001100325490000700336520116200343653001901505653002501524653002101549653002101570653001501591653001001606653000901616653001601625653002301641653003201664653001101696653001101707653000901718653001601727653004601743653001801789653002901807653001801836100001501854700001401869700001701883700001301900700001501913700001601928700001501944700001701959700001401976700001801990700001102008700001602019700001502035700001302050700001302063856012602076 2007 eng d a0025-7079 (Print)00aPsychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS)0 aPsychometric evaluation and calibration of healthrelated quality a2007/04/20 cMay aS22-310 v453 aBACKGROUND: The construction and evaluation of item banks to measure unidimensional constructs of health-related quality of life (HRQOL) is a fundamental objective of the Patient-Reported Outcomes Measurement Information System (PROMIS) project. OBJECTIVES: Item banks will be used as the foundation for developing short-form instruments and enabling computerized adaptive testing. The PROMIS Steering Committee selected 5 HRQOL domains for initial focus: physical functioning, fatigue, pain, emotional distress, and social role participation. This report provides an overview of the methods used in the PROMIS item analyses and proposed calibration of item banks. ANALYSES: Analyses include evaluation of data quality (eg, logic and range checking, spread of response distribution within an item), descriptive statistics (eg, frequencies, means), item response theory model assumptions (unidimensionality, local independence, monotonicity), model fit, differential item functioning, and item calibration for banking. RECOMMENDATIONS: Summarized are key analytic issues; recommendations are provided for future evaluations of item banks in HRQOL assessment.10a*Health Status10a*Information Systems10a*Quality of Life10a*Self Disclosure10aAdolescent10aAdult10aAged10aCalibration10aDatabases as Topic10aEvaluation Studies as Topic10aFemale10aHumans10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPsychometrics10aQuestionnaires/standards10aUnited States1 aReeve, B B1 aHays, R D1 aBjorner, J B1 aCook, KF1 aCrane, P K1 aTeresi, J A1 aThissen, D1 aRevicki, D A1 aWeiss, DJ1 aHambleton, RK1 aLiu, H1 aGershon, RC1 aReise, S P1 aLai, J S1 aCella, D uhttp://www.iacat.org/content/psychometric-evaluation-and-calibration-health-related-quality-life-item-banks-plans-patient02412nas a2200289 4500008004100000020002200041245010800063210006900171260004500240300001000285490000700295520141000302653003201712653002501744653002501769653002501794653002601819653001801845653003701863653002101900653001301921100001501934700001401949700001901963700002001982856012002002 2007 eng d a1015-5759 (Print)00aPsychometric properties of an emotional adjustment measure: An application of the graded response model0 aPsychometric properties of an emotional adjustment measure An ap bHogrefe & Huber Publishers GmbH: Germany a39-460 v233 aItem response theory (IRT) provides valuable methods for the analysis of the psychometric properties of a psychological measure. However, IRT has been mainly used for assessing achievements and ability rather than personality factors. This paper presents an application of the IRT to a personality measure. Thus, the psychometric properties of a new emotional adjustment measure that consists of a 28-six graded response items is shown. Classical test theory (CTT) analyses as well as IRT analyses are carried out. Samejima's (1969) graded-response model has been used for estimating item parameters. Results show that the bank of items fulfills model assumptions and fits the data reasonably well, demonstrating the suitability of the IRT models for the description and use of data originating from personality measures. In this sense, the model fulfills the expectations that IRT has undoubted advantages: (1) The invariance of the estimated parameters, (2) the treatment given to the standard error of measurement, and (3) the possibilities offered for the construction of computerized adaptive tests (CAT). The bank of items shows good reliability. It also shows convergent validity compared to the Eysenck Personality Inventory (EPQ-A; Eysenck & Eysenck, 1975) and the Big Five Questionnaire (BFQ; Caprara, Barbaranelli, & Borgogni, 1993). (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive tests10aEmotional Adjustment10aItem Response Theory10aPersonality Measures10apersonnel recruitment10aPsychometrics10aSamejima's graded response model10atest reliability10avalidity1 aRubio, V J1 aAguado, D1 aHontangas, P M1 aHernández, J M uhttp://www.iacat.org/content/psychometric-properties-emotional-adjustment-measure-application-graded-response-model01722nas a2200169 4500008004100000245016600041210006900207300001000276490000600286520105700292653001501349100001501364700001601379700001701395700001601412856012401428 2007 eng d00aRelative precision, efficiency and construct validity of different starting and stopping rules for a computerized adaptive test: The GAIN Substance Problem Scale0 aRelative precision efficiency and construct validity of differen a48-650 v83 aSubstance abuse treatment programs are being pressed to measure and make clinical decisions more efficiently about an increasing array of problems. This computerized adaptive testing (CAT) simulation examined the relative efficiency, precision and construct validity of different starting and stopping rules used to shorten the Global Appraisal of Individual Needs’ (GAIN) Substance Problem Scale (SPS) and facilitate diagnosis based on it. Data came from 1,048 adolescents and adults referred to substance abuse treatment centers in 5 sites. CAT performance was evaluated using: (1) average standard errors, (2) average number of items, (3) bias in personmeasures, (4) root mean squared error of person measures, (5) Cohen’s kappa to evaluate CAT classification compared to clinical classification, (6) correlation between CAT and full-scale measures, and (7) construct validity of CAT classification vs. clinical classification using correlations with five theoretically associated instruments. Results supported both CAT efficiency and validity.10aMy article1 aRiley, B B1 aConrad, K J1 aBezruczko, N1 aDennis, M L uhttp://www.iacat.org/content/relative-precision-efficiency-and-construct-validity-different-starting-and-stopping-rules01802nas a2200133 4500008004100000245011100041210006900152490001000221520125600231100001801487700002101505700001901526856012301545 2007 eng d00aA review of item exposure control strategies for computerized adaptive testing developed from 1983 to 20050 areview of item exposure control strategies for computerized adap0 v 5(8)3 aSince researchers acknowledged the several advantages of computerized adaptive testing (CAT) over traditional linear test administration, the issue of item exposure control has received increased attention. Due to CAT’s underlying philosophy, particular items in the item pool may be presented too often and become overexposed, while other items are rarely selected by the CAT algorithm and thus become underexposed. Several item exposure control strategies have been presented in the literature aiming to prevent overexposure of some items and to increase the use rate of rarely or never selected items. This paper reviews such strategies that appeared in the relevant literature from 1983 to 2005. The focus of this paper is on studies that have been conducted in order to evaluate the effectiveness of item exposure control strategies for dichotomous scoring, polytomous scoring and testlet-based CAT systems. In addition, the paper discusses the strengths and weaknesses of each strategy group using examples from simulation studies. No new research is presented but rather a compendium of models is reviewed with an overall objective of providing researchers of this field, especially newcomers, a wide view of item exposure control strategies.1 aGeorgiadou, E1 aTriantafillou, E1 aEconomides, AA uhttp://www.iacat.org/content/review-item-exposure-control-strategies-computerized-adaptive-testing-developed-1983-200500518nas a2200097 4500008004100000245008600041210006900127260009700196100002300293856010400316 2007 eng d00aThe shadow-test approach: A universal framework for implementing adaptive testing0 ashadowtest approach A universal framework for implementing adapt aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 avan der Linden, WJ uhttp://www.iacat.org/content/shadow-test-approach-universal-framework-implementing-adaptive-testing00473nas a2200097 4500008004100000245006700041210006700108260009700175100001300272856009000285 2007 eng d00aSome thoughts on controlling item exposure in adaptive testing0 aSome thoughts on controlling item exposure in adaptive testing aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aLewis, C uhttp://www.iacat.org/content/some-thoughts-controlling-item-exposure-adaptive-testing00474nas a2200109 4500008004100000245004400041210004400085260012600129100002300255700001600278856007000294 2007 eng d00aStatistical aspects of adaptive testing0 aStatistical aspects of adaptive testing aC. R. Rao and S. Sinharay (Eds.), Handbook of statistics (Vol. 27: Psychometrics) (pp. 801838). Amsterdam: North-Holland.1 avan der Linden, WJ1 aGlas, C A W uhttp://www.iacat.org/content/statistical-aspects-adaptive-testing02042nas a2200253 4500008004100000020002200041245007400063210006900137250001500206300001100221490000700232520121000239653002201449653001101471653005501482653005101537100001501588700002001603700002301623700001801646700001301664700001701677856009401694 2007 eng d a0885-3924 (Print)00aA system for interactive assessment and management in palliative care0 asystem for interactive assessment and management in palliative c a2007/03/16 a745-550 v333 aThe availability of psychometrically sound and clinically relevant screening, diagnosis, and outcome evaluation tools is essential to high-quality palliative care assessment and management. Such data will enable us to improve patient evaluations, prognoses, and treatment selections, and to increase patient satisfaction and quality of life. To accomplish these goals, medical care needs more precise, efficient, and comprehensive tools for data acquisition, analysis, interpretation, and management. We describe a system for interactive assessment and management in palliative care (SIAM-PC), which is patient centered, model driven, database derived, evidence based, and technology assisted. The SIAM-PC is designed to reliably measure the multiple dimensions of patients' needs for palliative care, and then to provide information to clinicians, patients, and the patients' families to achieve optimal patient care, while improving our capacity for doing palliative care research. This system is innovative in its application of the state-of-the-science approaches, such as item response theory and computerized adaptive testing, to many of the significant clinical problems related to palliative care.10a*Needs Assessment10aHumans10aMedical Informatics/*organization & administration10aPalliative Care/*organization & administration1 aChang, C-H1 aBoni-Saenz, A A1 aDurazo-Arvizu, R A1 aDesHarnais, S1 aLau, D T1 aEmanuel, L L uhttp://www.iacat.org/content/system-interactive-assessment-and-management-palliative-care01688nas a2200217 4500008004100000020002200041245008000063210006900143260002600212300001200238490000700250520095600257653003401213653002701247653002301274653002901297100001601326700001801342700001301360856009701373 2007 eng d a0146-6216 (Print)00aTest design optimization in CAT early stage with the nominal response model0 aTest design optimization in CAT early stage with the nominal res bSage Publications: US a213-2320 v313 aThe early stage of computerized adaptive testing (CAT) refers to the phase of the trait estimation during the administration of only a few items. This phase can be characterized by bias and instability of estimation. In this study, an item selection criterion is introduced in an attempt to lessen this instability: the D-optimality criterion. A polytomous unconstrained CAT simulation is carried out to evaluate this criterion's performance under different test premises. The simulation shows that the extent of early stage instability depends primarily on the quality of the item pool information and its size and secondarily on the item selection criteria. The efficiency of the D-optimality criterion is similar to the efficiency of other known item selection criteria. Yet, it often yields estimates that, at the beginning of CAT, display a more robust performance against instability. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10anominal response model10arobust performance10atest design optimization1 aPassos, V L1 aBerger, M P F1 aTan, F E uhttp://www.iacat.org/content/test-design-optimization-cat-early-stage-nominal-response-model00482nas a2200133 4500008004100000245007700041210006900118300001400187490000600201100001300207700001900220700001000239856009900249 2007 eng d00aTwo-phase item selection procedure for flexible content balancing in CAT0 aTwophase item selection procedure for flexible content balancing a467–4820 v31 aCheng, Y1 aChang, Hua-Hua1 aYi, Q uhttp://www.iacat.org/content/two-phase-item-selection-procedure-flexible-content-balancing-cat01435nas a2200145 4500008003900000245007700039210006900116300001200185490000700197520098600204100001501190700001901205700001201224856005301236 2007 d00aTwo-Phase Item Selection Procedure for Flexible Content Balancing in CAT0 aTwoPhase Item Selection Procedure for Flexible Content Balancing a467-4820 v313 a

Content balancing is an important issue in the design and implementation of computerized adaptive testing (CAT). Content-balancing techniques that have been applied in fixed content balancing, where the number of items from each content area is fixed, include constrained CAT (CCAT), the modified multinomial model (MMM), modified constrained CAT (MCCAT), and others. In this article, four methods are proposed to address the flexible content-balancing issue with the a-stratification design, named STR_C. The four methods are MMM+, an extension of MMM; MCCAT+, an extension of MCCAT; the TPM method, a two-phase content-balancing method using MMM in both phases; and the TPF method, a two-phase content-balancing method using MMM in the first phase and MCCAT in the second. Simulation results show that all of the methods work well in content balancing, and TPF performs the best in item exposure control and item pool utilization while maintaining measurement precision.

1 aYing Cheng1 aChang, Hua-Hua1 aQing Yi uhttp://apm.sagepub.com/content/31/6/467.abstract00585nas a2200121 4500008004100000245009300041210006900134260009700203100001300300700001600313700001900329856011500348 2007 eng d00aUp-and-down procedures for approximating optimal designs using person-response functions0 aUpanddown procedures for approximating optimal designs using per aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aSheng, Y1 aFlournoy, N1 aOsterlind, S J uhttp://www.iacat.org/content/and-down-procedures-approximating-optimal-designs-using-person-response-functions00376nas a2200097 4500008004100000245003400041210003400075260009700109100001500206856005700221 2007 eng d00aUse of CAT in dynamic testing0 aUse of CAT in dynamic testing aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aDe Beer, M uhttp://www.iacat.org/content/use-cat-dynamic-testing00586nas a2200121 4500008004100000245011800041210006900159260006500228100001600293700001500309700001600324856012400340 2007 eng d00aThe use of computerized adaptive testing to assess psychopathology using the Global Appraisal of Individual Needs0 ause of computerized adaptive testing to assess psychopathology u aPortland, OR USAbAmerican Evaluation Association cNovember1 aConrad, K J1 aRiley, B B1 aDennis, M L uhttp://www.iacat.org/content/use-computerized-adaptive-testing-assess-psychopathology-using-global-appraisal-individual00513nas a2200109 4500008003900000245007000039210006900109260009700178100001500275700001900290856009400309 2007 d00aValidity and decision issues in selecting a CAT measurement model0 aValidity and decision issues in selecting a CAT measurement mode aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aOlsen, J B1 aBunderson, C V uhttp://www.iacat.org/content/validity-and-decision-issues-selecting-cat-measurement-model02176nas a2200181 4500008004100000020002200041245006200063210006200125260003800187300001200225490000700237520155900244653002901803653003401832653001801866100002201884856008801906 2006 eng d a0033-3018 (Print)00aAdaptive success control in computerized adaptive testing0 aAdaptive success control in computerized adaptive testing bPabst Science Publishers: Germany a436-4500 v483 aIn computerized adaptive testing (CAT) procedures within the framework of probabilistic test theory the difficulty of an item is adjusted to the ability of the respondent, with the aim of maximizing the amount of information generated per item, thereby also increasing test economy and test reasonableness. However, earlier research indicates that respondents might feel over-challenged by a constant success probability of p = 0.5 and therefore cannot come to a sufficiently high answer certainty within a reasonable timeframe. Consequently response time per item increases, which -- depending on the test material -- can outweigh the benefit of administering optimally informative items. Instead of a benefit, the result of using CAT procedures could be a loss of test economy. Based on this problem, an adaptive success control algorithm was designed and tested, adapting the success probability to the working style of the respondent. Persons who need higher answer certainty in order to come to a decision are detected and receive a higher success probability, in order to minimize the test duration (not the number of items as in classical CAT). The method is validated on the re-analysis of data from the Adaptive Matrices Test (AMT, Hornke, Etzel & Rettig, 1999) and by the comparison between an AMT version using classical CAT and an experimental version using Adaptive Success Control. The results are discussed in the light of psychometric and psychological aspects of test quality. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aadaptive success control10acomputerized adaptive testing10aPsychometrics1 aHäusler, Joachim uhttp://www.iacat.org/content/adaptive-success-control-computerized-adaptive-testing01637nas a2200217 4500008004100000020004600041245008900087210006900176260002500245300000900270490000700279520083400286653001901120653002801139653003001167653003301197653002101230653003501251100001801286856011501304 2006 eng d a0895-7347 (Print); 1532-4818 (Electronic)00aApplying Bayesian item selection approaches to adaptive tests using polytomous items0 aApplying Bayesian item selection approaches to adaptive tests us bLawrence Erlbaum: US a1-200 v193 aThis study applied the maximum expected information (MEI) and the maximum posterior- weighted information (MPI) approaches of computer adaptive testing item selection to the case of a test using polytomous items following the partial credit model. The MEI and MPI approaches are described. A simulation study compared the efficiency of ability estimation using the MEI and MPI approaches to the traditional maximal item information (MII) approach. The results of the simulation study indicated that the MEI and MPI approaches led to a superior efficiency of ability estimation compared with the MII approach. The superiority of the MEI and MPI approaches over the MII approach was greatest when the bank contained items having a relatively peaked information function. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aadaptive tests10aBayesian item selection10acomputer adaptive testing10amaximum expected information10apolytomous items10aposterior weighted information1 aPenfield, R D uhttp://www.iacat.org/content/applying-bayesian-item-selection-approaches-adaptive-tests-using-polytomous-items01963nas a2200265 4500008004100000020002200041245008200063210006900145260002600214300001000240490000700250520112900257653001501386653003401401653001401435653001701449653002401466653001501490653002201505653001501527100002301542700001301565700001801578856010101596 2006 eng d a1076-9986 (Print)00aAssembling a computerized adaptive testing item pool as a set of linear tests0 aAssembling a computerized adaptive testing item pool as a set of bSage Publications: US a81-990 v313 aTest-item writing efforts typically results in item pools with an undesirable correlational structure between the content attributes of the items and their statistical information. If such pools are used in computerized adaptive testing (CAT), the algorithm may be forced to select items with less than optimal information, that violate the content constraints, and/or have unfavorable exposure rates. Although at first sight somewhat counterintuitive, it is shown that if the CAT pool is assembled as a set of linear test forms, undesirable correlations can be broken down effectively. It is proposed to assemble such pools using a mixed integer programming model with constraints that guarantee that each test meets all content specifications and an objective function that requires them to have maximal information at a well-chosen set of ability values. An empirical example with a previous master pool from the Law School Admission Test (LSAT) yielded a CAT with nearly uniform bias and mean-squared error functions for the ability estimator and item-exposure rates that satisfied the target for all items in the pool. 10aAlgorithms10acomputerized adaptive testing10aitem pool10alinear tests10amathematical models10astatistics10aTest Construction10aTest Items1 avan der Linden, WJ1 aAriel, A1 aVeldkamp, B P uhttp://www.iacat.org/content/assembling-computerized-adaptive-testing-item-pool-set-linear-tests00373nas a2200121 4500008004100000245004100041210004100082300001200123490001000135100001700145700001900162856007000181 2006 eng d00aAssessing CAT Test Security Severity0 aAssessing CAT Test Security Severity a62–630 v30(1)1 aYi, Zhang, J1 aChang, Hua-Hua uhttp://www.iacat.org/content/assessing-cat-test-security-severity00347nas a2200097 4500008004100000245004000041210003800081260005500119100001300174856006200187 2006 eng d00aA CAT with personality and attitude0 aCAT with personality and attitude aEnschede, The Netherlands: PrintPartners Ipskamp B1 aHol, A M uhttp://www.iacat.org/content/cat-personality-and-attitude01526nas a2200157 4500008003900000022001400039245011200053210006900165300001400234490000700248520101100255100001601266700001901282700001201301856005501313 2006 d a1745-398400aComparing Methods of Assessing Differential Item Functioning in a Computerized Adaptive Testing Environment0 aComparing Methods of Assessing Differential Item Functioning in  a245–2640 v433 a

Mantel-Haenszel and SIBTEST, which have known difficulty in detecting non-unidirectional differential item functioning (DIF), have been adapted with some success for computerized adaptive testing (CAT). This study adapts logistic regression (LR) and the item-response-theory-likelihood-ratio test (IRT-LRT), capable of detecting both unidirectional and non-unidirectional DIF, to the CAT environment in which pretest items are assumed to be seeded in CATs but not used for trait estimation. The proposed adaptation methods were evaluated with simulated data under different sample size ratios and impact conditions in terms of Type I error, power, and specificity in identifying the form of DIF. The adapted LR and IRT-LRT procedures are more powerful than the CAT version of SIBTEST for non-unidirectional DIF detection. The good Type I error control provided by IRT-LRT under extremely unequal sample sizes and large impact is encouraging. Implications of these and other findings are discussed.

1 aLei, Pui-Wa1 aChen, Shu-Ying1 aYu, Lan uhttp://dx.doi.org/10.1111/j.1745-3984.2006.00015.x01947nas a2200241 4500008004100000020002200041245011200063210006900175260004100244300001200285490000700297520102300304653003401327653002401361653004701385653002401432653002101456653007001477100001301547700001401560700001001574856012101584 2006 eng d a0022-0655 (Print)00aComparing methods of assessing differential item functioning in a computerized adaptive testing environment0 aComparing methods of assessing differential item functioning in  bBlackwell Publishing: United Kingdom a245-2640 v433 aMantel-Haenszel and SIBTEST, which have known difficulty in detecting non-unidirectional differential item functioning (DIF), have been adapted with some success for computerized adaptive testing (CAT). This study adapts logistic regression (LR) and the item-response-theory-likelihood-ratio test (IRT-LRT), capable of detecting both unidirectional and non-unidirectional DIF, to the CAT environment in which pretest items are assumed to be seeded in CATs but not used for trait estimation. The proposed adaptation methods were evaluated with simulated data under different sample size ratios and impact conditions in terms of Type I error, power, and specificity in identifying the form of DIF. The adapted LR and IRT-LRT procedures are more powerful than the CAT version of SIBTEST for non-unidirectional DIF detection. The good Type I error control provided by IRT-LRT under extremely unequal sample sizes and large impact is encouraging. Implications of these and other findings are discussed. all rights reserved)10acomputerized adaptive testing10aeducational testing10aitem response theory likelihood ratio test10alogistic regression10atrait estimation10aunidirectional & non-unidirectional differential item functioning1 aLei, P-W1 aChen, S-Y1 aYu, L uhttp://www.iacat.org/content/comparing-methods-assessing-differential-item-functioning-computerized-adaptive-testing02403nas a2200241 4500008004100000020002200041245008500063210006900148260002500217300001200242490000700254520161500261653000801876653003401884653002601918653003001944653002601974100001402000700001402014700001602028700001502044856010202059 2006 eng d a0439-755X (Print)00aThe comparison among item selection strategies of CAT with multiple-choice items0 acomparison among item selection strategies of CAT with multiplec bScience Press: China a778-7830 v383 aThe initial purpose of comparing item selection strategies for CAT was to increase the efficiency of tests. As studies continued, however, it was found that increasing the efficiency of item bank using was also an important goal of comparing item selection strategies. These two goals often conflicted. The key solution was to find a strategy with which both goals could be accomplished. The item selection strategies for graded response model in this study included: the average of the difficulty orders matching with the ability; the medium of the difficulty orders matching with the ability; maximum information; A stratified (average); and A stratified (medium). The evaluation indexes used for comparison included: the bias of ability estimates for the true; the standard error of ability estimates; the average items which the examinees have administered; the standard deviation of the frequency of items selected; and sum of the indices weighted. Using the Monte Carlo simulation method, we obtained some data and computer iterated the data 20 times each under the conditions that the item difficulty parameters followed the normal distribution and even distribution. The results were as follows; The results indicated that no matter difficulty parameters followed the normal distribution or even distribution. Every type of item selection strategies designed in this research had its strong and weak points. In general evaluation, under the condition that items were stratified appropriately, A stratified (medium) (ASM) had the best effect. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aCAT10acomputerized adaptive testing10agraded response model10aitem selection strategies10amultiple choice items1 aHai-qi, D1 aDe-zhi, C1 aShuliang, D1 aTaiping, D uhttp://www.iacat.org/content/comparison-among-item-selection-strategies-cat-multiple-choice-items00420nas a2200121 4500008004100000245005700041210005500098260002200153100001600175700001300191700001900204856007500223 2006 eng d00aA comparison of online calibration methods for a CAT0 acomparison of online calibration methods for a CAT aSan Francisco, CA1 aMorgan, D L1 aWay, W D1 aAugemberg, K E uhttp://www.iacat.org/content/comparison-online-calibration-methods-cat00526nas a2200133 4500008003900000245013200039210006900171300001200240490000700252100002300259700001900282700002500301856006600326 2006 d00aComparison of the Psychometric Properties of Several Computer-Based Test Designs for Credentialing Exams With Multiple Purposes0 aComparison of the Psychometric Properties of Several ComputerBas a203-2200 v191 aJodoin, Michael, G1 aZenisky, April1 aHambleton, Ronald, K uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_300642nas a2200169 4500008004100000020001300041245013500054210006900189300001400258490000700272100001300279700001000292700001800302700001400320700001300334856012500347 2006 eng d a0895435600aComputer adaptive testing improved accuracy and precision of scores over random item selection in a physical functioning item bank0 aComputer adaptive testing improved accuracy and precision of sco a1174-11820 v591 aHaley, S1 aNi, P1 aHambleton, RK1 aSlavin, M1 aJette, A uhttp://www.iacat.org/content/computer-adaptive-testing-improved-accuracy-and-precision-scores-over-random-item-selection02652nas a2200397 4500008004100000020002200041245013500063210006900198250001500267260000800282300001200290490000700302520140700309653002601716653003101742653001501773653001001788653000901798653002201807653002501829653003301854653001101887653001101898653000901909653001601918653004601934653003001980653003102010653001302041100001502054700001002069700001802079700001602097700001502113856012602128 2006 eng d a0895-4356 (Print)00aComputer adaptive testing improved accuracy and precision of scores over random item selection in a physical functioning item bank0 aComputer adaptive testing improved accuracy and precision of sco a2006/10/10 cNov a1174-820 v593 aBACKGROUND AND OBJECTIVE: Measuring physical functioning (PF) within and across postacute settings is critical for monitoring outcomes of rehabilitation; however, most current instruments lack sufficient breadth and feasibility for widespread use. Computer adaptive testing (CAT), in which item selection is tailored to the individual patient, holds promise for reducing response burden, yet maintaining measurement precision. We calibrated a PF item bank via item response theory (IRT), administered items with a post hoc CAT design, and determined whether CAT would improve accuracy and precision of score estimates over random item selection. METHODS: 1,041 adults were interviewed during postacute care rehabilitation episodes in either hospital or community settings. Responses for 124 PF items were calibrated using IRT methods to create a PF item bank. We examined the accuracy and precision of CAT-based scores compared to a random selection of items. RESULTS: CAT-based scores had higher correlations with the IRT-criterion scores, especially with short tests, and resulted in narrower confidence intervals than scores based on a random selection of items; gains, as expected, were especially large for low and high performing adults. CONCLUSION: The CAT design may have important precision and efficiency advantages for point-of-care functional assessment in rehabilitation practice settings.10a*Recovery of Function10aActivities of Daily Living10aAdolescent10aAdult10aAged10aAged, 80 and over10aConfidence Intervals10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aRehabilitation/*standards10aReproducibility of Results10aSoftware1 aHaley, S M1 aNi, P1 aHambleton, RK1 aSlavin, M D1 aJette, A M uhttp://www.iacat.org/content/computer-adaptive-testing-improved-accuracy-and-precision-scores-over-random-item-selectio-001470nas a2200205 4500008004100000245002700041210002600068260006000094300001100154490000800165520087300173653005101046653003001097653002001127653001801147653001301165100001501178700001501193856005601208 2006 eng d00aComputer-based testing0 aComputerbased testing aWashington D.C. USAbAmerican Psychological Association a87-1000 vxiv3 a(From the chapter) There has been a proliferation of research designed to explore and exploit opportunities provided by computer-based assessment. This chapter provides an overview of the diverse efforts by researchers in this area. It begins by describing how paper-and-pencil tests can be adapted for administration by computers. Computerization provides the important advantage that items can be selected so they are of appropriate difficulty for each examinee. Some of the psychometric theory needed for computerized adaptive testing is reviewed. Then research on innovative computerized assessments is summarized. These assessments go beyond multiple-choice items by using formats made possible by computerization. Then some hardware and software issues are described, and finally, directions for future work are outlined. (PsycINFO Database Record (c) 2006 APA )10aAdaptive Testing computerized adaptive testing10aComputer Assisted Testing10aExperimentation10aPsychometrics10aTheories1 aDrasgow, F1 aChuah, S C uhttp://www.iacat.org/content/computer-based-testing03329nas a2200469 4500008004100000020002200041245011600063210006900179250001500248260000800263300001200271490000700283520189400290653003202184653003102216653002202247653002002269653001002289653000902299653002202308653002802330653003302358653001102391653001102402653002502413653000902438653001602447653004602463653002202509653002402531653003002555653002902585100001502614700001502629700001602644700001102660700002402671700001402695700001802709700001002727856012202737 2006 eng d a0003-9993 (Print)00aComputerized adaptive testing for follow-up after discharge from inpatient rehabilitation: I. Activity outcomes0 aComputerized adaptive testing for followup after discharge from  a2006/08/01 cAug a1033-420 v873 aOBJECTIVE: To examine score agreement, precision, validity, efficiency, and responsiveness of a computerized adaptive testing (CAT) version of the Activity Measure for Post-Acute Care (AM-PAC-CAT) in a prospective, 3-month follow-up sample of inpatient rehabilitation patients recently discharged home. DESIGN: Longitudinal, prospective 1-group cohort study of patients followed approximately 2 weeks after hospital discharge and then 3 months after the initial home visit. SETTING: Follow-up visits conducted in patients' home setting. PARTICIPANTS: Ninety-four adults who were recently discharged from inpatient rehabilitation, with diagnoses of neurologic, orthopedic, and medically complex conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Summary scores from AM-PAC-CAT, including 3 activity domains of movement and physical, personal care and instrumental, and applied cognition were compared with scores from a traditional fixed-length version of the AM-PAC with 66 items (AM-PAC-66). RESULTS: AM-PAC-CAT scores were in good agreement (intraclass correlation coefficient model 3,1 range, .77-.86) with scores from the AM-PAC-66. On average, the CAT programs required 43% of the time and 33% of the items compared with the AM-PAC-66. Both formats discriminated across functional severity groups. The standardized response mean (SRM) was greater for the movement and physical fixed form than the CAT; the effect size and SRM of the 2 other AM-PAC domains showed similar sensitivity between CAT and fixed formats. Using patients' own report as an anchor-based measure of change, the CAT and fixed length formats were comparable in responsiveness to patient-reported change over a 3-month interval. CONCLUSIONS: Accurate estimates for functional activity group-level changes can be obtained from CAT administrations, with a considerable reduction in administration time.10a*Activities of Daily Living10a*Adaptation, Physiological10a*Computer Systems10a*Questionnaires10aAdult10aAged10aAged, 80 and over10aChi-Square Distribution10aFactor Analysis, Statistical10aFemale10aHumans10aLongitudinal Studies10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPatient Discharge10aProspective Studies10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aSiebens, H1 aCoster, W J1 aTao, W1 aBlack-Schaffer, R M1 aGandek, B1 aSinclair, S J1 aNi, P uhttp://www.iacat.org/content/computerized-adaptive-testing-follow-after-discharge-inpatient-rehabilitation-i-activity03166nas a2200361 4500008004100000020002200041245013600063210006900199250001500268260000800283300001200291490000700303520206800310653001502378653002402393653002102417653001002438653000902448653002902457653003402486653002402520653001102544653001102555653001302566653000902579653001602588100001602604700001302620700002302633700001202656700001102668856012502679 2006 eng d a0962-9343 (Print)00aComputerized adaptive testing of diabetes impact: a feasibility study of Hispanics and non-Hispanics in an active clinic population0 aComputerized adaptive testing of diabetes impact a feasibility s a2006/10/13 cNov a1503-180 v153 aBACKGROUND: Diabetes is a leading cause of death and disability in the US and is twice as common among Hispanic Americans as non-Hispanics. The societal costs of diabetes provide an impetus for developing tools that can improve patient care and delay or prevent diabetes complications. METHODS: We implemented a feasibility study of a Computerized Adaptive Test (CAT) to measure diabetes impact using a sample of 103 English- and 97 Spanish-speaking patients (mean age = 56.5, 66.5% female) in a community medical center with a high proportion of minority patients (28% African-American). The 37 items of the Diabetes Impact Survey were translated using forward-backward translation and cognitive debriefing. Participants were randomized to receive either the full-length tool or the Diabetes-CAT first, in the patient's native language. RESULTS: The number of items and the amount of time to complete the survey for the CAT was reduced to one-sixth the amount for the full-length tool in both languages, across disease severity. Confirmatory Factor Analysis confirmed that the Diabetes Impact Survey is unidimensional. The Diabetes-CAT demonstrated acceptable internal consistency reliability, construct validity, and discriminant validity in the overall sample, although subgroup analyses suggested that the English sample data evidenced higher levels of reliability and validity than the Spanish sample and issues with discriminant validity in the Spanish sample. Differential Item Function analysis revealed differences in responses tendencies by language group in 3 of the 37 items. Participant interviews suggested that the Spanish-speaking patients generally preferred the paper survey to the computer-assisted tool, and were twice as likely to experience difficulties understanding the items. CONCLUSIONS: While the Diabetes-CAT demonstrated clear advantages in reducing respondent burden as compared to the full-length tool, simplifying the item bank will be necessary for enhancing the feasibility of the Diabetes-CAT for use with low literacy patients.10a*Computers10a*Hispanic Americans10a*Quality of Life10aAdult10aAged10aData Collection/*methods10aDiabetes Mellitus/*psychology10aFeasibility Studies10aFemale10aHumans10aLanguage10aMale10aMiddle Aged1 aSchwartz, C1 aWelch, G1 aSantiago-Kelley, P1 aBode, R1 aSun, X uhttp://www.iacat.org/content/computerized-adaptive-testing-diabetes-impact-feasibility-study-hispanics-and-non-hispanics00429nas a2200121 4500008003900000245006500039210006500104300001200169490000700181100001000188700001500198856009400213 2006 d00aComputerized adaptive testing under nonparametric IRT models0 aComputerized adaptive testing under nonparametric IRT models a121-1370 v711 aXu, X1 aDouglas, J uhttp://www.iacat.org/content/computerized-adaptive-testing-under-nonparametric-irt-models00535nas a2200121 4500008004100000245011700041210006900158260001800227100001300245700001900258700001400277856012200291 2006 eng d00aConstraints-weighted information method for item selection of severely constrained computerized adaptive testing0 aConstraintsweighted information method for item selection of sev aSan Francisco1 aCheng, Y1 aChang, Hua-Hua1 aWang, X B uhttp://www.iacat.org/content/constraints-weighted-information-method-item-selection-severely-constrained-computerized00452nas a2200109 4500008004100000245004200041210004200083260011500125100001300240700001800253856007100271 2006 eng d00aDesigning computerized adaptive tests0 aDesigning computerized adaptive tests aS.M. Downing and T. M. Haladyna (Eds.), Handbook of test development. New Jersey: Lawrence Erlbaum Associates.1 aDavey, T1 aPitoniak, M J uhttp://www.iacat.org/content/designing-computerized-adaptive-tests01613nas a2200145 4500008003900000245011900039210006900158300001200227490000700239520110300246100002001349700002001369700002501389856005301414 2006 d00aEffects of Estimation Bias on Multiple-Category Classification With an IRT-Based Adaptive Classification Procedure0 aEffects of Estimation Bias on MultipleCategory Classification Wi a545-5640 v663 a

The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory–based adaptive classification procedure on multiple categories were studied via simulations. The following results were found. (a) The Bayesian estimators were more likely to misclassify examinees into an inward category because of their inward biases, when a fixed start value of zero was assigned to every examinee. (b) When moderately accurate start values were available, however, Bayesian estimators produced classifications that were slightly more accurate than was the maximum likelihood estimator or weighted likelihood estimator. Expected a posteriori was the procedure that produced the most accurate results among the three Bayesian methods. (c) All five estimators produced equivalent efficiencies in terms of number of items required, which was 50 or more items except for abilities that were less than -2.00 or greater than 2.00.

1 aYang, Xiangdong1 aPoggio, John, C1 aGlasnapp, Douglas, R uhttp://epm.sagepub.com/content/66/4/545.abstract01584nas a2200205 4500008004100000020002200041245005000063210005000113260002600163300001200189490000700201520094200208653003401150653002801184653001901212653002001231653003301251100002301284856007101307 2006 eng d a0146-6216 (Print)00aEquating scores from adaptive to linear tests0 aEquating scores from adaptive to linear tests bSage Publications: US a493-5080 v303 aTwo local methods for observed-score equating are applied to the problem of equating an adaptive test to a linear test. In an empirical study, the methods were evaluated against a method based on the test characteristic function (TCF) of the linear test and traditional equipercentile equating applied to the ability estimates on the adaptive test for a population of test takers. The two local methods were generally best. Surprisingly, the TCF method performed slightly worse than the equipercentile method. Both methods showed strong bias and uniformly large inaccuracy, but the TCF method suffered from extra error due to the lower asymptote of the test characteristic function. It is argued that the worse performances of the two methods are a consequence of the fact that they use a single equating transformation for an entire population of test takers and therefore have to compromise between the individual score distributions. 10acomputerized adaptive testing10aequipercentile equating10alocal equating10ascore reporting10atest characteristic function1 avan der Linden, WJ uhttp://www.iacat.org/content/equating-scores-adaptive-linear-tests01330nas a2200169 4500008004100000020002700041245010300068210006900171250001500240300000600255490000600261520073400267100001301001700001401014700001401028856011801042 2006 eng d a1975-5937 (Electronic)00aEstimation of an examinee's ability in the web-based computerized adaptive testing program IRT-CAT0 aEstimation of an examinees ability in the webbased computerized  a2006/01/01 a40 v33 aWe developed a program to estimate an examinee s ability in order to provide freely available access to a web-based computerized adaptive testing (CAT) program. We used PHP and Java Script as the program languages, PostgresSQL as the database management system on an Apache web server and Linux as the operating system. A system which allows for user input and searching within inputted items and creates tests was constructed. We performed an ability estimation on each test based on a Rasch model and 2- or 3-parametric logistic models. Our system provides an algorithm for a web-based CAT, replacing previous personal computer-based ones, and makes it possible to estimate an examinee's ability immediately at the end of test.1 aLee, Y H1 aPark, J H1 aPark, I Y uhttp://www.iacat.org/content/estimation-examinees-ability-web-based-computerized-adaptive-testing-program-irt-cat02132nas a2200181 4500008004100000020001300041245013400054210006900188300001200257490000700269520147700276100001601753700001501769700001401784700001601798700001401814856012201828 2006 eng d a0895435600aAn evaluation of a patient-reported outcomes found computerized adaptive testing was efficient in assessing osteoarthritis impact0 aevaluation of a patientreported outcomes found computerized adap a715-7230 v593 aBACKGROUND AND OBJECTIVES: Evaluate a patient-reported outcomes questionnaire that uses computerized adaptive testing (CAT) to measure the impact of osteoarthritis (OA) on functioning and well-being. MATERIALS AND METHODS: OA patients completed 37 questions about the impact of OA on physical, social and role functioning, emotional well-being, and vitality. Questionnaire responses were calibrated and scored using item response theory, and two scores were estimated: a Total-OA score based on patients' responses to all 37 questions, and a simulated CAT-OA score where the computer selected and scored the five most informative questions for each patient. Agreement between Total-OA and CAT-OA scores was assessed using correlations. Discriminant validity of Total-OA and CAT-OA scores was assessed with analysis of variance. Criterion measures included OA pain and severity, patient global assessment, and missed work days. RESULTS: Simulated CAT-OA and Total-OA scores correlated highly (r = 0.96). Both Total-OA and simulated CAT-OA scores discriminated significantly between patients differing on the criterion measures. F-statistics across criterion measures ranged from 39.0 (P < .001) to 225.1 (P < .001) for the Total-OA score, and from 40.5 (P < .001) to 221.5 (P < .001) for the simulated CAT-OA score. CONCLUSIONS: CAT methods produce valid and precise estimates of the impact of OA on functioning and well-being with significant reduction in response burden.1 aKosinski, M1 aBjorner, J1 aWarejr, J1 aSullivan, E1 aStraus, W uhttp://www.iacat.org/content/evaluation-patient-reported-outcomes-found-computerized-adaptive-testing-was-efficient-000450nas a2200133 4500008004100000245005600041210005600097300001200153490001200165100001800177700002100195700001900216856008100235 2006 eng d00aEvaluation parameters for computer adaptive testing0 aEvaluation parameters for computer adaptive testing a261-2780 vVol. 371 aGeorgiadou, E1 aTriantafillou, E1 aEconomides, AA uhttp://www.iacat.org/content/evaluation-parameters-computer-adaptive-testing02398nas a2200301 4500008004100000020002200041245010800063210006900171260002400240300000900264490000600273520142200279653002201701653003401723653002301757653003201780653001801812653002101830653001801851100001401869700001301883700001401896700001901910700001501929700001701944700001301961856012201974 2006 eng d a1529-7713 (Print)00aExpansion of a physical function item bank and development of an abbreviated form for clinical research0 aExpansion of a physical function item bank and development of an bRichard M Smith: US a1-150 v73 aWe expanded an existing 33-item physical function (PF) item bank with a sufficient number of items to enable computerized adaptive testing (CAT). Ten items were written to expand the bank and the new item pool was administered to 295 people with cancer. For this analysis of the new pool, seven poorly performing items were identified for further examination. This resulted in a bank with items that define an essentially unidimensional PF construct, cover a wide range of that construct, reliably measure the PF of persons with cancer, and distinguish differences in self-reported functional performance levels. We also developed a 5-item (static) assessment form ("BriefPF") that can be used in clinical research to express scores on the same metric as the overall bank. The BriefPF was compared to the PF-10 from the Medical Outcomes Study SF-36. Both short forms significantly differentiated persons across functional performance levels. While the entire bank was more precise across the PF continuum than either short form, there were differences in the area of the continuum in which each short form was more precise: the BriefPF was more precise than the PF-10 at the lower functional levels and the PF-10 was more precise than the BriefPF at the higher levels. Future research on this bank will include the development of a CAT version, the PF-CAT. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aclinical research10acomputerized adaptive testing10aperformance levels10aphysical function item bank10aPsychometrics10atest reliability10aTest Validity1 aBode, R K1 aLai, J-S1 aDineen, K1 aHeinemann, A W1 aShevrin, D1 aVon Roenn, J1 aCella, D uhttp://www.iacat.org/content/expansion-physical-function-item-bank-and-development-abbreviated-form-clinical-research02160nas a2200289 4500008004100000245010000041210006900141260000800210300001200218490000700230520127700237653003401514653002101548653000901569653001201578653002201590653001101612653001101623653000901634653001601643653002901659653001901688100001301707700001501720700001301735856012201748 2006 eng d00aFactor analysis techniques for assessing sufficient unidimensionality of cancer related fatigue0 aFactor analysis techniques for assessing sufficient unidimension cSep a1179-900 v153 aBACKGROUND: Fatigue is the most common unrelieved symptom experienced by people with cancer. The purpose of this study was to examine whether cancer-related fatigue (CRF) can be summarized using a single score, that is, whether CRF is sufficiently unidimensional for measurement approaches that require or assume unidimensionality. We evaluated this question using factor analysis techniques including the theory-driven bi-factor model. METHODS: Five hundred and fifty five cancer patients from the Chicago metropolitan area completed a 72-item fatigue item bank, covering a range of fatigue-related concerns including intensity, frequency and interference with physical, mental, and social activities. Dimensionality was assessed using exploratory and confirmatory factor analysis (CFA) techniques. RESULTS: Exploratory factor analysis (EFA) techniques identified from 1 to 17 factors. The bi-factor model suggested that CRF was sufficiently unidimensional. CONCLUSIONS: CRF can be considered sufficiently unidimensional for applications that require unidimensionality. One such application, item response theory (IRT), will facilitate the development of short-form and computer-adaptive testing. This may further enable practical and accurate clinical assessment of CRF.10a*Factor Analysis, Statistical10a*Quality of Life10aAged10aChicago10aFatigue/*etiology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/*complications10aQuestionnaires1 aLai, J-S1 aCrane, P K1 aCella, D uhttp://www.iacat.org/content/factor-analysis-techniques-assessing-sufficient-unidimensionality-cancer-related-fatigue01356nas a2200121 4500008003900000245010500039210006900144300001000213490000700223520092800230100002401158856005201182 2006 d00aA Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing0 aFeedback Control Strategy for Enhancing Item Selection Efficienc a84-990 v303 a

A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level (θ) estimation and vice versa. When discrepancies exist between an examinee's estimated and true θ levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with optimal item selection can be predicted using item response theory (IRT), without knowledge of an examinee's true θ level, yielding a specific reference point for applying an internal correcting or feedback control mechanism. Incorporating such a mechanism in a CAT is shown to be an effective strategy for increasing item selection efficiency. Results from simulation studies using maximum likelihood (ML) and modal a posteriori (MAP) trait-level estimation and Fisher information (FI) and Fisher interval information (FII) item selection are provided.

1 aWeissman, Alexander uhttp://apm.sagepub.com/content/30/2/84.abstract00471nas a2200133 4500008003900000245008700039210006900126300001200195490000700207100002200214700001500236700002000251856006600271 2006 d00aHow Big Is Big Enough? Sample Size Requirements for CAST Item Parameter Estimation0 aHow Big Is Big Enough Sample Size Requirements for CAST Item Par a241-2550 v191 aChuah, Siang Chee1 aDrasgow, F1 aLuecht, Richard uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_500333nas a2200109 4500008003900000245004200039210003900081300001200120490000700132100001800139856006600157 2006 d00aAn Introduction to Multistage Testing0 aIntroduction to Multistage Testing a185-1870 v191 aMead, Alan, D uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_102186nas a2200181 4500008004100000245009900041210006900140260000800209300001400217490000700231520157400238100001401812700001301826700001401839700001601853700001301869856012201882 2006 eng d00aItem banks and their potential applications to health status assessment in diverse populations0 aItem banks and their potential applications to health status ass cNov aS189-S1970 v443 aIn the context of an ethnically diverse, aging society, attention is increasingly turning to health-related quality of life measurement to evaluate healthcare and treatment options for chronic diseases. When evaluating and treating symptoms and concerns such as fatigue, pain, or physical function, reliable and accurate assessment is a priority. Modern psychometric methods have enabled us to move from long, static tests that provide inefficient and often inaccurate assessment of individual patients, to computerized adaptive tests (CATs) that can precisely measure individuals on health domains of interest. These modern methods, collectively referred to as item response theory (IRT), can produce calibrated "item banks" from larger pools of questions. From these banks, CATs can be conducted on individuals to produce their scores on selected domains. Item banks allow for comparison of patients across different question sets because the patient's score is expressed on a common scale. Other advantages of using item banks include flexibility in terms of the degree of precision desired; interval measurement properties under most circumstances; realistic capability for accurate individual assessment over time (using CAT); and measurement equivalence across different patient populations. This work summarizes the process used in the creation and evaluation of item banks and reviews their potential contributions and limitations regarding outcome assessment and patient care, particularly when they are applied across people of different cultural backgrounds.1 aHahn, E A1 aCella, D1 aBode, R K1 aGershon, RC1 aLai, J S uhttp://www.iacat.org/content/item-banks-and-their-potential-applications-health-status-assessment-diverse-populations03383nas a2200205 4500008004100000020002200041245009700063210006900160260002500229300001200254490000700266520266000273653003402933653002802967100001502995700001903010700001703029700001403046856011703060 2006 eng d a0439-755X (Print)00a[Item Selection Strategies of Computerized Adaptive Testing based on Graded Response Model.]0 aItem Selection Strategies of Computerized Adaptive Testing based bScience Press: China a461-4670 v383 aItem selection strategy (ISS) is an important component of Computerized Adaptive Testing (CAT). Its performance directly affects the security, efficiency and precision of the test. Thus, ISS becomes one of the central issues in CATs based on the Graded Response Model (GRM). It is well known that the goal of IIS is to administer the next unused item remaining in the item bank that best fits the examinees current ability estimate. In dichotomous IRT models, every item has only one difficulty parameter and the item whose difficulty matches the examinee's current ability estimate is considered to be the best fitting item. However, in GRM, each item has more than two ordered categories and has no single value to represent the item difficulty. Consequently, some researchers have used to employ the average or the median difficulty value across categories as the difficulty estimate for the item. Using the average value and the median value in effect introduced two corresponding ISSs. In this study, we used computer simulation compare four ISSs based on GRM. We also discussed the effect of "shadow pool" on the uniformity of pool usage as well as the influence of different item parameter distributions and different ability estimation methods on the evaluation criteria of CAT. In the simulation process, Monte Carlo method was adopted to simulate the entire CAT process; 1,000 examinees drawn from standard normal distribution and four 1,000-sized item pools of different item parameter distributions were also simulated. The assumption of the simulation is that a polytomous item is comprised of six ordered categories. In addition, ability estimates were derived using two methods. They were expected a posteriori Bayesian (EAP) and maximum likelihood estimation (MLE). In MLE, the Newton-Raphson iteration method and the Fisher Score iteration method were employed, respectively, to solve the likelihood equation. Moreover, the CAT process was simulated with each examinee 30 times to eliminate random error. The IISs were evaluated by four indices usually used in CAT from four aspects--the accuracy of ability estimation, the stability of IIS, the usage of item pool, and the test efficiency. Simulation results showed adequate evaluation of the ISS that matched the estimate of an examinee's current trait level with the difficulty values across categories. Setting "shadow pool" in ISS was able to improve the uniformity of pool utilization. Finally, different distributions of the item parameter and different ability estimation methods affected the evaluation indices of CAT. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aitem selection strategy1 aPing, Chen1 aShuliang, Ding1 aHaijing, Lin1 aJie, Zhou uhttp://www.iacat.org/content/item-selection-strategies-computerized-adaptive-testing-based-graded-response-model00561nas a2200121 4500008004100000245011200041210006900153260004500222100001800267700001500285700001700300856012200317 2006 eng d00aKernel-smoothed DIF detection procedure for computerized adaptive tests (Computerized testing report 00-08)0 aKernelsmoothed DIF detection procedure for computerized adaptive aNewton, PAbLaw School Admission Council1 aNandakumar, R1 aBanks, J C1 aRoussos, L A uhttp://www.iacat.org/content/kernel-smoothed-dif-detection-procedure-computerized-adaptive-tests-computerized-testing03119nas a2200277 4500008004100000020002200041245010900063210006900172250001500241260000800256300001200264490000700276520221700283653002902500653002002529653002502549653002102574653001502595653002802610653001102638653002502649100001702674700001502691700001202706856012302718 2006 eng d a0214-9915 (Print)00aMaximum information stratification method for controlling item exposure in computerized adaptive testing0 aMaximum information stratification method for controlling item e a2007/02/14 cFeb a156-1590 v183 aThe proposal for increasing the security in Computerized Adaptive Tests that has received most attention in recent years is the a-stratified method (AS - Chang and Ying, 1999): at the beginning of the test only items with low discrimination parameters (a) can be administered, with the values of the a parameters increasing as the test goes on. With this method, distribution of the exposure rates of the items is less skewed, while efficiency is maintained in trait-level estimation. The pseudo-guessing parameter (c), present in the three-parameter logistic model, is considered irrelevant, and is not used in the AS method. The Maximum Information Stratified (MIS) model incorporates the c parameter in the stratification of the bank and in the item-selection rule, improving accuracy by comparison with the AS, for item banks with a and b parameters correlated and uncorrelated. For both kinds of banks, the blocking b methods (Chang, Qian and Ying, 2001) improve the security of the item bank.Método de estratificación por máxima información para el control de la exposición en tests adaptativos informatizados. La propuesta para aumentar la seguridad en los tests adaptativos informatizados que ha recibido más atención en los últimos años ha sido el método a-estratificado (AE - Chang y Ying, 1999): en los momentos iniciales del test sólo pueden administrarse ítems con bajos parámetros de discriminación (a), incrementándose los valores del parámetro a admisibles según avanza el test. Con este método la distribución de las tasas de exposición de los ítems es más equilibrada, manteniendo una adecuada precisión en la medida. El parámetro de pseudoadivinación (c), presente en el modelo logístico de tres parámetros, se supone irrelevante y no se incorpora en el AE. El método de Estratificación por Máxima Información (EMI) incorpora el parámetro c a la estratificación del banco y a la regla de selección de ítems, mejorando la precisión en comparación con AE, tanto para bancos donde los parámetros a y b correlacionan como para bancos donde no. Para ambos tipos de bancos, los métodos de bloqueo de b (Chang, Qian y Ying, 2001) mejoran la seguridad del banco.10a*Artificial Intelligence10a*Microcomputers10a*Psychological Tests10a*Software Design10aAlgorithms10aChi-Square Distribution10aHumans10aLikelihood Functions1 aBarrada, J R1 aMazuela, P1 aOlea, J uhttp://www.iacat.org/content/maximum-information-stratification-method-controlling-item-exposure-computerized-adaptive02567nas a2200349 4500008004100000020002200041245016600063210006900229250001500298260000800313300001100321490000700332520142900339653002701768653001601795653001501811653001001826653002101836653001401857653005201871653001501923653001101938653001101949653003701960653001801997653001402015100001502029700001002044700001602054700002502070856012202095 2006 eng d a0003-9993 (Print)00aMeasurement precision and efficiency of multidimensional computer adaptive testing of physical functioning using the pediatric evaluation of disability inventory0 aMeasurement precision and efficiency of multidimensional compute a2006/08/29 cSep a1223-90 v873 aOBJECTIVE: To compare the measurement efficiency and precision of a multidimensional computer adaptive testing (M-CAT) application to a unidimensional CAT (U-CAT) comparison using item bank data from 2 of the functional skills scales of the Pediatric Evaluation of Disability Inventory (PEDI). DESIGN: Using existing PEDI mobility and self-care item banks, we compared the stability of item calibrations and model fit between unidimensional and multidimensional Rasch models and compared the efficiency and precision of the U-CAT- and M-CAT-simulated assessments to a random draw of items. SETTING: Pediatric rehabilitation hospital and clinics. PARTICIPANTS: Clinical and normative samples. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Not applicable. RESULTS: The M-CAT had greater levels of precision and efficiency than the separate mobility and self-care U-CAT versions when using a similar number of items for each PEDI subdomain. Equivalent estimation of mobility and self-care scores can be achieved with a 25% to 40% item reduction with the M-CAT compared with the U-CAT. CONCLUSIONS: M-CAT applications appear to have both precision and efficiency advantages compared with separate U-CAT assessments when content subdomains have a high correlation. Practitioners may also realize interpretive advantages of reporting test score information for each subdomain when separate clinical inferences are desired.10a*Disability Evaluation10a*Pediatrics10aAdolescent10aChild10aChild, Preschool10aComputers10aDisabled Persons/*classification/rehabilitation10aEfficiency10aHumans10aInfant10aOutcome Assessment (Health Care)10aPsychometrics10aSelf Care1 aHaley, S M1 aNi, P1 aLudlow, L H1 aFragala-Pinkham, M A uhttp://www.iacat.org/content/measurement-precision-and-efficiency-multidimensional-computer-adaptive-testing-physical02405nas a2200337 4500008004100000020002200041245010800063210006900171250001500240260000800255300001100263490000700274520139300281653002101674653002101695653001001716653001101726653001801737653001101755653000901766653001601775653003001791653002801821100001801849700001701867700001801884700001401902700001701916700001701933856011701950 2006 eng d a0962-9343 (Print)00aMultidimensional computerized adaptive testing of the EORTC QLQ-C30: basic developments and evaluations0 aMultidimensional computerized adaptive testing of the EORTC QLQC a2006/03/21 cApr a315-290 v153 aOBJECTIVE: Self-report questionnaires are widely used to measure health-related quality of life (HRQOL). Ideally, such questionnaires should be adapted to the individual patient and at the same time scores should be directly comparable across patients. This may be achieved using computerized adaptive testing (CAT). Usually, CAT is carried out for a single domain at a time. However, many HRQOL domains are highly correlated. Multidimensional CAT may utilize these correlations to improve measurement efficiency. We investigated the possible advantages and difficulties of multidimensional CAT. STUDY DESIGN AND SETTING: We evaluated multidimensional CAT of three scales from the EORTC QLQ-C30: the physical functioning, emotional functioning, and fatigue scales. Analyses utilised a database with 2958 European cancer patients. RESULTS: It was possible to obtain scores for the three domains with five to seven items administered using multidimensional CAT that were very close to the scores obtained using all 12 items and with no or little loss of measurement precision. CONCLUSION: The findings suggest that multidimensional CAT may significantly improve measurement precision and efficiency and encourage further research into multidimensional CAT. Particularly, the estimation of the model underlying the multidimensional CAT and the conceptual aspects need further investigations.10a*Quality of Life10a*Self Disclosure10aAdult10aFemale10aHealth Status10aHumans10aMale10aMiddle Aged10aQuestionnaires/*standards10aUser-Computer Interface1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aFayers, P1 aSprangers, M1 aBjorner, J B uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-eortc-qlq-c30-basic-developments-and00465nas a2200121 4500008004100000245006900041210006900110260002200179100001700201700001800218700001200236856009500248 2006 eng d00aMultiple maximum exposure rates in computerized adaptive testing0 aMultiple maximum exposure rates in computerized adaptive testing aBudapest, Hungary1 aBarrada, J R1 aVeldkamp, B P1 aOlea, J uhttp://www.iacat.org/content/multiple-maximum-exposure-rates-computerized-adaptive-testing00404nas a2200121 4500008003900000245005500039210005300094300001200147490000700159100001900166700003100185856006600216 2006 d00aMultistage Testing: Widely or Narrowly Applicable?0 aMultistage Testing Widely or Narrowly Applicable a257-2600 v191 aStark, Stephen1 aChernyshenko, Oleksandr, S uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_602433nas a2200241 4500008004100000020004600041245008600087210006900173260002500242300001200267490000700279520159900286653001801885653002401903653002001927653002801947653002101975653004001996653001402036100001802050700001202068856011102080 2006 eng d a0895-7347 (Print); 1532-4818 (Electronic)00aOptimal and nonoptimal computer-based test designs for making pass-fail decisions0 aOptimal and nonoptimal computerbased test designs for making pas bLawrence Erlbaum: US a221-2390 v193 aNow that many credentialing exams are being routinely administered by computer, new computer-based test designs, along with item response theory models, are being aggressively researched to identify specific designs that can increase the decision consistency and accuracy of pass-fail decisions. The purpose of this study was to investigate the impact of optimal and nonoptimal multistage test (MST) designs, linear parallel-form test designs (LPFT), and computer adaptive test (CAT) designs on the decision consistency and accuracy of pass-fail decisions. Realistic testing situations matching those of one of the large credentialing agencies were simulated to increase the generalizability of the findings. The conclusions were clear: (a) With the LPFTs, matching test information functions (TIFs) to the mean of the proficiency distribution produced slightly better results than matching them to the passing score; (b) all of the test designs worked better than test construction using random selection of items, subject to content constraints only; (c) CAT performed better than the other test designs; and (d) if matching a TIP to the passing score, the MST design produced a bit better results than the LPFT design. If an argument for the MST design is to be made, it can be made on the basis of slight improvements over the LPFT design and better expected item bank utilization, candidate preference, and the potential for improved diagnostic feedback, compared with the feedback that is possible with fixed linear test forms. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aadaptive test10acredentialing exams10aDecision Making10aEducational Measurement10amultistage tests10aoptimal computer-based test designs10atest form1 aHambleton, RK1 aXing, D uhttp://www.iacat.org/content/optimal-and-nonoptimal-computer-based-test-designs-making-pass-fail-decisions01621nas a2200217 4500008004100000020002200041245008200063210006900145260002600214300001200240490000700252520088700259653002801146653002501174653002501199653001901224653001601243100001601259700002501275856010301300 2006 eng d a0146-6216 (Print)00aOptimal testing with easy or difficult items in computerized adaptive testing0 aOptimal testing with easy or difficult items in computerized ada bSage Publications: US a379-3930 v303 aComputerized adaptive tests (CATs) are individualized tests that, from a measurement point of view, are optimal for each individual, possibly under some practical conditions. In the present study, it is shown that maximum information item selection in CATs using an item bank that is calibrated with the one- or the two-parameter logistic model results in each individual answering about 50% of the items correctly. Two item selection procedures giving easier (or more difficult) tests for students are presented and evaluated. Item selection on probability points of items yields good results only with the one-parameter logistic model and not with the two-parameter logistic model. An alternative selection procedure, based on maximum information at a shifted ability level, gives satisfactory results with both models. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputer adaptive tests10aindividualized tests10aItem Response Theory10aitem selection10aMeasurement1 aEggen, Theo1 aVerschoor, Angela, J uhttp://www.iacat.org/content/optimal-testing-easy-or-difficult-items-computerized-adaptive-testing01352nas a2200133 4500008003900000245008200039210006900121300001200190490000700202520091500209100001601124700002501140856005301165 2006 d00aOptimal Testing With Easy or Difficult Items in Computerized Adaptive Testing0 aOptimal Testing With Easy or Difficult Items in Computerized Ada a379-3930 v303 a

Computerized adaptive tests (CATs) are individualized tests that, from a measurement point of view, are optimal for each individual, possibly under some practical conditions. In the present study, it is shown that maximum information item selection in CATs using an item bank that is calibrated with the one or the two-parameter logistic model results in each individual answering about 50% of the items correctly. Two item selection procedures giving easier (or more difficult) tests for students are presented and evaluated. Item selection on probability points of items yields good results only with the one-parameter logistic model and not with the two-parameter logistic model. An alternative selection procedure, based on maximum information at a shifted ability level, gives satisfactory results with both models. Index terms: computerized adaptive testing, item selection, item response theory

1 aEggen, Theo1 aVerschoor, Angela, J uhttp://apm.sagepub.com/content/30/5/379.abstract01482nas a2200145 4500008003900000245006500039210006500104300001200169490000700181520102700188100002001215700002501235700002301260856005301283 2006 d00aOptimal Testlet Pool Assembly for Multistage Testing Designs0 aOptimal Testlet Pool Assembly for Multistage Testing Designs a204-2150 v303 a

Computerized multistage testing (MST) designs require sets of test questions (testlets) to be assembled to meet strict, often competing criteria. Rules that govern testlet assembly may dictate the number of questions on a particular subject or may describe desirable statistical properties for the test, such as measurement precision. In an MST design, testlets of differing difficulty levels must be created. Statistical properties for assembly of the testlets can be expressed using item response theory (IRT) parameters. The testlet test information function (TIF) value can be maximized at a specific point on the IRT ability scale. In practical MST designs, parallel versions of testlets are needed, so sets of testlets with equivalent properties are built according to equivalent specifications. In this project, the authors study the use of a mathematical programming technique to simultaneously assemble testlets to ensure equivalence and fairness to candidates who may be administered different testlets.

1 aAriel, Adelaide1 aVeldkamp, Bernard, P1 aBreithaupt, Krista uhttp://apm.sagepub.com/content/30/3/204.abstract02516nas a2200265 4500008004100000020004100041245013200082210006900214250001500283260000800298300001100306490000700317520154000324653003101864653003701895653003301932653002401965653001101989653002402000653002702024653003302051653003002084100001602114856012002130 2006 eng d a0025-7079 (Print)0025-7079 (Linking)00aOverview of quantitative measurement methods. Equivalence, invariance, and differential item functioning in health applications0 aOverview of quantitative measurement methods Equivalence invaria a2006/10/25 cNov aS39-490 v443 aBACKGROUND: Reviewed in this article are issues relating to the study of invariance and differential item functioning (DIF). The aim of factor analyses and DIF, in the context of invariance testing, is the examination of group differences in item response conditional on an estimate of disability. Discussed are parameters and statistics that are not invariant and cannot be compared validly in crosscultural studies with varying distributions of disability in contrast to those that can be compared (if the model assumptions are met) because they are produced by models such as linear and nonlinear regression. OBJECTIVES: The purpose of this overview is to provide an integrated approach to the quantitative methods used in this special issue to examine measurement equivalence. The methods include classical test theory (CTT), factor analytic, and parametric and nonparametric approaches to DIF detection. Also included in the quantitative section is a discussion of item banking and computerized adaptive testing (CAT). METHODS: Factorial invariance and the articles discussing this topic are introduced. A brief overview of the DIF methods presented in the quantitative section of the special issue is provided together with a discussion of ways in which DIF analyses and examination of invariance using factor models may be complementary. CONCLUSIONS: Although factor analytic and DIF detection methods share features, they provide unique information and can be viewed as complementary in informing about measurement equivalence.10a*Cross-Cultural Comparison10aData Interpretation, Statistical10aFactor Analysis, Statistical10aGuidelines as Topic10aHumans10aModels, Statistical10aPsychometrics/*methods10aStatistics as Topic/*methods10aStatistics, Nonparametric1 aTeresi, J A uhttp://www.iacat.org/content/overview-quantitative-measurement-methods-equivalence-invariance-and-differential-item00578nas a2200133 4500008003900000245014600039210006900185300001200254490000700266100001500273700002500288700001000313856012100323 2006 d00aSensitivity of a computer adaptive assessment for measuring functional mobility changes in children enrolled in a community fitness programme0 aSensitivity of a computer adaptive assessment for measuring func a616-6220 v201 aHaley, S M1 aFragala-Pinkham, M A1 aNi, P uhttp://www.iacat.org/content/sensitivity-computer-adaptive-assessment-measuring-functional-mobility-changes-children00395nas a2200109 4500008003900000245007400039210007200113300001000185490000600195100001800201856006600219 2006 d00aSequential Computerized Mastery Tests—Three Simulation Studies0 aSequential Computerized Mastery Tests†Three Simulation Studies a41-550 v61 aWiberg, Marie uhttp://www.tandfonline.com/doi/abs/10.1207/s15327574ijt0601_302346nas a2200217 4500008004100000020002200041245008000063210006900143260002600212300001000238490000700248520160400255653003001859653002101889653003201910653003001942653002501972100001501997700001502012856010102027 2006 eng d a0146-6216 (Print)00aSIMCAT 1.0: A SAS computer program for simulating computer adaptive testing0 aSIMCAT 10 A SAS computer program for simulating computer adaptiv bSage Publications: US a60-610 v303 aMonte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their flexibility is limited. SIMCAT 1.0 is aimed at the simulation of adaptive testing sessions under different adaptive expected a posteriori (EAP) proficiency-level estimation methods (Blais & Raîche, 2005; Raîche & Blais, 2005) based on the one-parameter Rasch logistic model. These methods are all adaptive in the a priori proficiency-level estimation, the proficiency-level estimation bias correction, the integration interval, or a combination of these factors. The use of these adaptive EAP estimation methods diminishes considerably the shrinking, and therefore biasing, effect of the estimated a priori proficiency level encountered when this a priori is fixed at a constant value independently of the computed previous value of the proficiency level. SIMCAT 1.0 also computes empirical and estimated skewness and kurtosis coefficients, such as the standard error, of the estimated proficiency-level sampling distribution. In this way, the program allows one to compare empirical and estimated properties of the estimated proficiency-level sampling distribution under different variations of the EAP estimation method: standard error and bias, like the skewness and kurtosis coefficients. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputer adaptive testing10acomputer program10aestimated proficiency level10aMonte Carlo methodologies10aRasch logistic model1 aRaîche, G1 aBlais, J-G uhttp://www.iacat.org/content/simcat-10-sas-computer-program-simulating-computer-adaptive-testing00595nas a2200145 4500008004100000245013800041210006900179300001200248490000700260100001200267700001600279700001500295700001700310856012200327 2006 eng d00aSimulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with lumbar sp a947-9560 v591 aHart, D1 aMioduski, J1 aWerenke, M1 aStratford, P uhttp://www.iacat.org/content/simulated-computerized-adaptive-test-patients-lumbar-spine-impairments-was-efficient-and02111nas a2200229 4500008004100000245013800041210006900179300001400248490000700262520127000269653003101539653003401570653002501604653001701629653001901646653002401665100001401689700001801703700001701721700001901738856012401757 2006 eng d00aSimulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with lumbar sp a947–9560 v593 aObjective: To equate physical functioning (PF) items with Back Pain Functional Scale (BPFS) items, develop a computerized adaptive test (CAT) designed to assess lumbar spine functional status (LFS) in people with lumbar spine impairments, and compare discriminant validity of LFS measures (qIRT) generated using all items analyzed with a rating scale Item Response Theory model (RSM) and measures generated using the simulated CAT (qCAT). Methods: We performed a secondary analysis of retrospective intake rehabilitation data. Results: Unidimensionality and local independence of 25 BPFS and PF items were supported. Differential item functioning was negligible for levels of symptom acuity, gender, age, and surgical history. The RSM fit the data well. A lumbar spine specific CAT was developed that was 72% more efficient than using all 25 items to estimate LFS measures. qIRT and qCAT measures did not discriminate patients by symptom acuity, age, or gender, but discriminated patients by surgical history in similar clinically logical ways. qCAT measures were as precise as qIRT measures. Conclusion: A body part specific simulated CAT developed from an LFS item bank was efficient and produced precise measures of LFS without eroding discriminant validity.10aBack Pain Functional Scale10acomputerized adaptive testing10aItem Response Theory10aLumbar spine10aRehabilitation10aTrue-score equating1 aHart, D L1 aMioduski, J E1 aWerneke, M W1 aStratford, P W uhttp://www.iacat.org/content/simulated-computerized-adaptive-test-patients-lumbar-spine-impairments-was-efficient-and-002653nas a2200409 4500008004100000245013400041210006900175300001000244490000700254520123100261653002501492653003201517653003101549653001001580653000901590653002201599653003301621653001101654653001101665653000901676653001601685653002401701653003101725653004101756653004501797653006801842653006101910653003001971653002802001653002202029100001402051700001302065700001802078700001402096700001502110856011802125 2006 eng d00aSimulated computerized adaptive test for patients with shoulder impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with shoulder  a290-80 v593 aBACKGROUND AND OBJECTIVE: To test unidimensionality and local independence of a set of shoulder functional status (SFS) items, develop a computerized adaptive test (CAT) of the items using a rating scale item response theory model (RSM), and compare discriminant validity of measures generated using all items (theta(IRT)) and measures generated using the simulated CAT (theta(CAT)). STUDY DESIGN AND SETTING: We performed a secondary analysis of data collected prospectively during rehabilitation of 400 patients with shoulder impairments who completed 60 SFS items. RESULTS: Factor analytic techniques supported that the 42 SFS items formed a unidimensional scale and were locally independent. Except for five items, which were deleted, the RSM fit the data well. The remaining 37 SFS items were used to generate the CAT. On average, 6 items were needed to estimate precise measures of function using the SFS CAT, compared with all 37 SFS items. The theta(IRT) and theta(CAT) measures were highly correlated (r = .96) and resulted in similar classifications of patients. CONCLUSION: The simulated SFS CAT was efficient and produced precise, clinically relevant measures of functional status with good discriminating ability.10a*Computer Simulation10a*Range of Motion, Articular10aActivities of Daily Living10aAdult10aAged10aAged, 80 and over10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aProspective Studies10aReproducibility of Results10aResearch Support, N.I.H., Extramural10aResearch Support, U.S. Gov't, Non-P.H.S.10aShoulder Dislocation/*physiopathology/psychology/rehabilitation10aShoulder Pain/*physiopathology/psychology/rehabilitation10aShoulder/*physiopathology10aSickness Impact Profile10aTreatment Outcome1 aHart, D L1 aCook, KF1 aMioduski, J E1 aTeal, C R1 aCrane, P K uhttp://www.iacat.org/content/simulated-computerized-adaptive-test-patients-shoulder-impairments-was-efficient-and02072nas a2200217 4500008004500000245013400045210006900179300001200248490000700260520127300267653003401540653004201574653002501616653001901641100001401660700001301674700001801687700001401705700001501719856012001734 2006 Engldsh 00aSimulated computerized adaptive test for patients with shoulder impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with shoulder  a290-2980 v593 a

Background and Objective: To test unidimensionality and local independence of a set of shoulder functional status (SFS) items,
develop a computerized adaptive test (CAT) of the items using a rating scale item response theory model (RSM), and compare discriminant validity of measures generated using all items (qIRT) and measures generated using the simulated CAT (qCAT).
Study Design and Setting: We performed a secondary analysis of data collected prospectively during rehabilitation of 400 patients
with shoulder impairments who completed 60 SFS items.
Results: Factor analytic techniques supported that the 42 SFS items formed a unidimensional scale and were locally independent. Except for five items, which were deleted, the RSM fit the data well. The remaining 37 SFS items were used to generate the CAT. On average, 6 items on were needed to estimate precise measures of function using the SFS CAT, compared with all 37 SFS items. The qIRT and qCAT measures were highly correlated (r 5 .96) and resulted in similar classifications of patients.
Conclusion: The simulated SFS CAT was efficient and produced precise, clinically relevant measures of functional status with good
discriminating ability. 

10acomputerized adaptive testing10aFlexilevel Scale of Shoulder Function10aItem Response Theory10aRehabilitation1 aHart, D L1 aCook, KF1 aMioduski, J E1 aTeal, C R1 aCrane, P K uhttp://www.iacat.org/content/simulated-computerized-adaptive-test-patients-shoulder-impairments-was-efficient-and-002251nas a2200301 4500008004500000020001400045245009800059210007100157300001200228490000700240520127200247653003201519653002601551653002801577653001801605653002501623653001601648653001201664653001501676653001801691653001601709653001801725653002701743653001101770100001901781700001601800856013301816 2006 Spandsh  a0212-972800aTécnicas para detectar patrones de respuesta atípicos [Aberrant patterns detection methods]0 aTécnicas para detectar patrones de respuesta atípicos Aberrant p a143-1540 v223 aLa identificación de patrones de respuesta atípicos es de gran utilidad para la construcción de tests y de bancos de ítems con propiedades psicométricas así como para el análisis de validez de los mismos. En este trabajo de revisión se han recogido los más relevantes y novedosos métodos de ajuste de personas que se han elaborado dentro de cada uno de los principales ámbitos de trabajo de la Psicometría: el escalograma de Guttman, la Teoría Clásica de Tests (TCT), la Teoría de la Generalizabilidad (TG), la Teoría de Respuesta al Ítem (TRI), los Modelos de Respuesta al Ítem No Paramétricos (MRINP), los Modelos de Clase Latente de Orden Restringido (MCL-OR) y el Análisis de Estructura de Covarianzas (AEC).Aberrant patterns detection has a great usefulness in order to make tests and item banks with psychometric characteristics and validity analysis of tests and items. The most relevant and newest person-fit methods have been reviewed. All of them have been made in each one of main areas of Psychometry: Guttman's scalogram, Classical Test Theory (CTT), Generalizability Theory (GT), Item Response Theory (IRT), Non-parametric Response Models (NPRM), Order-Restricted Latent Class Models (OR-LCM) and Covariance Structure Analysis (CSA).10aaberrant patterns detection10aClassical Test Theory10ageneralizability theory10aItem Response10aItem Response Theory10aMathematics10amethods10aperson-fit10aPsychometrics10apsychometry10aTest Validity10atest validity analysis10aTheory1 aNúñez, R M N1 aPina, J A L uhttp://www.iacat.org/content/t%C3%A9cnicas-para-detectar-patrones-de-respuesta-at%C3%ADpicos-aberrant-patterns-detection-methods00444nas a2200133 4500008003900000245006200039210006000101300001200161490000700173100002000180700002100200700002300221856006600244 2006 d00aA testlet assembly design for the uniform CPA Examination0 atestlet assembly design for the uniform CPA Examination a189-2020 v191 aLuecht, Richard1 aBrumfield, Terry1 aBreithaupt, Krista uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_200425nas a2200085 4500008004100000245009500041210007000136100001200206856012100218 2006 eng d00aValiditätssteigerungen durch adaptives Testen [Increasing validity by adaptive testing]. 0 aValiditätssteigerungen durch adaptives Testen Increasing validit1 aFrey, A uhttp://www.iacat.org/content/validit%C3%A4tssteigerungen-durch-adaptives-testen-increasing-validity-adaptive-testing00587nas a2200121 4500008004100000245016300041210006900204260001800273100001800291700001600309700001400325856012600339 2006 eng d00aA variant of the progressive restricted item exposure control procedure in computerized adaptive testing systems based on the 3PL and the partial credit model0 avariant of the progressive restricted item exposure control proc aSan Francisco1 aMcClarty, L K1 aSperling, R1 aDodd, B G uhttp://www.iacat.org/content/variant-progressive-restricted-item-exposure-control-procedure-computerized-adaptive-testing00544nas a2200097 4500008004100000245006200041210006200103260017400165100001900339856008800358 2005 eng d00aAdaptive orientation methods in computer adaptive testing0 aAdaptive orientation methods in computer adaptive testing aProceedings E-Learn 2005 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 1290-1295, Vancouver, Canada, AACE, October 2005.1 aEconomides, AA uhttp://www.iacat.org/content/adaptive-orientation-methods-computer-adaptive-testing00508nam a2200097 4500008004100000245009800041210006900139260006400208100001900272856011900291 2005 eng d00aAdaptive selection of personality items to inform a neural network predicting job performance0 aAdaptive selection of personality items to inform a neural netwo aUnpublished doctoral dissertation, University of Washington1 aThissen-Roe, A uhttp://www.iacat.org/content/adaptive-selection-personality-items-inform-neural-network-predicting-job-performance01469nas a2200217 4500008004100000245015400041210006900195260004600264300001200310520063100322653003000953653001100983653002500994653001601019653002201035653002301057100001801080700001501098700001401113856012401127 2005 eng d00aApplications of item response theory to improve health outcomes assessment: Developing item banks, linking instruments, and computer-adaptive testing0 aApplications of item response theory to improve health outcomes  aCambridge, UKbCambridge University Press a445-4643 a(From the chapter) The current chapter builds on Reise's introduction to the basic concepts, assumptions, popular models, and important features of IRT and discusses the applications of item response theory (IRT) modeling to health outcomes assessment. In particular, we highlight the critical role of IRT modeling in: developing an instrument to match a study's population; linking two or more instruments measuring similar constructs on a common metric; and creating item banks that provide the foundation for tailored short-form instruments or for computerized adaptive assessments. (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aHealth10aItem Response Theory10aMeasurement10aTest Construction10aTreatment Outcomes1 aHambleton, RK1 aGotay, C C1 aSnyder, C uhttp://www.iacat.org/content/applications-item-response-theory-improve-health-outcomes-assessment-developing-item-banks03123nas a2200385 4500008004100000020002200041245012900063210006900192250001500261260000800276300001000284490000700294520188400301653002502185653002702210653001502237653001002252653002102262653002802283653003802311653001102349653001102360653001102371653000902382653004602391653002702437653003002464653003202494100001502526700001602541700001602557700001502573700002502588856012402613 2005 eng d a0003-9993 (Print)00aAssessing mobility in children using a computer adaptive testing version of the pediatric evaluation of disability inventory0 aAssessing mobility in children using a computer adaptive testing a2005/05/17 cMay a932-90 v863 aOBJECTIVE: To assess score agreement, validity, precision, and response burden of a prototype computerized adaptive testing (CAT) version of the Mobility Functional Skills Scale (Mob-CAT) of the Pediatric Evaluation of Disability Inventory (PEDI) as compared with the full 59-item version (Mob-59). DESIGN: Computer simulation analysis of cross-sectional and longitudinal retrospective data; and cross-sectional prospective study. SETTING: Pediatric rehabilitation hospital, including inpatient acute rehabilitation, day school program, outpatient clinics, community-based day care, preschool, and children's homes. PARTICIPANTS: Four hundred sixty-nine children with disabilities and 412 children with no disabilities (analytic sample); 41 children without disabilities and 39 with disabilities (cross-validation sample). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Summary scores from a prototype Mob-CAT application and versions using 15-, 10-, and 5-item stopping rules; scores from the Mob-59; and number of items and time (in seconds) to administer assessments. RESULTS: Mob-CAT scores from both computer simulations (intraclass correlation coefficient [ICC] range, .94-.99) and field administrations (ICC=.98) were in high agreement with scores from the Mob-59. Using computer simulations of retrospective data, discriminant validity, and sensitivity to change of the Mob-CAT closely approximated that of the Mob-59, especially when using the 15- and 10-item stopping rule versions of the Mob-CAT. The Mob-CAT used no more than 15% of the items for any single administration, and required 20% of the time needed to administer the Mob-59. CONCLUSIONS: Comparable score estimates for the PEDI mobility scale can be obtained from CAT administrations, with losses in validity and precision for shorter forms, but with a considerable reduction in administration time.10a*Computer Simulation10a*Disability Evaluation10aAdolescent10aChild10aChild, Preschool10aCross-Sectional Studies10aDisabled Children/*rehabilitation10aFemale10aHumans10aInfant10aMale10aOutcome Assessment (Health Care)/*methods10aRehabilitation Centers10aRehabilitation/*standards10aSensitivity and Specificity1 aHaley, S M1 aRaczek, A E1 aCoster, W J1 aDumas, H M1 aFragala-Pinkham, M A uhttp://www.iacat.org/content/assessing-mobility-children-using-computer-adaptive-testing-version-pediatric-evaluation-000639nas a2200169 4500008004100000020001300041245012900054210006900183300001200252490000700264100001300271700001400284700001400298700001300312700002200325856012200347 2005 eng d a0003999300aAssessing Mobility in Children Using a Computer Adaptive Testing Version of the Pediatric Evaluation of Disability Inventory0 aAssessing Mobility in Children Using a Computer Adaptive Testing a932-9390 v861 aHaley, S1 aRaczek, A1 aCoster, W1 aDumas, H1 aFragalapinkham, M uhttp://www.iacat.org/content/assessing-mobility-children-using-computer-adaptive-testing-version-pediatric-evaluation01373nas a2200193 4500008004100000245005000041210004700091300001000138490000600148520081200154653001700966653002100983653002601004653002501030100001501055700001401070700002301084856007201107 2005 eng d00aAn Authoring Environment for Adaptive Testing0 aAuthoring Environment for Adaptive Testing a66-760 v83 a

SIETTE is a web-based adaptive testing system. It implements Computerized Adaptive Tests. These tests are tailor-made, theory-based tests, where questions shown to students, finalization of the test, and student knowledge estimation is accomplished adaptively. To construct these tests, SIETTE has an authoring environment comprising a suite of tools that helps teachers create questions and tests properly, and analyze students’ performance after taking a test. In this paper, we present this authoring environment in the
framework of adaptive testing. As will be shown, this set of visual tools, that contain some adaptable eatures, can be useful for teachers lacking skills in this kind of testing. Additionally, other systems that implement adaptive testing will be studied. 

10aAdaptability10aAdaptive Testing10aAuthoring environment10aItem Response Theory1 aGuzmán, E1 aConejo, R1 aGarcía-Hervás, E uhttp://www.iacat.org/content/authoring-environment-adaptive-testing00443nas a2200133 4500008003900000245005900039210005900098300001200157490000600169100002300175700002000198700002500218856006600243 2005 d00aAutomated Simultaneous Assembly for Multistage Testing0 aAutomated Simultaneous Assembly for Multistage Testing a319-3300 v51 aBreithaupt, Krista1 aAriel, Adelaide1 aVeldkamp, Bernard, P uhttp://www.tandfonline.com/doi/abs/10.1207/s15327574ijt0503_802242nas a2200205 4500008004100000020004600041245009500087210006900182260002700251300001200278490000700290520149400297653002701791653003001818653001701848653002501865100001901890700001001909856011701919 2005 eng d a1560-4292 (Print); 1560-4306 (Electronic)00aA Bayesian student model without hidden nodes and its comparison with item response theory0 aBayesian student model without hidden nodes and its comparison w bIOS Press: Netherlands a291-3230 v153 aThe Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where such a technique can be useful is Computer Adaptive Testing (CAT). A Bayesian modeling scheme, POKS, is proposed and compared to the traditional Item Response Theory (IRT), which has been the prevalent CAT approach for the last three decades. POKS is based on the theory of knowledge spaces and constructs item-to-item graph structures without hidden nodes. It aims to offer an effective knowledge assessment method with an efficient algorithm for learning the graph structure from data. We review the different Bayesian approaches to modeling student ability assessment and discuss how POKS relates to them. The performance of POKS is compared to the IRT two parameter logistic model. Experimental results over a 34 item Unix test and a 160 item French language test show that both approaches can classify examinees as master or non-master effectively and efficiently, with relatively comparable performance. However, more significant differences are found in favor of POKS for a second task that consists in predicting individual question item outcome. Implications of these results for adaptive testing and student modeling are discussed, as well as the limitations and advantages of POKS, namely the issue of integrating concepts into its structure. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aBayesian Student Model10acomputer adaptive testing10ahidden nodes10aItem Response Theory1 aDesmarais, M C1 aPu, X uhttp://www.iacat.org/content/bayesian-student-model-without-hidden-nodes-and-its-comparison-item-response-theory00534nas a2200133 4500008003900000245010500039210006900144300001200213490000700225100001700232700001600249700001500265856012000280 2005 d00aA closer look at using judgments of item difficulty to change answers on computerized adaptive tests0 acloser look at using judgments of item difficulty to change answ a331-3500 v421 aVispoel, W P1 aClough, S J1 aBleiler, T uhttp://www.iacat.org/content/closer-look-using-judgments-item-difficulty-change-answers-computerized-adaptive-tests00519nam a2200097 4500008004100000245009600041210006900137260008000206100002400286856011100310 2005 eng d00aA comparison of adaptive mastery testing using testlets with the 3-parameter logistic model0 acomparison of adaptive mastery testing using testlets with the 3 aUnpublished doctoral dissertation, University of Minnesota, Minneapolis, MN1 aJacobs-Cassuto, M S uhttp://www.iacat.org/content/comparison-adaptive-mastery-testing-using-testlets-3-parameter-logistic-model02152nas a2200229 4500008004100000020002200041245008700063210006900150260004100219300001200260490000700272520135500279653002101634653001501655653002401670653002601694653002501720653002101745653003101766100002301797856010201820 2005 eng d a0022-0655 (Print)00aA comparison of item-selection methods for adaptive tests with content constraints0 acomparison of itemselection methods for adaptive tests with cont bBlackwell Publishing: United Kingdom a283-3020 v423 aIn test assembly, a fundamental difference exists between algorithms that select a test sequentially or simultaneously. Sequential assembly allows us to optimize an objective function at the examinee's ability estimate, such as the test information function in computerized adaptive testing. But it leads to the non-trivial problem of how to realize a set of content constraints on the test—a problem more naturally solved by a simultaneous item-selection method. Three main item-selection methods in adaptive testing offer solutions to this dilemma. The spiraling method moves item selection across categories of items in the pool proportionally to the numbers needed from them. Item selection by the weighted-deviations method (WDM) and the shadow test approach (STA) is based on projections of the future consequences of selecting an item. These two methods differ in that the former calculates a projection of a weighted sum of the attributes of the eventual test and the latter a projection of the test itself. The pros and cons of these methods are analyzed. An empirical comparison between the WDM and STA was conducted for an adaptive version of the Law School Admission Test (LSAT), which showed equally good item-exposure rates but violations of some of the constraints and larger bias and inaccuracy of the ability estimator for the WDM.10aAdaptive Testing10aAlgorithms10acontent constraints10aitem selection method10ashadow test approach10aspiraling method10aweighted deviations method1 avan der Linden, WJ uhttp://www.iacat.org/content/comparison-item-selection-methods-adaptive-tests-content-constraints00453nas a2200109 4500008004100000245008700041210006900128300001200197490000700209100002300216856010400239 2005 eng d00aA comparison of item-selection methods for adaptive tests with content constraints0 acomparison of itemselection methods for adaptive tests with cont a283-3020 v421 avan der Linden, WJ uhttp://www.iacat.org/content/comparison-item-selection-methods-adaptive-tests-content-constraints-000305nas a2200109 4500008004100000245003000041210003000071300001100101490000600112100001600118856006100134 2005 eng d00aComputer adaptive testing0 aComputer adaptive testing a109-270 v61 aGershon, RC uhttp://www.iacat.org/content/computer-adaptive-testing-001605nas a2200253 4500008004100000020002200041245003000063210003000093250001500123300001100138490000600149520095200155653001401107653002501121653002901146653001801175653001901193653001101212653001401223653001901237653002001256100001601276856005901292 2005 eng d a1529-7713 (Print)00aComputer adaptive testing0 aComputer adaptive testing a2005/02/11 a109-270 v63 aThe creation of item response theory (IRT) and Rasch models, inexpensive accessibility to high speed desktop computers, and the growth of the Internet, has led to the creation and growth of computerized adaptive testing or CAT. This form of assessment is applicable for both high stakes tests such as certification or licensure exams, as well as health related quality of life surveys. This article discusses the historical background of CAT including its many advantages over conventional (typically paper and pencil) alternatives. The process of CAT is then described including descriptions of the specific differences of using CAT based upon 1-, 2- and 3-parameter IRT and various Rasch models. Numerous specific topics describing CAT in practice are described including: initial item selection, content balancing, test difficulty, test length and stopping rules. The article concludes with the author's reflections regarding the future of CAT.10a*Internet10a*Models, Statistical10a*User-Computer Interface10aCertification10aHealth Surveys10aHumans10aLicensure10aMicrocomputers10aQuality of Life1 aGershon, RC uhttp://www.iacat.org/content/computer-adaptive-testing02791nas a2200469 4500008004100000020002200041245010400063210006900167250001500236260000800251300001200259490000700271520132800278653002201606653003101628653001501659653001601674653001001690653003401700653002101734653002401755653002501779653001501804653001101819653005301830653002901883653001101912653001101923653002001934653000901954653003101963653004601994653003102040653001402071653003202085100001502117700001002132700002502142700001702167700001302184856012402197 2005 eng d a0012-1622 (Print)00aA computer adaptive testing approach for assessing physical functioning in children and adolescents0 acomputer adaptive testing approach for assessing physical functi a2005/02/15 cFeb a113-1200 v473 aThe purpose of this article is to demonstrate: (1) the accuracy and (2) the reduction in amount of time and effort in assessing physical functioning (self-care and mobility domains) of children and adolescents using computer-adaptive testing (CAT). A CAT algorithm selects questions directly tailored to the child's ability level, based on previous responses. Using a CAT algorithm, a simulation study was used to determine the number of items necessary to approximate the score of a full-length assessment. We built simulated CAT (5-, 10-, 15-, and 20-item versions) for self-care and mobility domains and tested their accuracy in a normative sample (n=373; 190 males, 183 females; mean age 6y 11mo [SD 4y 2m], range 4mo to 14y 11mo) and a sample of children and adolescents with Pompe disease (n=26; 21 males, 5 females; mean age 6y 1mo [SD 3y 10mo], range 5mo to 14y 10mo). Results indicated that comparable score estimates (based on computer simulations) to the full-length tests can be achieved in a 20-item CAT version for all age ranges and for normative and clinical samples. No more than 13 to 16% of the items in the full-length tests were needed for any one administration. These results support further consideration of using CAT programs for accurate and efficient clinical assessments of physical functioning.10a*Computer Systems10aActivities of Daily Living10aAdolescent10aAge Factors10aChild10aChild Development/*physiology10aChild, Preschool10aComputer Simulation10aConfidence Intervals10aDemography10aFemale10aGlycogen Storage Disease Type II/physiopathology10aHealth Status Indicators10aHumans10aInfant10aInfant, Newborn10aMale10aMotor Activity/*physiology10aOutcome Assessment (Health Care)/*methods10aReproducibility of Results10aSelf Care10aSensitivity and Specificity1 aHaley, S M1 aNi, P1 aFragala-Pinkham, M A1 aSkrinar, A M1 aCorzo, D uhttp://www.iacat.org/content/computer-adaptive-testing-approach-assessing-physical-functioning-children-and-adolescents00512nas a2200097 4500008004100000245005100041210005100092260017200143100001900315856008000334 2005 eng d00aComputer adaptive testing quality requirements0 aComputer adaptive testing quality requirements aProceedings E-Learn 2005 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 288-295, Vancouver, Canada, AACE, October 2005.1 aEconomides, AA uhttp://www.iacat.org/content/computer-adaptive-testing-quality-requirements02352nas a2200193 4500008004100000245008700041210006900128300001200197490000700209520170500216653003001921653002201951653001401973653002801987653001302015100001002028700001302038856010702051 2005 eng d00aA computer-assisted test design and diagnosis system for use by classroom teachers0 acomputerassisted test design and diagnosis system for use by cla a419-4290 v213 aComputer-assisted assessment (CAA) has become increasingly important in education in recent years. A variety of computer software systems have been developed to help assess the performance of students at various levels. However, such systems are primarily designed to provide objective assessment of students and analysis of test items, and focus has been mainly placed on higher and further education. Although there are commercial professional systems available for use by primary and secondary educational institutions, such systems are generally expensive and require skilled expertise to operate. In view of the rapid progress made in the use of computer-based assessment for primary and secondary students by education authorities here in the UK and elsewhere, there is a need to develop systems which are economic and easy to use and can provide the necessary information that can help teachers improve students' performance. This paper presents the development of a software system that provides a range of functions including generating items and building item banks, designing tests, conducting tests on computers and analysing test results. Specifically, the system can generate information on the performance of students and test items that can be easily used to identify curriculum areas where students are under performing. A case study based on data collected from five secondary schools in Hong Kong involved in the Curriculum, Evaluation and Management Centre's Middle Years Information System Project, Durham University, UK, has been undertaken to demonstrate the use of the system for diagnostic and performance analysis. (PsycINFO Database Record (c) 2006 APA ) (journal abstract)10aComputer Assisted Testing10aComputer Software10aDiagnosis10aEducational Measurement10aTeachers1 aHe, Q1 aTymms, P uhttp://www.iacat.org/content/computer-assisted-test-design-and-diagnosis-system-use-classroom-teachers02219nas a2200241 4500008004100000020004100041245009600082210006900178250001500247260000800262300001100270490000700281520139600288653002701684653003701711653002701748653001101775653002601786100001501812700001901827700001301846856011801859 2005 eng d a0007-1102 (Print)0007-1102 (Linking)00aComputerized adaptive testing: a mixture item selection approach for constrained situations0 aComputerized adaptive testing a mixture item selection approach  a2005/11/19 cNov a239-570 v583 aIn computerized adaptive testing (CAT), traditionally the most discriminating items are selected to provide the maximum information so as to attain the highest efficiency in trait (theta) estimation. The maximum information (MI) approach typically results in unbalanced item exposure and hence high item-overlap rates across examinees. Recently, Yi and Chang (2003) proposed the multiple stratification (MS) method to remedy the shortcomings of MI. In MS, items are first sorted according to content, then difficulty and finally discrimination parameters. As discriminating items are used strategically, MS offers a better utilization of the entire item pool. However, for testing with imposed non-statistical constraints, this new stratification approach may not maintain its high efficiency. Through a series of simulation studies, this research explored the possible benefits of a mixture item selection approach (MS-MI), integrating the MS and MI approaches, in testing with non-statistical constraints. In all simulation conditions, MS consistently outperformed the other two competing approaches in item pool utilization, while the MS-MI and the MI approaches yielded higher measurement efficiency and offered better conformity to the constraints. Furthermore, the MS-MI approach was shown to perform better than MI on all evaluation criteria when control of item exposure was imposed.10a*Computer-Aided Design10a*Educational Measurement/methods10a*Models, Psychological10aHumans10aPsychometrics/methods1 aLeung, C K1 aChang, Hua-Hua1 aHau, K T uhttp://www.iacat.org/content/computerized-adaptive-testing-mixture-item-selection-approach-constrained-situations00541nas a2200121 4500008004100000020001400041245014400055210006900199300001200268490000700280100001500287856011700302 2005 eng d a0146-621600aComputerized adaptive testing with the partial credit model: Estimation procedures, population distributions, and item pool characteristics0 aComputerized adaptive testing with the partial credit model Esti a433-4560 v291 aGorin, J S uhttp://www.iacat.org/content/computerized-adaptive-testing-partial-credit-model-estimation-procedures-population01564nas a2200157 4500008003900000245014400039210006900183300001200252490000700264520099200271100002101263700002101284700002701305700002101332856005301353 2005 d00aComputerized Adaptive Testing With the Partial Credit Model: Estimation Procedures, Population Distributions, and Item Pool Characteristics0 aComputerized Adaptive Testing With the Partial Credit Model Esti a433-4560 v293 a

The primary purpose of this research is to examine the impact of estimation methods, actual latent trait distributions, and item pool characteristics on the performance of a simulated computerized adaptive testing (CAT) system. In this study, three estimation procedures are compared for accuracy of estimation: maximum likelihood estimation (MLE), expected a priori (EAP), and Warm's weighted likelihood estimation (WLE). Some research has shown that MLE and EAP perform equally well under certain conditions in polytomous CAT systems, such that they match the actual latent trait distribution. However, little research has compared these methods when prior estimates of. distributions are extremely poor. In general, it appears that MLE, EAP, and WLE procedures perform equally well when using an optimal item pool. However, the use of EAP procedures may be advantageous under nonoptimal testing conditions when the item pool is not appropriately matched to the examinees.

1 aGorin, Joanna, S1 aDodd, Barbara, G1 aFitzpatrick, Steven, J1 aShieh, Yann Yann uhttp://apm.sagepub.com/content/29/6/433.abstract00601nas a2200145 4500008004100000245014400041210006900185300001200254490000700266100001300273700001400286700002100300700001500321856011900336 2005 eng d00aComputerized adaptive testing with the partial credit model: Estimation procedures, population distributions, and item pool characteristics0 aComputerized adaptive testing with the partial credit model Esti a533-5460 v291 aGorin, J1 aDodd, B G1 aFitzpatrick, S J1 aShieh, Y Y uhttp://www.iacat.org/content/computerized-adaptive-testing-partial-credit-model-estimation-procedures-population-000685nas a2200121 4500008004100000245017000041210006900211260011000280100001800390700002000408700001600428856011900444 2005 eng d00aComputerizing statewide assessments in Minnesota: A report on the feasibility of converting the Minnesota Comprehensive Assessments to a computerized adaptive format0 aComputerizing statewide assessments in Minnesota A report on the bOffice of Educational Accountability, College of Education and Human Development, University of Minnesota1 aPeterson, K A1 aL., Davison., M1 aHjelseth, L uhttp://www.iacat.org/content/computerizing-statewide-assessments-minnesota-report-feasibility-converting-minnesota00515nas a2200109 4500008004100000245008200041210006900123260006700192100002300259700001800282856010500300 2005 eng d00aConstraining item exposure in computerized adaptive testing with shadow tests0 aConstraining item exposure in computerized adaptive testing with aLaw School Admission Council Computerized Testing Report 02-031 avan der Linden, WJ1 aVeldkamp, B P uhttp://www.iacat.org/content/constraining-item-exposure-computerized-adaptive-testing-shadow-tests-100447nas a2200121 4500008003900000245009000039210006900129300001200198490000700210100002200217700002000239856006600259 2005 d00aConstructing a Computerized Adaptive Test for University Applicants With Disabilities0 aConstructing a Computerized Adaptive Test for University Applica a381-4050 v181 aMoshinsky, Avital1 aKazin, Cathrael uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1804_302123nas a2200253 4500008004100000245007900041210006900120300001200189490000700201520113300208653002701341653004601368653005201414653002901466653001101495653005601506653002501562653004101587653004501628653006201673100001501735700001501750856010401765 2005 eng d00aContemporary measurement techniques for rehabilitation outcomes assessment0 aContemporary measurement techniques for rehabilitation outcomes  a339-3450 v373 aIn this article, we review the limitations of traditional rehabilitation functional outcome instruments currently in use within the rehabilitation field to assess Activity and Participation domains as defined by the International Classification of Function, Disability, and Health. These include a narrow scope of functional outcomes, data incompatibility across instruments, and the precision vs feasibility dilemma. Following this, we illustrate how contemporary measurement techniques, such as item response theory methods combined with computer adaptive testing methodology, can be applied in rehabilitation to design functional outcome instruments that are comprehensive in scope, accurate, allow for compatibility across instruments, and are sensitive to clinically important change without sacrificing their feasibility. Finally, we present some of the pressing challenges that need to be overcome to provide effective dissemination and training assistance to ensure that current and future generations of rehabilitation professionals are familiar with and skilled in the application of contemporary outcomes measurement.10a*Disability Evaluation10aActivities of Daily Living/classification10aDisabled Persons/classification/*rehabilitation10aHealth Status Indicators10aHumans10aOutcome Assessment (Health Care)/*methods/standards10aRecovery of Function10aResearch Support, N.I.H., Extramural10aResearch Support, U.S. Gov't, Non-P.H.S.10aSensitivity and Specificity computerized adaptive testing1 aJette, A M1 aHaley, S M uhttp://www.iacat.org/content/contemporary-measurement-techniques-rehabilitation-outcomes-assessment00471nas a2200121 4500008004100000245008000041210006900121300001400190490001000204100001400214700001300228856010800241 2005 eng d00aControlling item exposure and test overlap in computerized adaptive testing0 aControlling item exposure and test overlap in computerized adapt a204–2170 v29(2)1 aChen, S Y1 aLei, P W uhttp://www.iacat.org/content/controlling-item-exposure-and-test-overlap-computerized-adaptive-testing-001320nas a2200133 4500008003900000245008000039210006900119300001200188490000700200520089100207100001901098700001601117856005301133 2005 d00aControlling Item Exposure and Test Overlap in Computerized Adaptive Testing0 aControlling Item Exposure and Test Overlap in Computerized Adapt a204-2170 v293 a

This article proposes an item exposure control method, which is the extension of the Sympson and Hetter procedure and can provide item exposure control at both the item and test levels. Item exposure rate and test overlap rate are two indices commonly used to track item exposure in computerized adaptive tests. By considering both indices, item exposure can be monitored at both the item and test levels. To control the item exposure rate and test overlap rate simultaneously, the modified procedure attempted to control not only the maximum value but also the variance of item exposure rates. Results indicated that the item exposure rate and test overlap rate could be controlled simultaneously by implementing the modified procedure. Item exposure control was improved and precision of trait estimation decreased when a prespecified maximum test overlap rate was stringent.

1 aChen, Shu-Ying1 aLei, Pui-Wa uhttp://apm.sagepub.com/content/29/3/204.abstract01559nas a2200169 4500008004100000245008000041210006900121300001200190490000700202520094200209653002101151653003001172653005401202100001401256700001301270856010601283 2005 eng d00aControlling item exposure and test overlap in computerized adaptive testing0 aControlling item exposure and test overlap in computerized adapt a204-2170 v293 aThis article proposes an item exposure control method, which is the extension of the Sympson and Hetter procedure and can provide item exposure control at both the item and test levels. Item exposure rate and test overlap rate are two indices commonly used to track item exposure in computerized adaptive tests. By considering both indices, item exposure can be monitored at both the item and test levels. To control the item exposure rate and test overlap rate simultaneously, the modified procedure attempted to control not only the maximum value but also the variance of item exposure rates. Results indicated that the item exposure rate and test overlap rate could be controlled simultaneously by implementing the modified procedure. Item exposure control was improved and precision of trait estimation decreased when a prespecified maximum test overlap rate was stringent. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aItem Content (Test) computerized adaptive testing1 aChen, S-Y1 aLei, P-W uhttp://www.iacat.org/content/controlling-item-exposure-and-test-overlap-computerized-adaptive-testing02214nas a2200373 4500008004100000245011500041210006900156300001100225490000700236520104400243653002101287653002001308653001001328653000901338653002801347653001101375653003801386653000901424653001601433653004101449653001801490653003701508653003001545100001401575700001301589700001301602700001501615700001701630700001501647700001901662700001601681700001801697856012501715 2005 eng d00aData pooling and analysis to build a preliminary item bank: an example using bowel function in prostate cancer0 aData pooling and analysis to build a preliminary item bank an ex a142-590 v283 aAssessing bowel function (BF) in prostate cancer can help determine therapeutic trade-offs. We determined the components of BF commonly assessed in prostate cancer studies as an initial step in creating an item bank for clinical and research application. We analyzed six archived data sets representing 4,246 men with prostate cancer. Thirty-one items from validated instruments were available for analysis. Items were classified into domains (diarrhea, rectal urgency, pain, bleeding, bother/distress, and other) then subjected to conventional psychometric and item response theory (IRT) analyses. Items fit the IRT model if the ratio between observed and expected item variance was between 0.60 and 1.40. Four of 31 items had inadequate fit in at least one analysis. Poorly fitting items included bleeding (2), rectal urgency (1), and bother/distress (1). A fifth item assessing hemorrhoids was poorly correlated with other items. Our analyses supported four related components of BF: diarrhea, rectal urgency, pain, and bother/distress.10a*Quality of Life10a*Questionnaires10aAdult10aAged10aData Collection/methods10aHumans10aIntestine, Large/*physiopathology10aMale10aMiddle Aged10aProstatic Neoplasms/*physiopathology10aPsychometrics10aResearch Support, Non-U.S. Gov't10aStatistics, Nonparametric1 aEton, D T1 aLai, J S1 aCella, D1 aReeve, B B1 aTalcott, J A1 aClark, J A1 aMcPherson, C P1 aLitwin, M S1 aMoinpour, C M uhttp://www.iacat.org/content/data-pooling-and-analysis-build-preliminary-item-bank-example-using-bowel-function-prostate00498nas a2200121 4500008004100000245010000041210006900141300001200210490001000222100000700232700001400239856012300253 2005 eng d00aDesign and evaluation of an XML-based platform-independent computerized adaptive testing system0 aDesign and evaluation of an XMLbased platformindependent compute a230-2370 v48(2)1 aHo1 aYen, Y -C uhttp://www.iacat.org/content/design-and-evaluation-xml-based-platform-independent-computerized-adaptive-testing-system00537nas a2200169 4500008004100000245006700041210006300108300001600171490000700187100001400194700001400208700001600222700001700238700001500255700001200270856008500282 2005 eng d00aDevelopment of a computer-adaptive test for depression (D-CAT)0 aDevelopment of a computeradaptive test for depression DCAT a2277–22910 v141 aFliege, H1 aBecker, J1 aWalter, O B1 aBjorner, J B1 aKlapp, B F1 aRose, M uhttp://www.iacat.org/content/development-computer-adaptive-test-depression-d-cat00627nas a2200109 4500008004100000245009500041210006900136260016800205100001800373700001900391856010700410 2005 eng d00aThe development of the adaptive item language assessment (AILA) for mixed-ability students0 adevelopment of the adaptive item language assessment AILA for mi aProceedings E-Learn 2005 World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 643-650, Vancouver, Canada, AACE, October 2005.1 aGiouroglou, H1 aEconomides, AA uhttp://www.iacat.org/content/development-adaptive-item-language-assessment-aila-mixed-ability-students02000nas a2200205 4500008004100000020004600041245007900087210006900166260004100235300001400276490000700290520127200297653003001569653002501599653003401624100001301658700001801671700001601689856008901705 2005 eng d a0017-9124 (Print); 1475-6773 (Electronic)00aDynamic assessment of health outcomes: Time to let the CAT out of the bag?0 aDynamic assessment of health outcomes Time to let the CAT out of bBlackwell Publishing: United Kingdom a1694-17110 v403 aBackground: The use of item response theory (IRT) to measure self-reported outcomes has burgeoned in recent years. Perhaps the most important application of IRT is computer-adaptive testing (CAT), a measurement approach in which the selection of items is tailored for each respondent. Objective. To provide an introduction to the use of CAT in the measurement of health outcomes, describe several IRT models that can be used as the basis of CAT, and discuss practical issues associated with the use of adaptive scaling in research settings. Principal Points: The development of a CAT requires several steps that are not required in the development of a traditional measure including identification of "starting" and "stopping" rules. CAT's most attractive advantage is its efficiency. Greater measurement precision can be achieved with fewer items. Disadvantages of CAT include the high cost and level of technical expertise required to develop a CAT. Conclusions: Researchers, clinicians, and patients benefit from the availability of psychometrically rigorous measures that are not burdensome. CAT outcome measures hold substantial promise in this regard, but their development is not without challenges. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputer adaptive testing10aItem Response Theory10aself reported health outcomes1 aCook, KF1 aO'Malley, K J1 aRoddey, T S uhttp://www.iacat.org/content/dynamic-assessment-health-outcomes-time-let-cat-out-bag00463nas a2200109 4500008004100000245008400041210006900125260003000194100001300224700001300237856010300250 2005 eng d00aThe effectiveness of using multiple item pools in computerized adaptive testing0 aeffectiveness of using multiple item pools in computerized adapt aMontreal, Canadac04/20051 aZhang, J1 aChang, H uhttp://www.iacat.org/content/effectiveness-using-multiple-item-pools-computerized-adaptive-testing00595nas a2200109 4500008004100000245014100041210006900182260008300251100001500334700001500349856012100364 2005 eng d00aFeatures of the estimated sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules0 aFeatures of the estimated sampling distribution of the ability e aD. G. Englehard (Eds.), Objective measurement: Theory into practice. Volume 6.1 aBlais, J-G1 aRaîche, G uhttp://www.iacat.org/content/features-estimated-sampling-distribution-ability-estimate-computerized-adaptive-testing00452nas a2200121 4500008004100000245006700041210006700108260002100175100001000196700001300206700001900219856009200238 2005 eng d00aIdentifying practical indices for enhancing item pool security0 aIdentifying practical indices for enhancing item pool security aMontreal, Canada1 aYi, Q1 aZhang, J1 aChang, Hua-Hua uhttp://www.iacat.org/content/identifying-practical-indices-enhancing-item-pool-security00649nas a2200109 4500008004100000245010000041210006900141260017200210100001800382700001900400856012000419 2005 eng d00aAn implemented theoretical framework for a common European foreign language adaptive assessment0 aimplemented theoretical framework for a common European foreign  aProceedings ICODL 2005, 3rd ternational Conference on Open and Distance Learning 'Applications of Pedagogy and Technology',339-350,Greek Open University, Patra, Greece1 aGiouroglou, H1 aEconomides, AA uhttp://www.iacat.org/content/implemented-theoretical-framework-common-european-foreign-language-adaptive-assessment00553nas a2200109 4500008004100000245010300041210006900144260006800213100002300281700001900304856012000323 2005 eng d00aImplementing content constraints in alpha-stratified adaptive testing using a shadow test approach0 aImplementing content constraints in alphastratified adaptive tes aLaw School Admission Council, Computerized Testing Report 01-091 avan der Linden, WJ1 aChang, Hua-Hua uhttp://www.iacat.org/content/implementing-content-constraints-alpha-stratified-adaptive-testing-using-shadow-test-002241nas a2200217 4500008004100000020002200041245014200063210006900205260004100274300001200315490000700327520142600334653001401760653003401774653002301808653001601831653002701847100001201874700001701886856012001903 2005 eng d a0022-0655 (Print)00aIncreasing the homogeneity of CAT's item-exposure rates by minimizing or maximizing varied target functions while assembling shadow tests0 aIncreasing the homogeneity of CATs itemexposure rates by minimiz bBlackwell Publishing: United Kingdom a245-2690 v423 aA computerized adaptive testing (CAT) algorithm that has the potential to increase the homogeneity of CATs item-exposure rates without significantly sacrificing the precision of ability estimates was proposed and assessed in the shadow-test (van der Linden & Reese, 1998) CAT context. This CAT algorithm was formed by a combination of maximizing or minimizing varied target functions while assembling shadow tests. There were four target functions to be separately used in the first, second, third, and fourth quarter test of CAT. The elements to be used in the four functions were associated with (a) a random number assigned to each item, (b) the absolute difference between an examinee's current ability estimate and an item difficulty, (c) the absolute difference between an examinee's current ability estimate and an optimum item difficulty, and (d) item information. The results indicated that this combined CAT fully utilized all the items in the pool, reduced the maximum exposure rates, and achieved more homogeneous exposure rates. Moreover, its precision in recovering ability estimates was similar to that of the maximum item-information method. The combined CAT method resulted in the best overall results compared with the other individual CAT item-selection methods. The findings from the combined CAT are encouraging. Future uses are discussed. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aalgorithm10acomputerized adaptive testing10aitem exposure rate10ashadow test10avaried target function1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/increasing-homogeneity-cats-item-exposure-rates-minimizing-or-maximizing-varied-target02020nas a2200193 4500008004100000245009300041210006900134300001200203490000700215520136400222653001501586653002401601653001101625653002201636100001801658700001801676700001901694856011301713 2005 eng d00aInfeasibility in automated test assembly models: A comparison study of different methods0 aInfeasibility in automated test assembly models A comparison stu a223-2430 v423 aSeveral techniques exist to automatically put together a test meeting a number of specifications. In an item bank, the items are stored with their characteristics. A test is constructed by selecting a set of items that fulfills the specifications set by the test assembler. Test assembly problems are often formulated in terms of a model consisting of restrictions and an objective to be maximized or minimized. A problem arises when it is impossible to construct a test from the item pool that meets all specifications, that is, when the model is not feasible. Several methods exist to handle these infeasibility problems. In this article, test assembly models resulting from two practical testing programs were reconstructed to be infeasible. These models were analyzed using methods that forced a solution (Goal Programming, Multiple-Goal Programming, Greedy Heuristic), that analyzed the causes (Relaxed and Ordered Deletion Algorithm (RODA), Integer Randomized Deletion Algorithm (IRDA), Set Covering (SC), and Item Sampling), or that analyzed the causes and used this information to force a solution (Irreducible Infeasible Set-Solver). Specialized methods such as the IRDA and the Irreducible Infeasible Set-Solver performed best. Recommendations about the use of different methods are given. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAlgorithms10aItem Content (Test)10aModels10aTest Construction1 aHuitzing, H A1 aVeldkamp, B P1 aVerschoor, A J uhttp://www.iacat.org/content/infeasibility-automated-test-assembly-models-comparison-study-different-methods02443nas a2200373 4500008004100000020004100041245008200082210006900164250001500233260000800248300001000256490000700266520136700273653001001640653000901650653002201659653003301681653003301714653001101747653001101758653000901769653001601778653004001794653001801834653001901852100001301871700001301884700001401897700001201911700001701923700001601940700001501956856009801971 2005 eng d a0895-4356 (Print)0895-4356 (Linking)00aAn item bank was created to improve the measurement of cancer-related fatigue0 aitem bank was created to improve the measurement of cancerrelate a2005/02/01 cFeb a190-70 v583 aOBJECTIVE: Cancer-related fatigue (CRF) is one of the most common unrelieved symptoms experienced by patients. CRF is underrecognized and undertreated due to a lack of clinically sensitive instruments that integrate easily into clinics. Modern computerized adaptive testing (CAT) can overcome these obstacles by enabling precise assessment of fatigue without requiring the administration of a large number of questions. A working item bank is essential for development of a CAT platform. The present report describes the building of an operational item bank for use in clinical settings with the ultimate goal of improving CRF identification and treatment. STUDY DESIGN AND SETTING: The sample included 301 cancer patients. Psychometric properties of items were examined by using Rasch analysis, an Item Response Theory (IRT) model. RESULTS AND CONCLUSION: The final bank includes 72 items. These 72 unidimensional items explained 57.5% of the variance, based on factor analysis results. Excellent internal consistency (alpha=0.99) and acceptable item-total correlation were found (range: 0.51-0.85). The 72 items covered a reasonable range of the fatigue continuum. No significant ceiling effects, floor effects, or gaps were found. A sample short form was created for demonstration purposes. The resulting bank is amenable to the development of a CAT platform.10aAdult10aAged10aAged, 80 and over10aFactor Analysis, Statistical10aFatigue/*etiology/psychology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/*complications/psychology10aPsychometrics10aQuestionnaires1 aLai, J-S1 aCella, D1 aDineen, K1 aBode, R1 aVon Roenn, J1 aGershon, RC1 aShevrin, D uhttp://www.iacat.org/content/item-bank-was-created-improve-measurement-cancer-related-fatigue01315nas a2200229 4500008004100000020002200041245007700063210006900140260002500209300001200234490000700246520057900253653002700832653003000859653002500889100001100914700001600925700001500941700001300956700001500969856010100984 2005 eng d a0439-755X (Print)00a[Item characteristic curve equating under graded response models in IRT]0 aItem characteristic curve equating under graded response models  bScience Press: China a832-8380 v373 aIn one of the largest qualificatory tests--economist test, to guarantee the comparability among different years, construct item bank and prepare for computerized adaptive testing, item characteristic curve equating and anchor test equating design under graded models in IRT are used, which have realized the item and ability parameter equating of test data in five years and succeeded in establishing an item bank. Based on it, cut scores of different years are compared by equating and provide demonstrational gist to constitute the eligibility standard of economist test. 10agraded response models10aitem characteristic curve10aItem Response Theory1 aJun, Z1 aDongming, O1 aShuyuan, X1 aHaiqi, D1 aShuqing, Q uhttp://www.iacat.org/content/item-characteristic-curve-equating-under-graded-response-models-irt00559nas a2200145 4500008003900000245011100039210006900150300001000219490000700229100001400236700001400250700001800264700001700282856011400299 2005 d00aItem response theory in computer adaptive testing: implications for outcomes measurement in rehabilitation0 aItem response theory in computer adaptive testing implications f a71-780 v501 aWare, J E1 aGandek, B1 aSinclair, S J1 aBjorner, J B uhttp://www.iacat.org/content/item-response-theory-computer-adaptive-testing-implications-outcomes-measurement01743nas a2200229 4500008004100000245008300041210006900124300001100193490000700204520103000211653003401241100001301275700001401288700001501302700001701317700001501334700001501349700001401364700001301378700001301391856010901404 2005 eng d00aAn item response theory-based pain item bank can enhance measurement precision0 aitem response theorybased pain item bank can enhance measurement a278-880 v303 aCancer-related pain is often under-recognized and undertreated. This is partly due to the lack of appropriate assessments, which need to be comprehensive and precise yet easily integrated into clinics. Computerized adaptive testing (CAT) can enable precise-yet-brief assessments by only selecting the most informative items from a calibrated item bank. The purpose of this study was to create such a bank. The sample included 400 cancer patients who were asked to complete 61 pain-related items. Data were analyzed using factor analysis and the Rasch model. The final bank consisted of 43 items which satisfied the measurement requirement of factor analysis and the Rasch model, demonstrated high internal consistency and reasonable item-total correlations, and discriminated patients with differing degrees of pain. We conclude that this bank demonstrates good psychometric properties, is sensitive to pain reported by patients, and can be used as the foundation for a CAT pain-testing platform for use in clinical practice.10acomputerized adaptive testing1 aLai, J-S1 aDineen, K1 aReeve, B B1 aVon Roenn, J1 aShervin, D1 aMcGuire, M1 aBode, R K1 aPaice, J1 aCella, D uhttp://www.iacat.org/content/item-response-theory-based-pain-item-bank-can-enhance-measurement-precision02300nas a2200205 4500008004100000245009000041210007100131300000900202490000700211520161900218653002001837653001601857653001801873653002201891653001601913653001501929653001801944100001401962856011801976 2005 eng d00aLa Validez desde una óptica psicométrica [Validity from a psychometric perspective]0 aLa Validez desde una óptica psicométrica Validity from a psychom a9-200 v133 aEl estudio de la validez constituye el eje central de los análisis psicométricos de los instrumentos de medida. En esta comunicación se traza una breve nota histórica de los distintos modos de concebir la validez a lo largo de los tiempos, se comentan las líneas actuales, y se tratan de vislumbrar posibles vías futuras, teniendo en cuenta el impacto que las nuevas tecnologías informáticas están ejerciendo sobre los propios instrumentos de medida en Psicología y Educación. Cuestiones como los nuevos formatos multimedia de los ítems, la evaluación a distancia, el uso intercultural de las pruebas, las consecuencias de su uso, o los tests adaptativos informatizados, reclaman nuevas formas de evaluar y conceptualizar la validez. También se analizan críticamente algunos planteamientos recientes sobre el concepto de validez. The study of validity constitutes a central axis of psychometric analyses of measurement instruments. This paper presents a historical sketch of different modes of conceiving validity, with commentary on current views, and it attempts to predict future lines of research by considering the impact of new computerized technologies on measurement instruments in psychology and education. Factors such as the new multimedia format of items, distance assessment, the intercultural use of tests, the consequences of the latter, or the development of computerized adaptive tests demand new ways of conceiving and evaluating validity. Some recent thoughts about the concept of validity are also critically analyzed. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aFactor Analysis10aMeasurement10aPsychometrics10aScaling (Testing)10aStatistical10aTechnology10aTest Validity1 aMuñiz, J uhttp://www.iacat.org/content/la-validez-desde-una-%C3%B3ptica-psicom%C3%A9trica-validity-psychometric-perspective02902nas a2200409 4500008004100000245012300041210006900164260000800233300001000241490000700251520159700258653004701855653001001902653000901912653001901921653003101940653002601971653001101997653002902008653001102037653000902048653001602057653003902073653001402112653002502126653002702151653003002178653003202208653002802240653002202268100001502290700001602305700001702321700001602338700001502354856012302369 2005 eng d00aMeasuring physical function in patients with complex medical and postsurgical conditions: a computer adaptive approach0 aMeasuring physical function in patients with complex medical and cOct a741-80 v843 aOBJECTIVE: To examine whether the range of disability in the medically complex and postsurgical populations receiving rehabilitation is adequately sampled by the new Activity Measure--Post-Acute Care (AM-PAC), and to assess whether computer adaptive testing (CAT) can derive valid patient scores using fewer questions. DESIGN: Observational study of 158 subjects (mean age 67.2 yrs) receiving skilled rehabilitation services in inpatient (acute rehabilitation hospitals, skilled nursing facility units) and community (home health services, outpatient departments) settings for recent-onset or worsening disability from medical (excluding neurological) and surgical (excluding orthopedic) conditions. Measures were interviewer-administered activity questions (all patients) and physical functioning portion of the SF-36 (outpatients) and standardized chart items (11 Functional Independence Measure (FIM), 19 Standardized Outcome and Assessment Information Set (OASIS) items, and 22 Minimum Data Set (MDS) items). Rasch modeling analyzed all data and the relationship between person ability estimates and average item difficulty. CAT assessed the ability to derive accurate patient scores using a sample of questions. RESULTS: The 163-item activity item pool covered the range of physical movement and personal and instrumental activities. CAT analysis showed comparable scores between estimates using 10 items or the total item pool. CONCLUSION: The AM-PAC can assess a broad range of function in patients with complex medical illness. CAT achieves valid patient scores using fewer questions.10aActivities of Daily Living/*classification10aAdult10aAged10aCohort Studies10aContinuity of Patient Care10aDisability Evaluation10aFemale10aHealth Services Research10aHumans10aMale10aMiddle Aged10aPostoperative Care/*rehabilitation10aPrognosis10aRecovery of Function10aRehabilitation Centers10aRehabilitation/*standards10aSensitivity and Specificity10aSickness Impact Profile10aTreatment Outcome1 aSiebens, H1 aAndres, P L1 aPengsheng, N1 aCoster, W J1 aHaley, S M uhttp://www.iacat.org/content/measuring-physical-function-patients-complex-medical-and-postsurgical-conditions-computer01198nas a2200133 4500008003900000245006700039210006700106300001200173490000700185520077300192100002100965700002500986856005301011 2005 d00aMonte Carlo Test Assembly for Item Pool Analysis and Extension0 aMonte Carlo Test Assembly for Item Pool Analysis and Extension a239-2610 v293 a

A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal chance of being built during an assembly. This allows the authors to address the following issues of pool analysis and extension: compare the strengths and weaknesses of different pools, identify the most restrictive constraint(s) for test assembly, and identify properties of the items that should be added to a pool to achieve greater usability of the pool. Computer experiments with operational pools are given.

1 aBelov, Dmitry, I1 aArmstrong, Ronald, D uhttp://apm.sagepub.com/content/29/4/239.abstract00382nas a2200097 4500008004100000245003300041210003300074260009900107100001900206856005900225 2005 eng d00aPersonalized feedback in CAT0 aPersonalized feedback in CAT aWSEAS Transactions on Advances in Engineering Education, Issue 3, Volume 2,174-181, July 2005.1 aEconomides, AA uhttp://www.iacat.org/content/personalized-feedback-cat01914nas a2200157 4500008004100000245010500041210006900146300001000215490000700225520132900232653003401561100001501595700001301610700001301623856012001636 2005 eng d00aThe promise of PROMIS: using item response theory to improve assessment of patient-reported outcomes0 apromise of PROMIS using item response theory to improve assessme aS53-70 v233 aPROMIS (Patient-Reported-Outcomes Measurement Information System) is an NIH Roadmap network project intended to improve the reliability, validity, and precision of PROs and to provide definitive new instruments that will exceed the capabilities of classic instruments and enable improved outcome measurement for clinical research across all NIH institutes. Item response theory (IRT) measurement models now permit us to transition conventional health status assessment into an era of item banking and computerized adaptive testing (CAT). Item banking uses IRT measurement models and methods to develop item banks from large pools of items from many available questionnaires. IRT allows the reduction and improvement of items and assembles domains of items which are unidimensional and not excessively redundant. CAT provides a model-driven algorithm and software to iteratively select the most informative remaining item in a domain until a desired degree of precision is obtained. Through these approaches the number of patients required for a clinical trial may be reduced while holding statistical power constant. PROMIS tools, expected to improve precision and enable assessment at the individual patient level which should broaden the appeal of PROs, will begin to be available to the general medical community in 2008.10acomputerized adaptive testing1 aFries, J F1 aBruce, B1 aCella, D uhttp://www.iacat.org/content/promise-promis-using-item-response-theory-improve-assessment-patient-reported-outcomes02854nas a2200241 4500008004100000245018600041210007000227300001200297490000700309520195000316653003002266653002502296653001802321653002502339653001802364653001802382653001102400100001402411700001502425700001902440700002002459856013302479 2005 eng d00aPropiedades psicométricas de un test Adaptativo Informatizado para la medición del ajuste emocional [Psychometric properties of an Emotional Adjustment Computerized Adaptive Test]0 aPropiedades psicométricas de un test Adaptativo Informatizado pa a484-4910 v173 aEn el presente trabajo se describen las propiedades psicométricas de un Test Adaptativo Informatizado para la medición del ajuste emocional de las personas. La revisión de la literatura acerca de la aplicación de los modelos de la teoría de la respuesta a los ítems (TRI) muestra que ésta se ha utilizado más en el trabajo con variables aptitudinales que para la medición de variables de personalidad, sin embargo diversos estudios han mostrado la eficacia de la TRI para la descripción psicométrica de dichasvariables. Aun así, pocos trabajos han explorado las características de un Test Adaptativo Informatizado, basado en la TRI, para la medición de una variable de personalidad como es el ajuste emocional. Nuestros resultados muestran la eficiencia del TAI para la evaluación del ajuste emocional, proporcionando una medición válida y precisa, utilizando menor número de elementos de medida encomparación con las escalas de ajuste emocional de instrumentos fuertemente implantados. Psychometric properties of an emotional adjustment computerized adaptive test. In the present work it was described the psychometric properties of an emotional adjustment computerized adaptive test. An examination of Item Response Theory (IRT) research literature indicates that IRT has been mainly used for assessing achievements and ability rather than personality factors. Nevertheless last years have shown several studies wich have successfully used IRT to personality assessment instruments. Even so, a few amount of works has inquired the computerized adaptative test features, based on IRT, for the measurement of a personality traits as it’s the emotional adjustment. Our results show the CAT efficiency for the emotional adjustment assessment so this provides a valid and accurate measurement; by using a less number of items in comparison with the emotional adjustment scales from the most strongly established questionnaires.10aComputer Assisted Testing10aEmotional Adjustment10aItem Response10aPersonality Measures10aPsychometrics10aTest Validity10aTheory1 aAguado, D1 aRubio, V J1 aHontangas, P M1 aHernández, J M uhttp://www.iacat.org/content/propiedades-psicom%C3%A9tricas-de-un-test-adaptativo-informatizado-para-la-medici%C3%B3n-del-ajuste01737nas a2200181 4500008004100000245014500041210006900186300001200255490000700267520104600274653003001320653002401350653001501374100001301389700001701402700002101419856011501440 2005 eng d00aA randomized experiment to compare conventional, computerized, and computerized adaptive administration of ordinal polytomous attitude items0 arandomized experiment to compare conventional computerized and c a159-1830 v293 aA total of 520 high school students were randomly assigned to a paper-and-pencil test (PPT), a computerized standard test (CST), or a computerized adaptive test (CAT) version of the Dutch School Attitude Questionnaire (SAQ), consisting of ordinal polytomous items. The CST administered items in the same order as the PPT. The CAT administered all items of three SAQ subscales in adaptive order using Samejima's graded response model, so that six different stopping rule settings could be applied afterwards. School marks were used as external criteria. Results showed significant but small multivariate administration mode effects on conventional raw scores and small to medium effects on maximum likelihood latent trait estimates. When the precision of CAT latent trait estimates decreased, correlations with grade point average in general decreased. However, the magnitude of the decrease was not very large as compared to the PPT, the CST, and the CAT without the stopping rule. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aComputer Assisted Testing10aTest Administration10aTest Items1 aHol, A M1 aVorst, H C M1 aMellenbergh, G J uhttp://www.iacat.org/content/randomized-experiment-compare-conventional-computerized-and-computerized-adaptive01542nas a2200145 4500008003900000245014500039210006900184300001200253490000700265520100100272100002001273700002301293700002701316856005301343 2005 d00aA Randomized Experiment to Compare Conventional, Computerized, and Computerized Adaptive Administration of Ordinal Polytomous Attitude Items0 aRandomized Experiment to Compare Conventional Computerized and C a159-1830 v293 a

A total of 520 high school students were randomly assigned to a paper-and-pencil test (PPT), a computerized standard test (CST), or a computerized adaptive test (CAT) version of the Dutch School Attitude Questionnaire (SAQ), consisting of ordinal polytomous items. The CST administered items in the same order as the PPT. The CAT administered all items of three SAQ subscales in adaptive order using Samejima’s graded response model, so that six different stopping rule settings could be applied afterwards. School marks were used as external criteria. Results showed significant but small multivariate administration mode effects on conventional raw scores and small to medium effects on maximum likelihood latent trait estimates. When the precision of CAT latent trait estimates decreased, correlations with grade point average in general decreased. However, the magnitude of the decrease was not very large as compared to the PPT, the CST, and the CAT without the stopping rule.

1 aHol, Michiel, A1 aVorst, Harrie, C M1 aMellenbergh, Gideon, J uhttp://apm.sagepub.com/content/29/3/159.abstract00511nas a2200157 4500008004100000020001000041245004300051210004300094260002600137653003000163653002800193653003400221653001700255100001200272856006900284 2005 eng d a05-0500aRecent trends in comparability studies0 aRecent trends in comparability studies bPearsoncAugust, 200510acomputer adaptive testing10aComputerized assessment10adifferential item functioning10aMode effects1 aPaek, P uhttp://www.iacat.org/content/recent-trends-comparability-studies00342nas a2200109 4500008004100000245004000041210004000081260002100121100001500142700001300157856006200170 2005 eng d00aRescuing CAT by fixing the problems0 aRescuing CAT by fixing the problems aMontreal, Canada1 aChang, S-H1 aZhang, J uhttp://www.iacat.org/content/rescuing-cat-fixing-problems02720nas a2200373 4500008004100000245017500041210006900216300001100285490000700296520137800303653003001681653003101711653001501742653001001757653000901767653002201776653003201798653004201830653001101872653003001883653001101913653005101924653003101975653003702006653000902043653001602052653004102068653004102109653002602150100001402176700001802190700001902208856011902227 2005 eng d00aSimulated computerized adaptive tests for measuring functional status were efficient with good discriminant validity in patients with hip, knee, or foot/ankle impairments0 aSimulated computerized adaptive tests for measuring functional s a629-380 v583 aBACKGROUND AND OBJECTIVE: To develop computerized adaptive tests (CATs) designed to assess lower extremity functional status (FS) in people with lower extremity impairments using items from the Lower Extremity Functional Scale and compare discriminant validity of FS measures generated using all items analyzed with a rating scale Item Response Theory model (theta(IRT)) and measures generated using the simulated CATs (theta(CAT)). METHODS: Secondary analysis of retrospective intake rehabilitation data. RESULTS: Unidimensionality of items was strong, and local independence of items was adequate. Differential item functioning (DIF) affected item calibration related to body part, that is, hip, knee, or foot/ankle, but DIF did not affect item calibration for symptom acuity, gender, age, or surgical history. Therefore, patients were separated into three body part specific groups. The rating scale model fit all three data sets well. Three body part specific CATs were developed: each was 70% more efficient than using all LEFS items to estimate FS measures. theta(IRT) and theta(CAT) measures discriminated patients by symptom acuity, age, and surgical history in similar ways. theta(CAT) measures were as precise as theta(IRT) measures. CONCLUSION: Body part-specific simulated CATs were efficient and produced precise measures of FS with good discriminant validity.10a*Health Status Indicators10aActivities of Daily Living10aAdolescent10aAdult10aAged10aAged, 80 and over10aAnkle Joint/physiopathology10aDiagnosis, Computer-Assisted/*methods10aFemale10aHip Joint/physiopathology10aHumans10aJoint Diseases/physiopathology/*rehabilitation10aKnee Joint/physiopathology10aLower Extremity/*physiopathology10aMale10aMiddle Aged10aResearch Support, N.I.H., Extramural10aResearch Support, U.S. Gov't, P.H.S.10aRetrospective Studies1 aHart, D L1 aMioduski, J E1 aStratford, P W uhttp://www.iacat.org/content/simulated-computerized-adaptive-tests-measuring-functional-status-were-efficient-good01476nas a2200193 4500008004100000245020200041210006900243300001200312490000700324520066400331653002100995653003001016653005501046653001101101653001801112100001401130700001701144856012101161 2005 eng d00aSomministrazione di test computerizzati di tipo adattivo: Un' applicazione del modello di misurazione di Rasch [Administration of computerized and adaptive tests: An application of the Rasch Model]0 aSomministrazione di test computerizzati di tipo adattivo Un appl a131-1490 v123 aThe aim of the present study is to describe the characteristics of a procedure for administering computerized and adaptive tests (Computer Adaptive Testing or CAT). Items to be asked to the individuals are interactively chosen and are selected from a "bank" in which they were previously calibrated and recorded on the basis of their difficulty level. The selection of items is performed by increasingly more accurate estimates of the examinees' ability. The building of an item-bank on Psychometrics and the implementation of this procedure allow a first validation through Monte Carlo simulations. (PsycINFO Database Record (c) 2006 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aItem Response Theory computerized adaptive testing10aModels10aPsychometrics1 aMiceli, R1 aMolinengo, G uhttp://www.iacat.org/content/somministrazione-di-test-computerizzati-di-tipo-adattivo-un-applicazione-del-modello-di00535nas a2200109 4500008004100000245010800041210006900149260005800218100001400276700001200290856012300302 2005 eng d00aStrategies for controlling item exposure in computerized adaptive testing with the partial credit model0 aStrategies for controlling item exposure in computerized adaptiv aPearson Educational Measurement Research Report 05-011 aDavis, LL1 aDodd, B uhttp://www.iacat.org/content/strategies-controlling-item-exposure-computerized-adaptive-testing-partial-credit-model-001472nas a2200217 4500008004100000245004600041210004600087300001200133490000700145520085100152653001801003653002501021653003201046653001301078653002201091653002401113653001501137100001601152700001501168856007101183 2005 eng d00aTest construction for cognitive diagnosis0 aTest construction for cognitive diagnosis a262-2770 v293 aAlthough cognitive diagnostic models (CDMs) can be useful in the analysis and interpretation of existing tests, little has been developed to specify how one might construct a good test using aspects of the CDMs. This article discusses the derivation of a general CDM index based on Kullback-Leibler information that will serve as a measure of how informative an item is for the classification of examinees. The effectiveness of the index is examined for items calibrated using the deterministic input noisy "and" gate model (DINA) and the reparameterized unified model (RUM) by implementing a simple heuristic to construct a test from an item bank. When compared to randomly constructed tests from the same item bank, the heuristic shows significant improvement in classification rates. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10a(Measurement)10aCognitive Assessment10aItem Analysis (Statistical)10aProfiles10aTest Construction10aTest Interpretation10aTest Items1 aHenson, R K1 aDouglas, J uhttp://www.iacat.org/content/test-construction-cognitive-diagnosis10201nas a2200553 4500008004100000245016300041210006900204300001400273490000700287520862500294653001808919653003208937100001608969700001608985700001409001700001609015700001409031700001509045700001609060700001409076700001509090700001509105700001409120700001709134700001709151700001709168700001609185700001709201700001609218700001509234700001609249700001709265700002309282700001609305700002209321700001609343700001609359700001709375700001309392700001509405700001309420700001609433700001209449700001409461700001609475700002009491700001209511856012409523 2005 eng d00aToward efficient and comprehensive measurement of the alcohol problems continuum in college students: The Brief Young Adult Alcohol Consequences Questionnaire0 aToward efficient and comprehensive measurement of the alcohol pr a1180-11890 v293 aBackground: Although a number of measures of alcohol problems in college students have been studied, the psychometric development and validation of these scales have been limited, for the most part, to methods based on classical test theory. In this study, we conducted analyses based on item response theory to select a set of items for measuring the alcohol problem severity continuum in college students that balances comprehensiveness and efficiency and is free from significant gender bias., Method: We conducted Rasch model analyses of responses to the 48-item Young Adult Alcohol Consequences Questionnaire by 164 male and 176 female college students who drank on at least a weekly basis. An iterative process using item fit statistics, item severities, item discrimination parameters, model residuals, and analysis of differential item functioning by gender was used to pare the items down to those that best fit a Rasch model and that were most efficient in discriminating among levels of alcohol problems in the sample., Results: The process of iterative Rasch model analyses resulted in a final 24-item scale with the data fitting the unidimensional Rasch model very well. The scale showed excellent distributional properties, had items adequately matched to the severity of alcohol problems in the sample, covered a full range of problem severity, and appeared highly efficient in retaining all of the meaningful variance captured by the original set of 48 items., Conclusions: The use of Rasch model analyses to inform item selection produced a final scale that, in both its comprehensiveness and its efficiency, should be a useful tool for researchers studying alcohol problems in college students. To aid interpretation of raw scores, examples of the types of alcohol problems that are likely to be experienced across a range of selected scores are provided., (C)2005Research Society on AlcoholismAn important, sometimes controversial feature of all psychological phenomena is whether they are categorical or dimensional. A conceptual and psychometric framework is described for distinguishing whether the latent structure behind manifest categories (e.g., psychiatric diagnoses, attitude groups, or stages of development) is category-like or dimension-like. Being dimension-like requires (a) within-category heterogeneity and (b) between-category quantitative differences. Being category-like requires (a) within-category homogeneity and (b) between-category qualitative differences. The relation between this classification and abrupt versus smooth differences is discussed. Hybrid structures are possible. Being category-like is itself a matter of degree; the authors offer a formalized framework to determine this degree. Empirical applications to personality disorders, attitudes toward capital punishment, and stages of cognitive development illustrate the approach., (C) 2005 by the American Psychological AssociationThe authors conducted Rasch model ( G. Rasch, 1960) analyses of items from the Young Adult Alcohol Problems Screening Test (YAAPST; S. C. Hurlbut & K. J. Sher, 1992) to examine the relative severity and ordering of alcohol problems in 806 college students. Items appeared to measure a single dimension of alcohol problem severity, covering a broad range of the latent continuum. Items fit the Rasch model well, with less severe symptoms reliably preceding more severe symptoms in a potential progression toward increasing levels of problem severity. However, certain items did not index problem severity consistently across demographic subgroups. A shortened, alternative version of the YAAPST is proposed, and a norm table is provided that allows for a linking of total YAAPST scores to expected symptom expression., (C) 2004 by the American Psychological AssociationA didactic on latent growth curve modeling for ordinal outcomes is presented. The conceptual aspects of modeling growth with ordinal variables and the notion of threshold invariance are illustrated graphically using a hypothetical example. The ordinal growth model is described in terms of 3 nested models: (a) multivariate normality of the underlying continuous latent variables (yt) and its relationship with the observed ordinal response pattern (Yt), (b) threshold invariance over time, and (c) growth model for the continuous latent variable on a common scale. Algebraic implications of the model restrictions are derived, and practical aspects of fitting ordinal growth models are discussed with the help of an empirical example and Mx script ( M. C. Neale, S. M. Boker, G. Xie, & H. H. Maes, 1999). The necessary conditions for the identification of growth models with ordinal data and the methodological implications of the model of threshold invariance are discussed., (C) 2004 by the American Psychological AssociationRecent research points toward the viability of conceptualizing alcohol problems as arrayed along a continuum. Nevertheless, modern statistical techniques designed to scale multiple problems along a continuum (latent trait modeling; LTM) have rarely been applied to alcohol problems. This study applies LTM methods to data on 110 problems reported during in-person interviews of 1,348 middle-aged men (mean age = 43) from the general population. The results revealed a continuum of severity linking the 110 problems, ranging from heavy and abusive drinking, through tolerance and withdrawal, to serious complications of alcoholism. These results indicate that alcohol problems can be arrayed along a dimension of severity and emphasize the relevance of LTM to informing the conceptualization and assessment of alcohol problems., (C) 2004 by the American Psychological AssociationItem response theory (IRT) is supplanting classical test theory as the basis for measures development. This study demonstrated the utility of IRT for evaluating DSM-IV diagnostic criteria. Data on alcohol, cannabis, and cocaine symptoms from 372 adult clinical participants interviewed with the Composite International Diagnostic Interview-Expanded Substance Abuse Module (CIDI-SAM) were analyzed with Mplus ( B. Muthen & L. Muthen, 1998) and MULTILOG ( D. Thissen, 1991) software. Tolerance and legal problems criteria were dropped because of poor fit with a unidimensional model. Item response curves, test information curves, and testing of variously constrained models suggested that DSM-IV criteria in the CIDI-SAM discriminate between only impaired and less impaired cases and may not be useful to scale case severity. IRT can be used to study the construct validity of DSM-IV diagnoses and to identify diagnostic criteria with poor performance., (C) 2004 by the American Psychological AssociationThis study examined the psychometric characteristics of an index of substance use involvement using item response theory. The sample consisted of 292 men and 140 women who qualified for a Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; American Psychiatric Association, 1987) substance use disorder (SUD) diagnosis and 293 men and 445 women who did not qualify for a SUD diagnosis. The results indicated that men had a higher probability of endorsing substance use compared with women. The index significantly predicted health, psychiatric, and psychosocial disturbances as well as level of substance use behavior and severity of SUD after a 2-year follow-up. Finally, this index is a reliable and useful prognostic indicator of the risk for SUD and the medical and psychosocial sequelae of drug consumption., (C) 2002 by the American Psychological AssociationComparability, validity, and impact of loss of information of a computerized adaptive administration of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) were assessed in a sample of 140 Veterans Affairs hospital patients. The countdown method ( Butcher, Keller, & Bacon, 1985) was used to adaptively administer Scales L (Lie) and F (Frequency), the 10 clinical scales, and the 15 content scales. Participants completed the MMPI-2 twice, in 1 of 2 conditions: computerized conventional test-retest, or computerized conventional-computerized adaptive. Mean profiles and test-retest correlations across modalities were comparable. Correlations between MMPI-2 scales and criterion measures supported the validity of the countdown method, although some attenuation of validity was suggested for certain health-related items. Loss of information incurred with this mode of adaptive testing has minimal impact on test validity. Item and time savings were substantial., (C) 1999 by the American Psychological Association10aPsychometrics10aSubstance-Related Disorders1 aKahler, C W1 aStrong, D R1 aRead, J P1 aDe Boeck, P1 aWilson, M1 aActon, G S1 aPalfai, T P1 aWood, M D1 aMehta, P D1 aNeale, M C1 aFlay, B R1 aConklin, C A1 aClayton, R R1 aTiffany, S T1 aShiffman, S1 aKrueger, R F1 aNichol, P E1 aHicks, B M1 aMarkon, K E1 aPatrick, C J1 aIacono, William, G1 aMcGue, Matt1 aLangenbucher, J W1 aLabouvie, E1 aMartin, C S1 aSanjuan, P M1 aBavly, L1 aKirisci, L1 aChung, T1 aVanyukov, M1 aDunn, M1 aTarter, R1 aHandel, R W1 aBen-Porath, Y S1 aWatt, M uhttp://www.iacat.org/content/toward-efficient-and-comprehensive-measurement-alcohol-problems-continuum-college-students01434nas a2200133 4500008003900000245010900039210006900148300000900217490000700226520097600233100001601209700002401225856005101249 2005 d00aTrait Parameter Recovery Using Multidimensional Computerized Adaptive Testing in Reading and Mathematics0 aTrait Parameter Recovery Using Multidimensional Computerized Ada a3-250 v293 a

Under a multidimensional item response theory (MIRT) computerized adaptive testing (CAT) testing scenario, a trait estimate (θ) in one dimension will provide clues for subsequently seeking a solution in other dimensions. This feature may enhance the efficiency of MIRT CAT’s item selection and its scoring algorithms compared with its counterpart, the unidimensional CAT (UCAT). The present study used existing Reading and Math test data to generate simulated item parameters. A confirmatory item factor analysis model was applied to the data using NOHARM to produce interpretable MIRT item parameters. Results showed that MIRT CAT, conditional on the constraints, was quite capable of producing accurate estimates on both measures. Compared with UCAT, MIRT CAT slightly increased the accuracy of both trait estimates, especially for the low-level or high-level trait examinees in both measures, and reduced the rate of unused items in the item pool.

1 aLi, Yuan, H1 aSchafer, William, D uhttp://apm.sagepub.com/content/29/1/3.abstract01663nas a2200133 4500008004100000020001400041245010900055210006900164300000900233490000700242520114500249100001201394856012301406 2005 eng d a0146-621600aTrait parameter recovery using multidimensional computerized adaptive testing in reading and mathematics0 aTrait parameter recovery using multidimensional computerized ada a3-250 v293 aUnder a multidimensional item response theory (MIRT) computerized adaptive testing (CAT) testing scenario, a trait estimate (θ) in onedimension will provide clues for subsequentlyseeking a solution in other dimensions. Thisfeature may enhance the efficiency of MIRT CAT’s item selection and its scoring algorithms compared with its counterpart, the unidimensional CAT (UCAT). The present study used existing Reading and Math test data to generate simulated item parameters. A confirmatory item factor analysis model was applied to the data using NOHARM to produce interpretable MIRT item parameters. Results showed that MIRT CAT, conditional on theconstraints, was quite capable of producing accurate estimates on both measures. Compared with UCAT, MIRT CAT slightly increased the accuracy of both trait estimates, especially for the low-level or high-level trait examinees in both measures, and reduced the rate of unused items in the item pool. Index terms: computerized adaptive testing (CAT), item response theory (IRT), dimensionality, 0-1 linear programming, constraints, item exposure, reading assessment, mathematics assessment. 1 aLi, Y H uhttp://www.iacat.org/content/trait-parameter-recovery-using-multidimensional-computerized-adaptive-testing-reading-and00540nas a2200121 4500008004100000020003800041245007000079210006500149260007200214100001600286700002700302856008900329 2005 eng d aComputerized Testing Report 97-1400aThe use of person-fit statistics in computerized adaptive testing0 ause of personfit statistics in computerized adaptive testing aNewton, PA. USAbLaw School Administration CouncilcSeptember, 20051 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/use-person-fit-statistics-computerized-adaptive-testing01450nas a2200133 4500008004100000245012200041210006900163300001000232490001000242520092300252100001001175700001501185856011601200 2005 eng d00aValidation of a computerized adaptive testing version of the Schedule for Nonadaptive and Adaptive Personality (SNAP)0 aValidation of a computerized adaptive testing version of the Sch a28-430 v17(1)3 aThis is a validation study of a computerized adaptive (CAT) version of the Schedule for Nonadaptive and Adaptive Personality (SNAP) conducted with 413 undergraduates who completed the SNAP twice, 1 week apart. Participants were assigned randomly to 1 of 4 retest groups: (a) paper-and-pencil (P&P) SNAP, (b) CAT, (c) P&P/CAT, and (d) CAT/P&P. With number of items held constant, computerized administration had little effect on descriptive statistics, rank ordering of scores, reliability, and concurrent validity, but was preferred over P&P administration by most participants. CAT administration yielded somewhat lower precision and validity than P&P administration, but required 36% to 37% fewer items and 58% to 60% less time to complete. These results confirm not only key findings from previous CAT simulation studies of personality measures but extend them for the 1st time to a live assessment setting.1 aSimms1 aClark, L A uhttp://www.iacat.org/content/validation-computerized-adaptive-testing-version-schedule-nonadaptive-and-adaptive01451nas a2200133 4500008004100000245011400041210006900155300001000224490000700234520092000241100001501161700001501176856012601191 2005 eng d00aValidation of a computerized adaptive version of the Schedule of Non-Adaptive and Adaptive Personality (SNAP)0 aValidation of a computerized adaptive version of the Schedule of a28-430 v173 a This is a validation study of a computerized adaptive (CAT) version of the Schedule for Nonadaptive and Adaptive Personality (SNAP) conducted with 413 undergraduates who completed the SNAP twice, 1 week apart. Participants were assigned randomly to 1 of 4 retest groups: (a) paper-and-pencil (P&P) SNAP, (b) CAT, (c) P&P/CAT, and (d) CAT/P&P. With number of items held constant, computerized administration had little effect on descriptive statistics, rank ordering of scores, reliability, and concurrent validity, but was preferred over P&P administration by most participants. CAT administration yielded somewhat lower precision and validity than P&P administration, but required 36% to 37% fewer items and 58% to 60% less time to complete. These results confirm not only key findings from previous CAT simulation studies of personality measures but extend them for the 1st time to a live assessment setting. 1 aSimms, L J1 aClark, L J uhttp://www.iacat.org/content/validation-computerized-adaptive-version-schedule-non-adaptive-and-adaptive-personality-snap00430nas a2200097 4500008004100000245004600041210004200087260011900129100001600248856006800264 2004 eng d00aThe ABCs of Computerized Adaptive Testing0 aABCs of Computerized Adaptive Testing aT. M. Wood and W. Zhi (Eds.), Measurement issues and practice in physical activity. Champaign, IL: Human kinetics.1 aGershon, RC uhttp://www.iacat.org/content/abcs-computerized-adaptive-testing00502nas a2200109 4500008004100000245011600041210006900157260001700226100001400243700001300257856012200270 2004 eng d00aAchieving accuracy of retest calibration for a national CAT placement examination with a restricted test length0 aAchieving accuracy of retest calibration for a national CAT plac aSan Diego CA1 aWang, X B1 aWiley, A uhttp://www.iacat.org/content/achieving-accuracy-retest-calibration-national-cat-placement-examination-restricted-test03707nas a2200481 4500008004100000245005200041210005200093300001200145490000700157520221100164653001902375653002902394653005802423653001002481653005302491653000902544653001102553653002502564653002602589653003302615653001102648653001002659653000902669653001602678653002402694653007402718653001802792653002902810653005802839653003102897653003202928653003602960653003202996100001503028700001603043700001603059700001603075700001003091700001403101700001803115700001503133856007703148 2004 eng d00aActivity outcome measurement for postacute care0 aActivity outcome measurement for postacute care aI49-1610 v423 aBACKGROUND: Efforts to evaluate the effectiveness of a broad range of postacute care services have been hindered by the lack of conceptually sound and comprehensive measures of outcomes. It is critical to determine a common underlying structure before employing current methods of item equating across outcome instruments for future item banking and computer-adaptive testing applications. OBJECTIVE: To investigate the factor structure, reliability, and scale properties of items underlying the Activity domains of the International Classification of Functioning, Disability and Health (ICF) for use in postacute care outcome measurement. METHODS: We developed a 41-item Activity Measure for Postacute Care (AM-PAC) that assessed an individual's execution of discrete daily tasks in his or her own environment across major content domains as defined by the ICF. We evaluated the reliability and discriminant validity of the prototype AM-PAC in 477 individuals in active rehabilitation programs across 4 rehabilitation settings using factor analyses, tests of item scaling, internal consistency reliability analyses, Rasch item response theory modeling, residual component analysis, and modified parallel analysis. RESULTS: Results from an initial exploratory factor analysis produced 3 distinct, interpretable factors that accounted for 72% of the variance: Applied Cognition (44%), Personal Care & Instrumental Activities (19%), and Physical & Movement Activities (9%); these 3 activity factors were verified by a confirmatory factor analysis. Scaling assumptions were met for each factor in the total sample and across diagnostic groups. Internal consistency reliability was high for the total sample (Cronbach alpha = 0.92 to 0.94), and for specific diagnostic groups (Cronbach alpha = 0.90 to 0.95). Rasch scaling, residual factor, differential item functioning, and modified parallel analyses supported the unidimensionality and goodness of fit of each unique activity domain. CONCLUSIONS: This 3-factor model of the AM-PAC can form the conceptual basis for common-item equating and computer-adaptive applications, leading to a comprehensive system of outcome instruments for postacute care settings.10a*Self Efficacy10a*Sickness Impact Profile10aActivities of Daily Living/*classification/psychology10aAdult10aAftercare/*standards/statistics & numerical data10aAged10aBoston10aCognition/physiology10aDisability Evaluation10aFactor Analysis, Statistical10aFemale10aHuman10aMale10aMiddle Aged10aMovement/physiology10aOutcome Assessment (Health Care)/*methods/statistics & numerical data10aPsychometrics10aQuestionnaires/standards10aRehabilitation/*standards/statistics & numerical data10aReproducibility of Results10aSensitivity and Specificity10aSupport, U.S. Gov't, Non-P.H.S.10aSupport, U.S. Gov't, P.H.S.1 aHaley, S M1 aCoster, W J1 aAndres, P L1 aLudlow, L H1 aNi, P1 aBond, T L1 aSinclair, S J1 aJette, A M uhttp://www.iacat.org/content/activity-outcome-measurement-postacute-care01884nas a2200241 4500008004100000245006000041210005900101260004800160300001200208520112200220653001501342653003401357653002201391653002101413653001901434653001601453653001701469653001301486653002801499100001301527700001601540856008601556 2004 eng d00aAdaptive computerized educational systems: A case study0 aAdaptive computerized educational systems A case study aSan Diego, CA. USAbElsevier Academic Press a143-1693 a(Created by APA) Adaptive instruction describes adjustments typical of one-on-one tutoring as discussed in the college tutorial scenario. So computerized adaptive instruction refers to the use of computer software--almost always incorporating artificially intelligent services--which has been designed to adjust both the presentation of information and the form of questioning to meet the current needs of an individual learner. This chapter describes a system for Internet-delivered adaptive instruction. The author attempts to demonstrate a sharp difference between the teaching that takes place outside of the classroom in universities and the kind that is at least afforded, if not taken advantage of by many, students in a more personalized educational setting such as those in the small liberal arts colleges. The author describes a computer-based technology that allows that gap to be bridged with the advantage of at least having more highly prepared learners sitting in college classrooms. A limited range of emerging research that supports that proposition is cited. (PsycINFO Database Record (c) 2005 APA )10aArtificial10aComputer Assisted Instruction10aComputer Software10aHigher Education10aIndividualized10aInstruction10aIntelligence10aInternet10aUndergraduate Education1 aRay, R D1 aMalott, R W uhttp://www.iacat.org/content/adaptive-computerized-educational-systems-case-study00451nas a2200121 4500008004100000245006900041210006900110300001200179490001000191100001700201700001900218856009200237 2004 eng d00aAdaptive exploration of user knowledge in computer based testing0 aAdaptive exploration of user knowledge in computer based testing a322-3270 v3 (1)1 aLamboudis, D1 aEconomides, AA uhttp://www.iacat.org/content/adaptive-exploration-user-knowledge-computer-based-testing01341nas a2200145 4500008003900000245008200039210006900121300001200190490000700202520087300209100001601082700001901098700002101117856005701138 2004 d00aAdaptive Testing With Regression Trees in the Presence of Multidimensionality0 aAdaptive Testing With Regression Trees in the Presence of Multid a293-3160 v293 a

It is unrealistic to suppose that standard item response theory (IRT) models will be appropriate for all the new and currently considered computer-based tests. In addition to developing new models, we also need to give attention to the possibility of constructing and analyzing new tests without the aid of strong models. Computerized adaptive testing currently relies heavily on IRT. Alternative, empirically based, nonparametric adaptive testing algorithms exist, but their properties are little known. This article introduces a nonparametric, tree-based algorithm for adaptive testing and shows that it may be superior to conventional, IRT-based adaptive testing in cases where the IRT assumptions are not satisfied. In particular, it shows that the tree-based approach clearly outperformed (one-dimensional) IRT when the pool was strongly two-dimensional.

1 aYan, Duanli1 aLewis, Charles1 aStocking, Martha uhttp://jeb.sagepub.com/cgi/content/abstract/29/3/29302776nas a2200421 4500008004100000020004600041245011200087210006900199250001500268260001000283300000700293490000600300520144100306653002701747653003001774653004701804653001001851653000901861653002201870653002801892653001101920653001101931653002001942653000901962653001601971653001601987653001902003653001602022653003502038653002902073653004002102653003002142100001402172700001702186700001702203700001402220856012002234 2004 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aThe AMC Linear Disability Score project in a population requiring residential care: psychometric properties0 aAMC Linear Disability Score project in a population requiring re a2004/08/05 cAug 3 a420 v23 aBACKGROUND: Currently there is a lot of interest in the flexible framework offered by item banks for measuring patient relevant outcomes, including functional status. However, there are few item banks, which have been developed to quantify functional status, as expressed by the ability to perform activities of daily life. METHOD: This paper examines the psychometric properties of the AMC Linear Disability Score (ALDS) project item bank using an item response theory model and full information factor analysis. Data were collected from 555 respondents on a total of 160 items. RESULTS: Following the analysis, 79 items remained in the item bank. The remaining 81 items were excluded because of: difficulties in presentation (1 item); low levels of variation in response pattern (28 items); significant differences in measurement characteristics for males and females or for respondents under or over 85 years old (26 items); or lack of model fit to the data at item level (26 items). CONCLUSIONS: It is conceivable that the item bank will have different measurement characteristics for other patient or demographic populations. However, these results indicate that the ALDS item bank has sound psychometric properties for respondents in residential care settings and could form a stable base for measuring functional status in a range of situations, including the implementation of computerised adaptive testing of functional status.10a*Disability Evaluation10a*Health Status Indicators10aActivities of Daily Living/*classification10aAdult10aAged10aAged, 80 and over10aData Collection/methods10aFemale10aHumans10aLogistic Models10aMale10aMiddle Aged10aNetherlands10aPilot Projects10aProbability10aPsychometrics/*instrumentation10aQuestionnaires/standards10aResidential Facilities/*utilization10aSeverity of Illness Index1 aHolman, R1 aLindeboom, R1 aVermeulen, M1 aHaan, R J uhttp://www.iacat.org/content/amc-linear-disability-score-project-population-requiring-residential-care-psychometric00521nam a2200097 4500008004100000245010500041210006900146260006900215100001700284856012200301 2004 eng d00aThe application of cognitive diagnosis and computerized adaptive testing to a large-scale assessment0 aapplication of cognitive diagnosis and computerized adaptive tes aUnpublished doctoral dissertation, University of Texas at Austin1 aMcGlohen, MK uhttp://www.iacat.org/content/application-cognitive-diagnosis-and-computerized-adaptive-testing-large-scale-assessment01668nas a2200229 4500008004100000245005500041210005300096300000800149490000700157520102900164653002101193653001201214653003001226653001801256653000901274100001701283700001201300700001501312700001601327700001401343856008101357 2004 eng d00aAssisted self-adapted testing: A comparative study0 aAssisted selfadapted testing A comparative study a2-90 v203 aA new type of self-adapted test (S-AT), called Assisted Self-Adapted Test (AS-AT), is presented. It differs from an ordinary S-AT in that prior to selecting the difficulty category, the computer advises examinees on their best difficulty category choice, based on their previous performance. Three tests (computerized adaptive test, AS-AT, and S-AT) were compared regarding both their psychometric (precision and efficiency) and psychological (anxiety) characteristics. Tests were applied in an actual assessment situation, in which test scores determined 20% of term grades. A sample of 173 high school students participated. Neither differences in posttest anxiety nor ability were obtained. Concerning precision, AS-AT was as precise as CAT, and both revealed more precision than S-AT. It was concluded that AS-AT acted as a CAT concerning precision. Some hints, but not conclusive support, of the psychological similarity between AS-AT and S-AT was also found. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aAnxiety10aComputer Assisted Testing10aPsychometrics10aTest1 aHontangas, P1 aOlea, J1 aPonsoda, V1 aRevuelta, J1 aWise, S L uhttp://www.iacat.org/content/assisted-self-adapted-testing-comparative-study00496nas a2200121 4500008004100000245009100041210006900132260001700201100001800218700001300236700001600249856010900265 2004 eng d00aAutomated Simultaneous Assembly of Multi-Stage Testing for the Uniform CPA Examination0 aAutomated Simultaneous Assembly of MultiStage Testing for the Un aSan Diego CA1 aBreithaupt, K1 aAriel, A1 aVeldkamp, B uhttp://www.iacat.org/content/automated-simultaneous-assembly-multi-stage-testing-uniform-cpa-examination00506nas a2200121 4500008004100000245009000041210006900131260001700200100001700217700001900234700001500253856011600268 2004 eng d00aCombining computer adaptive testing technology with cognitively diagnostic assessment0 aCombining computer adaptive testing technology with cognitively  aSan Diego CA1 aMcGlohen, MK1 aChang, Hua-Hua1 aWills, J T uhttp://www.iacat.org/content/combining-computer-adaptive-testing-technology-cognitively-diagnostic-assessment-001801nas a2200361 4500008004100000020002200041245009500063210006900158250001500227260001100242300001000253490000700263520066300270653002500933653002900958653001000987653000900997653002201006653004501028653003701073653001101110653001101121653000901132653001601141653003601157653003001193653003401223100001601257700002401273700001001297700001501307856011701322 2004 eng d a1074-9357 (Print)00aComputer adaptive testing: a strategy for monitoring stroke rehabilitation across settings0 aComputer adaptive testing a strategy for monitoring stroke rehab a2004/05/01 cSpring a33-390 v113 aCurrent functional assessment instruments in stroke rehabilitation are often setting-specific and lack precision, breadth, and/or feasibility. Computer adaptive testing (CAT) offers a promising potential solution by providing a quick, yet precise, measure of function that can be used across a broad range of patient abilities and in multiple settings. CAT technology yields a precise score by selecting very few relevant items from a large and diverse item pool based on each individual's responses. We demonstrate the potential usefulness of a CAT assessment model with a cross-sectional sample of persons with stroke from multiple rehabilitation settings.10a*Computer Simulation10a*User-Computer Interface10aAdult10aAged10aAged, 80 and over10aCerebrovascular Accident/*rehabilitation10aDisabled Persons/*classification10aFemale10aHumans10aMale10aMiddle Aged10aMonitoring, Physiologic/methods10aSeverity of Illness Index10aTask Performance and Analysis1 aAndres, P L1 aBlack-Schaffer, R M1 aNi, P1 aHaley, S M uhttp://www.iacat.org/content/computer-adaptive-testing-strategy-monitoring-stroke-rehabilitation-across-settings00415nas a2200109 4500008004100000245006300041210006300104260001700167100001900184700001400203856008800217 2004 eng d00aComputer adaptive testing and the No Child Left Behind Act0 aComputer adaptive testing and the No Child Left Behind Act aSan Diego CA1 aKingsbury, G G1 aHauser, C uhttp://www.iacat.org/content/computer-adaptive-testing-and-no-child-left-behind-act00379nas a2200097 4500008004100000245003000041210002900071260010500100100001500205856006100220 2004 eng d00aComputer-adaptive testing0 aComputeradaptive testing aB. Everett, and D. Howell (Eds.), Encyclopedia of statistics in behavioral science. New York: Wiley.1 aLuecht, RM uhttp://www.iacat.org/content/computer-adaptive-testing-200528nas a2200109 4500008004100000245009800041210006900139260006200208100001800270700001200288856011800300 2004 eng d00aComputer-based test designs with optimal and non-optimal tests for making pass-fail decisions0 aComputerbased test designs with optimal and nonoptimal tests for aResearch Report, University of Massachusetts, Amherst, MA1 aHambleton, RK1 aXing, D uhttp://www.iacat.org/content/computer-based-test-designs-optimal-and-non-optimal-tests-making-pass-fail-decisions01904nas a2200217 4500008004100000245010000041210006900141260000800210300001100218490000700229520117300236653002201409653001501431653003701446653003101483653001101514653001901525100001201544700001501556856011501571 2004 eng d00aA computerized adaptive knowledge test as an assessment tool in general practice: a pilot study0 acomputerized adaptive knowledge test as an assessment tool in ge cMar a178-830 v263 aAdvantageous to assessment in many fields, CAT (computerized adaptive testing) use in general practice has been scarce. In adapting CAT to general practice, the basic assumptions of item response theory and the case specificity must be taken into account. In this context, this study first evaluated the feasibility of converting written extended matching tests into CAT. Second, it questioned the content validity of CAT. A stratified sample of students was invited to participate in the pilot study. The items used in this test, together with their parameters, originated from the written test. The detailed test paths of the students were retained and analysed thoroughly. Using the predefined pass-fail standard, one student failed the test. There was a positive correlation between the number of items and the candidate's ability level. The majority of students were presented with questions in seven of the 10 existing domains. Although proved to be a feasible test format, CAT cannot substitute for the existing high-stakes large-scale written test. It may provide a reliable instrument for identifying candidates who are at risk of failing in the written test.10a*Computer Systems10aAlgorithms10aEducational Measurement/*methods10aFamily Practice/*education10aHumans10aPilot Projects1 aRoex, A1 aDegryse, J uhttp://www.iacat.org/content/computerized-adaptive-knowledge-test-assessment-tool-general-practice-pilot-study02593nas a2200469 4500008004100000245007200041210006900113300001000182490000600192520108600198653002501284653001001309653001501319653002101334653002201355653005901377653007001436653003301506653001101539653001101550653001301561653000901574653002701583653002201610653005501632653001901687653001501706653006601721653001801787653003701805653004101842653003001883653001301913100001501926700001301941700001801954700001501972700001401987700001402001700001302015856009502028 2004 eng d00aComputerized adaptive measurement of depression: A simulation study0 aComputerized adaptive measurement of depression A simulation stu a13-230 v43 aBackground: Efficient, accurate instruments for measuring depression are increasingly importantin clinical practice. We developed a computerized adaptive version of the Beck DepressionInventory (BDI). We examined its efficiency and its usefulness in identifying Major DepressiveEpisodes (MDE) and in measuring depression severity.Methods: Subjects were 744 participants in research studies in which each subject completed boththe BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale.Results: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%,equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21items). The adaptive latent depression score correlated r = .92 with the BDI total score and thelatent depression score correlated more highly with the Hamilton (r = .74) than the BDI total scoredid (r = .70).Conclusions: Adaptive testing for depression may provide greatly increased efficiency withoutloss of accuracy in identifying MDE or in measuring depression severity.10a*Computer Simulation10aAdult10aAlgorithms10aArea Under Curve10aComparative Study10aDepressive Disorder/*diagnosis/epidemiology/psychology10aDiagnosis, Computer-Assisted/*methods/statistics & numerical data10aFactor Analysis, Statistical10aFemale10aHumans10aInternet10aMale10aMass Screening/methods10aPatient Selection10aPersonality Inventory/*statistics & numerical data10aPilot Projects10aPrevalence10aPsychiatric Status Rating Scales/*statistics & numerical data10aPsychometrics10aResearch Support, Non-U.S. Gov't10aResearch Support, U.S. Gov't, P.H.S.10aSeverity of Illness Index10aSoftware1 aGardner, W1 aShear, K1 aKelleher, K J1 aPajer, K A1 aMammen, O1 aBuysse, D1 aFrank, E uhttp://www.iacat.org/content/computerized-adaptive-measurement-depression-simulation-study00344nas a2200097 4500008004100000245003400041210003400075260005600109100001600165856006500181 2004 eng d00aComputerized adaptive testing0 aComputerized adaptive testing aEncyclopedia of social measurement. Academic Press.1 aSegall, D O uhttp://www.iacat.org/content/computerized-adaptive-testing-100511nas a2200133 4500008004100000245005100041210005100092260009900143100001700242700001600259700001400275700000800289856008000297 2004 eng d00aComputerized adaptive testing and item banking0 aComputerized adaptive testing and item banking aP. M. Fayers and R. D. Hays (Eds.) Assessing Quality of Life. Oxford: Oxford University Press.1 aBjorner, J B1 aKosinski, M1 aWare, J E1 aJr. uhttp://www.iacat.org/content/computerized-adaptive-testing-and-item-banking00481nas a2200109 4500008004500000245010200045210006900147300001000216490000700226100001400233856012400247 2004 Engldsh 00aComputerized Adaptive Testing for Effective and Efficient Measurement in Counseling and Education0 aComputerized Adaptive Testing for Effective and Efficient Measur a70-840 v371 aWeiss, DJ uhttp://www.iacat.org/content/computerized-adaptive-testing-effective-and-efficient-measurement-counseling-and-education01251nas a2200157 4500008003900000245006400039210006300103300001200166490000700178520076400185100002500949700002200974700002200996700002201018856005301040 2004 d00aComputerized Adaptive Testing With Multiple-Form Structures0 aComputerized Adaptive Testing With MultipleForm Structures a147-1640 v283 a

A multiple-form structure (MFS) is an orderedcollection or network of testlets (i.e., sets of items).An examinee’s progression through the networkof testlets is dictated by the correctness of anexaminee’s answers, thereby adapting the test tohis or her trait level. The collection of pathsthrough the network yields the set of all possibletest forms, allowing test specialists the opportunityto review them before they are administered. Also,limiting the exposure of an individual MFS to aspecific period of time can enhance test security.This article provides an overview of methods thathave been developed to generate parallel MFSs.The approach is applied to the assembly of anexperimental computerized Law School Admission Test (LSAT).

1 aArmstrong, Ronald, D1 aJones, Douglas, H1 aKoppel, Nicole, B1 aPashley, Peter, J uhttp://apm.sagepub.com/content/28/3/147.abstract01543nas a2200229 4500008004100000020002200041245006400063210006300127260002600190300001200216490000700228520081800235653003401053653003001087653002801117653001301145100001901158700001501177700001601192700001701208856008801225 2004 eng d a0146-6216 (Print)00aComputerized adaptive testing with multiple-form structures0 aComputerized adaptive testing with multipleform structures bSage Publications: US a147-1640 v283 aA multiple-form structure (MFS) is an ordered collection or network of testlets (i.e., sets of items). An examinee's progression through the network of testlets is dictated by the correctness of an examinee's answers, thereby adapting the test to his or her trait level. The collection of paths through the network yields the set of all possible test forms, allowing test specialists the opportunity to review them before they are administered. Also, limiting the exposure of an individual MFS to a specific period of time can enhance test security. This article provides an overview of methods that have been developed to generate parallel MFSs. The approach is applied to the assembly of an experimental computerized Law School Admission Test (LSAT). (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aLaw School Admission Test10amultiple-form structure10atestlets1 aArmstrong, R D1 aJones, D H1 aKoppel, N B1 aPashley, P J uhttp://www.iacat.org/content/computerized-adaptive-testing-multiple-form-structures01908nas a2200217 4500008004100000020004600041245010100087210006900188260002600257300001200283490000700295520111100302653002401413653003201437653001301469653003801482100001701520700001501537700001401552856012401566 2004 eng d a0021-9762 (Print); 1097-4679 (Electronic)00aComputers in clinical assessment: Historical developments, present status, and future challenges0 aComputers in clinical assessment Historical developments present bJohn Wiley & Sons: US a331-3450 v603 aComputerized testing methods have long been regarded as a potentially powerful asset for providing psychological assessment services. Ever since computers were first introduced and adapted to the field of assessment psychology in the 1950s, they have been a valuable aid for scoring, data processing, and even interpretation of test results. The history and status of computer-based personality and neuropsychological tests are discussed in this article. Several pertinent issues involved in providing test interpretation by computer are highlighted. Advances in computer-based test use, such as computerized adaptive testing, are described and problems noted. Today, there is great interest in expanding the availability of psychological assessment applications on the Internet. Although these applications show great promise, there are a number of problems associated with providing psychological tests on the Internet that need to be addressed by psychologists before the Internet can become a major medium for psychological service delivery. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aclinical assessment10acomputerized testing method10aInternet10apsychological assessment services1 aButcher, J N1 aPerry, J L1 aHahn, J A uhttp://www.iacat.org/content/computers-clinical-assessment-historical-developments-present-status-and-future-challenges01612nas a2200217 4500008004100000020002200041245008200063210006900145260004300214300001200257490000700269520084600276653003401122653002601156653003501182653001601217653001701233100002301250700001801273856010301291 2004 eng d a1076-9986 (Print)00aConstraining item exposure in computerized adaptive testing with shadow tests0 aConstraining item exposure in computerized adaptive testing with bAmerican Educational Research Assn: US a273-2910 v293 aItem-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles Sympson and Hetter’s (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. The method does not, however, require time-consuming simulation studies to set values for control parameters before the operational use of the test. Instead, it can set the probabilities of item ineligibility adaptively during the test using the actual item-exposure rates. An empirical study using an item pool from the Law School Admission Test showed that application of the method yielded perfect control of the item-exposure rates and had negligible impact on the bias and mean-squared error functions of the ability estimator. 10acomputerized adaptive testing10aitem exposure control10aitem ineligibility constraints10aProbability10ashadow tests1 avan der Linden, WJ1 aVeldkamp, B P uhttp://www.iacat.org/content/constraining-item-exposure-computerized-adaptive-testing-shadow-tests01302nas a2200133 4500008003900000245008200039210006900121300001200190490000700202520085800209100001901067700002501086856005701111 2004 d00aConstraining Item Exposure in Computerized Adaptive Testing With Shadow Tests0 aConstraining Item Exposure in Computerized Adaptive Testing With a273-2910 v293 a

Item-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles Sympson and Hetter’s (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. The method does not, however, require time-consuming simulation studies to set values for control parameters before the operational use of the test. Instead, it can set the probabilities of item ineligibility adaptively during the test using the actual item-exposure rates. An empirical study using an item pool from the Law School Admission Test showed that application of the method yielded perfect control of the item-exposure rates and had negligible impact on the bias and mean-squared error functions of the ability estimator.

1 aLinden, Wim, J1 aVeldkamp, Bernard, P uhttp://jeb.sagepub.com/cgi/content/abstract/29/3/27301907nas a2200217 4500008004100000020002200041245007000063210006900133260004100202300001200243490000700255520117100262653003201433653003301465653001801498653002401516100001301540700001801553700002301571856009501594 2004 eng d a0022-0655 (Print)00aConstructing rotating item pools for constrained adaptive testing0 aConstructing rotating item pools for constrained adaptive testin bBlackwell Publishing: United Kingdom a345-3590 v413 aPreventing items in adaptive testing from being over- or underexposed is one of the main problems in computerized adaptive testing. Though the problem of overexposed items can be solved using a probabilistic item-exposure control method, such methods are unable to deal with the problem of underexposed items. Using a system of rotating item pools, on the other hand, is a method that potentially solves both problems. In this method, a master pool is divided into (possibly overlapping) smaller item pools, which are required to have similar distributions of content and statistical attributes. These pools are rotated among the testing sites to realize desirable exposure rates for the items. A test assembly model, motivated by Gulliksen's matched random subtests method, was explored to help solve the problem of dividing a master pool into a set of smaller pools. Different methods to solve the model are proposed. An item pool from the Law School Admission Test was used to evaluate the performances of computerized adaptive tests from systems of rotating item pools constructed using these methods. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive tests10aconstrained adaptive testing10aitem exposure10arotating item pools1 aAriel, A1 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/constructing-rotating-item-pools-constrained-adaptive-testing00512nas a2200109 4500008004100000245012200041210006900163260001700232100001200249700001700261856012400278 2004 eng d00aThe context effects of multidimensional CAT on the accuracy of multidimensional abilities and the item exposure rates0 acontext effects of multidimensional CAT on the accuracy of multi aSan Diego CA1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/context-effects-multidimensional-cat-accuracy-multidimensional-abilities-and-item-exposure00436nam a2200097 4500008003900000245007800039210006900117260003900186100001600225856009700241 2004 d00aContributions to the theory and practice of computerized adaptive testing0 aContributions to the theory and practice of computerized adaptiv aArnhem, The Netherlands: Citogroep1 aEggen, Theo uhttp://www.iacat.org/content/contributions-theory-and-practice-computerized-adaptive-testing00399nas a2200109 4500008004100000245005900041210005800100260001700158100001100175700001800186856008500204 2004 eng d00aDetecting exposed test items in computer-based testing0 aDetecting exposed test items in computerbased testing aSan Diego CA1 aHan, N1 aHambleton, RK uhttp://www.iacat.org/content/detecting-exposed-test-items-computer-based-testing00489nas a2200097 4500008003900000245008700039210006900126260006200195100001700257856011700274 2004 d00aDeveloping tailored instruments: Item banking and computerized adaptive assessment0 aDeveloping tailored instruments Item banking and computerized ad aItem Banks, and Computer-Adaptive Testing,” Bethesda MD1 aBjorner, J B uhttp://www.iacat.org/content/developing-tailored-instruments-item-banking-and-computerized-adaptive-assessment-100489nas a2200097 4500008004100000245008700041210006900128260006200197100001500259856011700274 2004 eng d00aDeveloping tailored instruments: Item banking and computerized adaptive assessment0 aDeveloping tailored instruments Item banking and computerized ad aItem Banks, and Computer-Adaptive Testing,” Bethesda MD1 aChang, C-H uhttp://www.iacat.org/content/developing-tailored-instruments-item-banking-and-computerized-adaptive-assessment-200546nas a2200145 4500008004100000245008900041210006900130300001200199490000700211653003400218100001400252700001400266700001500280856010500295 2004 eng d00aThe development and evaluation of a software prototype for computer-adaptive testing0 adevelopment and evaluation of a software prototype for computera a109-1230 v4310acomputerized adaptive testing1 aLilley, M1 aBarker, T1 aBritton, C uhttp://www.iacat.org/content/development-and-evaluation-software-prototype-computer-adaptive-testing01993nas a2200193 4500008004100000020002200041245011400063210006900177260004100246300001200287490000700299520125600306653003401562653002501596653002601621100001401647700001901661856011901680 2004 eng d a0022-0655 (Print)00aEffects of practical constraints on item selection rules at the early stages of computerized adaptive testing0 aEffects of practical constraints on item selection rules at the  bBlackwell Publishing: United Kingdom a149-1740 v413 aThe purpose of this study was to compare the effects of four item selection rules--(1) Fisher information (F), (2) Fisher information with a posterior distribution (FP), (3) Kullback-Leibler information with a posterior distribution (KP), and (4) completely randomized item selection (RN)--with respect to the precision of trait estimation and the extent of item usage at the early stages of computerized adaptive testing. The comparison of the four item selection rules was carried out under three conditions: (1) using only the item information function as the item selection criterion; (2) using both the item information function and content balancing; and (3) using the item information function, content balancing, and item exposure control. When test length was less than 10 items, FP and KP tended to outperform F at extreme trait levels in Condition 1. However, in more realistic settings, it could not be concluded that FP and KP outperformed F, especially when item exposure control was imposed. When test length was greater than 10 items, the three nonrandom item selection procedures performed similarly no matter what the condition was, while F had slightly higher item usage. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aitem selection rules10apractical constraints1 aChen, S-Y1 aAnkenmann, R D uhttp://www.iacat.org/content/effects-practical-constraints-item-selection-rules-early-stages-computerized-adaptive01903nas a2200193 4500008004100000020002200041245010000063210006900163260004300232300001200275490000700287520117500294653002301469653003001492653002301522653002501545100001601570856012301586 2004 eng d a1076-9986 (Print)00aEstimating ability and item-selection strategy in self-adapted testing: A latent class approach0 aEstimating ability and itemselection strategy in selfadapted tes bAmerican Educational Research Assn: US a379-3960 v293 aThis article presents a psychometric model for estimating ability and item-selection strategies in self-adapted testing. In contrast to computer adaptive testing, in self-adapted testing the examinees are allowed to select the difficulty of the items. The item-selection strategy is defined as the distribution of difficulty conditional on the responses given to previous items. The article shows that missing responses in self-adapted testing are missing at random and can be ignored in the estimation of ability. However, the item-selection strategy cannot always be ignored in such an estimation. An EM algorithm is presented to estimate an examinee's ability and strategies, and a model fit is evaluated using Akaike's information criterion. The article includes an application with real data to illustrate how the model can be used in practice for evaluating hypotheses, estimating ability, and identifying strategies. In the example, four strategies were identified and related to examinees' ability. It was shown that individual examinees tended not to follow a consistent strategy throughout the test. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aestimating ability10aitem-selection strategies10apsychometric model10aself-adapted testing1 aRevuelta, J uhttp://www.iacat.org/content/estimating-ability-and-item-selection-strategy-self-adapted-testing-latent-class-approach00426nas a2200109 4500008004100000245006900041210006900110260002100179100001100200700001200211856009300223 2004 eng d00aEvaluating scale stability of a computer adaptive testing system0 aEvaluating scale stability of a computer adaptive testing system aMcLean, VAbGMAC1 aGuo, F1 aWang, L uhttp://www.iacat.org/content/evaluating-scale-stability-computer-adaptive-testing-system00572nam a2200097 4500008004100000245015200041210006900193260007600262100001700338856011900355 2004 eng d00aEvaluating the effects of several multi-stage testing design variables on selected psychometric outcomes for certification and licensure assessment0 aEvaluating the effects of several multistage testing design vari aUnpublished doctoral dissertation, University of Massachusetts, Amherst1 aZenisky, A L uhttp://www.iacat.org/content/evaluating-effects-several-multi-stage-testing-design-variables-selected-psychometric02472nas a2200193 4500008004100000245010700041210007100148300001200219490000700231520172200238653002101960653003401981653001602015653003002031653002302061653004502084100001502129856013402144 2004 eng d00aÉvaluation et multimédia dans l'apprentissage d'une L2 [Assessment and multimedia in learning an L2]0 aÉvaluation et multimédia dans lapprentissage dune L2 Assessment  a475-4870 v163 aIn the first part of this paper different areas where technology may be used for second language assessment are described. First, item banking operations, which are generally based on item Response Theory but not necessarily restricted to dichotomously scored items, facilitate assessment task organization and require technological support. Second, technology may help to design more authentic assessment tasks or may be needed in some direct testing situations. Third, the assessment environment may be more adapted and more stimulating when technology is used to give the student more control. The second part of the paper presents different functions of assessment. The monitoring function (often called formative assessment) aims at adapting the classroom activities to students and to provide continuous feedback. Technology may be used to train the teachers in monitoring techniques, to organize data or to produce diagnostic information; electronic portfolios or quizzes that are built in some educational software may also be used for monitoring. The placement function is probably the one in which the application of computer adaptive testing procedures (e.g. French CAPT) is the most appropriate. Automatic scoring devices may also be used for placement purposes. Finally the certification function requires more valid and more reliable tools. Technology may be used to enhance the testing situation (to make it more authentic) or to facilitate data processing during the construction of a test. Almond et al. (2002) propose a four component model (Selection, Presentation, Scoring and Response) for designing assessment systems. Each component must be planned taking into account the assessment function. 10aAdaptive Testing10aComputer Assisted Instruction10aEducational10aForeign Language Learning10aProgram Evaluation10aTechnology computerized adaptive testing1 aLaurier, M uhttp://www.iacat.org/content/%C3%A9valuation-et-multim%C3%A9dia-dans-lapprentissage-dune-l2-assessment-and-multimedia-learning-l202036nas a2200181 4500008004100000020002200041245006400063210006400127260004300191300001200234490000700246520141900253653003201672653003401704100001801738700001701756856008101773 2004 eng d a1076-9986 (Print)00aEvaluation of the CATSIB DIF procedure in a pretest setting0 aEvaluation of the CATSIB DIF procedure in a pretest setting bAmerican Educational Research Assn: US a177-1990 v293 aA new procedure, CATSIB, for assessing differential item functioning (DIF) on computerized adaptive tests (CATs) is proposed. CATSIB, a modified SIBTEST procedure, matches test takers on estimated ability and controls for impact-induced Type I error inflation by employing a CAT version of the SIBTEST "regression correction." The performance of CATSIB in terms of detection of DIF in pretest items was evaluated in a simulation study. Simulated test takers were adoptively administered 25 operational items from a pool of 1,000 and were linearly administered 16 pretest items that were evaluated for DIF. Sample size varied from 250 to 500 in each group. Simulated impact levels ranged from a 0- to 1-standard-deviation difference in mean ability levels. The results showed that CATSIB with the regression correction displayed good control over Type 1 error, whereas CATSIB without the regression correction displayed impact-induced Type 1 error inflation. With 500 test takers in each group, power rates were exceptionally high (84% to 99%) for values of DIF at the boundary between moderate and large DIF. For smaller samples of 250 test takers in each group, the corresponding power rates ranged from 47% to 95%. In addition, in all cases, CATSIB was very accurate in estimating the true values of DIF, displaying at most only minor estimation bias. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive tests10adifferential item functioning1 aNandakumar, R1 aRoussos, L A uhttp://www.iacat.org/content/evaluation-catsib-dif-procedure-pretest-setting00524nas a2200121 4500008004100000245011300041210006900154300001200223490000700235100001500242700001900257856012600276 2004 eng d00affects of practical constraints on item selection rules at the early stages of computerized adaptive testing0 affects of practical constraints on item selection rules at the e a149-1740 v411 aChen, Y -Y1 aAnkenmann, R D uhttp://www.iacat.org/content/ffects-practical-constraints-item-selection-rules-early-stages-computerized-adaptive-testing01470nas a2200133 4500008003900000245013600039210006900175300000900244490000700253520098400260100001601244700002501260856005101285 2004 d00aImpact of Test Design, Item Quality, and Item Bank Size on the Psychometric Properties of Computer-Based Credentialing Examinations0 aImpact of Test Design Item Quality and Item Bank Size on the Psy a5-210 v643 a

Computer-based testing by credentialing agencies has become common; however, selecting a test design is difficult because several good ones are available—parallel forms, computer adaptive (CAT), and multistage (MST). In this study, three computerbased test designs under some common examination conditions were investigated. Item bank size and item quality had a practically significant impact on decision consistency and accuracy. Even in nearly ideal situations, the choice of test design was not a factor in the results. Two conclusions follow from the findings: (a) More time and resources should be committed to expanding the size and quality of item banks, and (b) designs that individualize an exam administration such as MST and CAT may not be helpful when the primary purpose of the examination is to make pass-fail decisions and conditions are present for using parallel forms with a target information function that can be centered on the passing score.

1 aXing, Dehui1 aHambleton, Ronald, K uhttp://epm.sagepub.com/content/64/1/5.abstract01192nas a2200133 4500008003900000245009600039210006900135300001200204490000700216520074500223100002000968700001700988856005301005 2004 d00aImplementation and Measurement Efficiency of Multidimensional Computerized Adaptive Testing0 aImplementation and Measurement Efficiency of Multidimensional Co a295-3160 v283 a

Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random administration. The results showed that the higher the correlation between latent traits, the more latent traits there were, and the more scoring levels there were in the items, the more efficient MAT was than the other two procedures. For tests containing multidimensional items, only MAT is applicable, whereas unidimensional adaptive testing is not. Issues in implementing MAT are discussed.

1 aWang, Wen-Chung1 aChen, Po-Hsi uhttp://apm.sagepub.com/content/28/5/295.abstract00501nas a2200109 4500008004100000245010500041210006900146260001700215100001700232700001800249856012400267 2004 eng d00aInvestigating the effects of selected multi-stage test design alternatives on credentialing outcomes0 aInvestigating the effects of selected multistage test design alt aSan Diego CA1 aZenisky, A L1 aHambleton, RK uhttp://www.iacat.org/content/investigating-effects-selected-multi-stage-test-design-alternatives-credentialing-outcomes00613nas a2200121 4500008004100000245012400041210006900165260010500234100001200339700001200351700001100363856011700374 2004 eng d00aAn investigation of two combination procedures of SPRT for three-category decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat aPaper presented at the annual meeting of the American Educational Research Association, San Diego CA1 aJiao, H1 aWang, S1 aLau, A uhttp://www.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-decisions-computerized00709nas a2200157 4500008004100000245013900041210006900180260003200249653003400281653004000315653004100355100001200396700001200408700001200420856011900432 2004 eng d00aAn investigation of two combination procedures of SPRT for three-category classification decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat aSan Antonio, Texasc04/200410acomputerized adaptive testing10aComputerized classification testing10asequential probability ratio testing1 aJiao, H1 aWang, S1 aLau, CA uhttp://www.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-classification-decisions00390nas a2200121 4500008004100000245004800041210004800089260001700137100001200154700001500166700001500181856007200196 2004 eng d00aItem parameter recovery with adaptive tests0 aItem parameter recovery with adaptive tests aSan Diego CA1 aDo, B-R1 aChuah, S C1 aDrasgow, F uhttp://www.iacat.org/content/item-parameter-recovery-adaptive-tests01773nas a2200193 4500008004100000245023000041210006900271300000900340490000700349520093900356653002101295653003001316653001801346653001601364653004201380100001201422700001901434856012601453 2004 eng d00aKann die Konfundierung von Konzentrationsleistung und Aktivierung durch adaptives Testen mit dern FAKT vermieden werden? [Avoiding the confounding of concentration performance and activation by adaptive testing with the FACT]0 aKann die Konfundierung von Konzentrationsleistung und Aktivierun a1-170 v253 aThe study investigates the effect of computerized adaptive testing strategies on the confounding of concentration performance with activation. A sample of 54 participants was administered 1 out of 3 versions (2 adaptive, 1 non-adaptive) of the computerized Frankfurt Adaptive Concentration Test FACT (Moosbrugger & Heyden, 1997) at three subsequent points in time. During the test administration changes in activation (electrodermal activity) were recorded. The results pinpoint a confounding of concentration performance with activation for the non-adaptive test version, but not for the adaptive test versions (p = .01). Thus, adaptive FACT testing strategies can remove the confounding of concentration performance with activation, thereby increasing the discriminant validity. In conclusion, an attention-focusing-hypothesis is formulated to explain the observed effect. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aConcentration10aPerformance10aTesting computerized adaptive testing1 aFrey, A1 aMoosbrugger, H uhttp://www.iacat.org/content/kann-die-konfundierung-von-konzentrationsleistung-und-aktivierung-durch-adaptives-testen-mit00585nas a2200133 4500008004100000245010800041210006900149260003200218100002400250700001700274700001800291700001600309856012600325 2004 eng d00aA learning environment for english for academic purposes based on adaptive tests and task-based systems0 alearning environment for english for academic purposes based on  b Springer Berlin Heidelberg1 aPITON-GONÇALVES, J1 aALUISIO, S M1 aMENDONCA, L H1 aNOVAES, O O uhttp://www.iacat.org/content/learning-environment-english-academic-purposes-based-adaptive-tests-and-task-based-systems-000717nas a2200205 4500008004100000020002200041245010800063210006900171260003300240300000900273490000900282100002400291700002300315700002700338700002900365700002100394700002300415700002300438856005000461 2004 eng d a978-3-540-22948-300aA Learning Environment for English for Academic Purposes Based on Adaptive Tests and Task-Based Systems0 aLearning Environment for English for Academic Purposes Based on  bSpringer Berlin / Heidelberg a1-110 v32201 aGonçalves, Jean, P1 aAluisio, Sandra, M1 aOliveira, Leandro, H M1 aOliveira Jr., Osvaldo, N1 aLester, James, C1 aVicari, Rosa Maria1 aParaguaçu, Fábio uhttp://dx.doi.org/10.1007/978-3-540-30139-4_101441nas a2200157 4500008003900000245006700039210006700106300001200173490000700185520094700192100002901139700002301168700001901191700002001210856005301230 2004 d00aMokken Scale Analysis Using Hierarchical Clustering Procedures0 aMokken Scale Analysis Using Hierarchical Clustering Procedures a332-3540 v283 a

Mokken scale analysis (MSA) can be used to assess and build unidimensional scales from an item pool that is sensitive to multiple dimensions. These scales satisfy a set of scaling conditions, one of which follows from the model of monotone homogeneity. An important drawback of the MSA program is that the sequential item selection and scale construction procedure may not find the dominant underlying dimensionality of the responses to a set of items. The authors investigated alternative hierarchical item selection procedures and compared the performance of four hierarchical methods and the sequential clustering method in the MSA context. The results showed that hierarchical clustering methods can improve the search process of the dominant dimensionality of a data matrix. In particular, the complete linkage and scale linkage methods were promising in finding the dimensionality of the item response data from a set of items.

1 aAbswoude, Alexandra, A H1 aVermunt, Jeroen, K1 aHemker, Bas, T1 aArk, Andries, L uhttp://apm.sagepub.com/content/28/5/332.abstract00423nas a2200097 4500008004100000245007800041210006900119260001700188100001600205856010400221 2004 eng d00aMutual information item selection in multiple-category classification CAT0 aMutual information item selection in multiplecategory classifica aSan Diego CA1 aWeissman, A uhttp://www.iacat.org/content/mutual-information-item-selection-multiple-category-classification-cat00328nas a2200097 4500008004100000245004500041210004500086260001700131100001200148856007000160 2004 eng d00aNew methods for CBT item pool evaluation0 aNew methods for CBT item pool evaluation aSan Diego CA1 aWang, L uhttp://www.iacat.org/content/new-methods-cbt-item-pool-evaluation00542nas a2200109 4500008004100000245012100041210006900162260004000231100001600271700001900287856012600306 2004 eng d00aOptimal testing with easy items in computerized adaptive testing (Measurement and Research Department Report 2004-2)0 aOptimal testing with easy items in computerized adaptive testing aArnhem, The Netherlands: Cito Group1 aEggen, Theo1 aVerschoor, A J uhttp://www.iacat.org/content/optimal-testing-easy-items-computerized-adaptive-testing-measurement-and-research-department02843nas a2200349 4500008004100000020004600041245011400087210006900201250001500270260001100285300000700296490000600303520169400309653002702003653002002030653002102050653002002071653004702091653003702138653001802175653001102193653001902204653001602223653002002239653003002259100001402289700001402303700001702317700002002334700001402354856012502368 2004 eng d a1477-7525 (Electronic)1477-7525 (Linking)00aPractical methods for dealing with 'not applicable' item responses in the AMC Linear Disability Score project0 aPractical methods for dealing with not applicable item responses a2004/06/18 cJun 16 a290 v23 aBACKGROUND: Whenever questionnaires are used to collect data on constructs, such as functional status or health related quality of life, it is unlikely that all respondents will respond to all items. This paper examines ways of dealing with responses in a 'not applicable' category to items included in the AMC Linear Disability Score (ALDS) project item bank. METHODS: The data examined in this paper come from the responses of 392 respondents to 32 items and form part of the calibration sample for the ALDS item bank. The data are analysed using the one-parameter logistic item response theory model. The four practical strategies for dealing with this type of response are: cold deck imputation; hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. RESULTS: The item and respondent population parameter estimates were very similar for the strategies involving hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. The estimates obtained using the cold deck imputation method were substantially different. CONCLUSIONS: The cold deck imputation method was not considered suitable for use in the ALDS item bank. The other three methods described can be usefully implemented in the ALDS item bank, depending on the purpose of the data analysis to be carried out. These three methods may be useful for other data sets examining similar constructs, when item response theory based methods are used.10a*Disability Evaluation10a*Health Surveys10a*Logistic Models10a*Questionnaires10aActivities of Daily Living/*classification10aData Interpretation, Statistical10aHealth Status10aHumans10aPilot Projects10aProbability10aQuality of Life10aSeverity of Illness Index1 aHolman, R1 aGlas, C A1 aLindeboom, R1 aZwinderman, A H1 aHaan, R J uhttp://www.iacat.org/content/practical-methods-dealing-not-applicable-item-responses-amc-linear-disability-score-project01774nas a2200217 4500008004100000245007700041210006900118300001100187490000600198520108400204653001501288653002501303653001601328653001001344653001801354653002101372653003101393100001901424700001501443856009801458 2004 eng d00aPre-equating: a simulation study based on a large scale assessment model0 aPreequating a simulation study based on a large scale assessment a301-180 v53 aAlthough post-equating (PE) has proven to be an acceptable method in the scaling and equating of items and forms, there are times when the turn-around period for equating and converting raw scores to scale scores is so small that PE cannot be undertaken within the prescribed time frame. In such cases, pre-equating (PrE) could be considered as an acceptable alternative. Assessing the feasibility of using item calibrations from the item bank (as in PrE) is conditioned on the equivalency of the calibrations and the errors associated with it vis a vis the results obtained via PE. This paper creates item banks over three periods of item introduction into the banks and uses the Rasch model in examining data with respect to the recovery of item parameters, the measurement error, and the effect cut-points have on examinee placement in both the PrE and PE situations. Results indicate that PrE is a viable solution to PE provided the stability of the item calibrations are enhanced by using large sample sizes (perhaps as large as full-population) in populating the item bank.10a*Databases10a*Models, Theoretical10aCalibration10aHuman10aPsychometrics10aReference Values10aReproducibility of Results1 aTaherbhai, H M1 aYoung, M J uhttp://www.iacat.org/content/pre-equating-simulation-study-based-large-scale-assessment-model00448nas a2200097 4500008004100000245009600041210006900137260001700206100001500223856011200238 2004 eng d00aProtecting the integrity of computer-adaptive licensure tests: Results of a legal challenge0 aProtecting the integrity of computeradaptive licensure tests Res aSan Diego CA1 aCizek, G J uhttp://www.iacat.org/content/protecting-integrity-computer-adaptive-licensure-tests-results-legal-challenge04032nas a2200433 4500008004100000245012300041210006900164260000800233300001200241490000700253520252400260653001902784653002902803653005802832653001002890653000902900653002202909653002602931653003302957653001102990653001103001653000903012653001603021653007403037653003003111653003603141653005803177653003103235653004503266653004103311653003203352100001603384700001503400700001603415700001603431700001403447700001203461856012503473 2004 eng d00aRefining the conceptual basis for rehabilitation outcome measurement: personal care and instrumental activities domain0 aRefining the conceptual basis for rehabilitation outcome measure cJan aI62-1720 v423 aBACKGROUND: Rehabilitation outcome measures routinely include content on performance of daily activities; however, the conceptual basis for item selection is rarely specified. These instruments differ significantly in format, number, and specificity of daily activity items and in the measurement dimensions and type of scale used to specify levels of performance. We propose that a requirement for upper limb and hand skills underlies many activities of daily living (ADL) and instrumental activities of daily living (IADL) items in current instruments, and that items selected based on this definition can be placed along a single functional continuum. OBJECTIVE: To examine the dimensional structure and content coverage of a Personal Care and Instrumental Activities item set and to examine the comparability of items from existing instruments and a set of new items as measures of this domain. METHODS: Participants (N = 477) from 3 different disability groups and 4 settings representing the continuum of postacute rehabilitation care were administered the newly developed Activity Measure for Post-Acute Care (AM-PAC), the SF-8, and an additional setting-specific measure: FIM (in-patient rehabilitation); MDS (skilled nursing facility); MDS-PAC (postacute settings); OASIS (home care); or PF-10 (outpatient clinic). Rasch (partial-credit model) analyses were conducted on a set of 62 items covering the Personal Care and Instrumental domain to examine item fit, item functioning, and category difficulty estimates and unidimensionality. RESULTS: After removing 6 misfitting items, the remaining 56 items fit acceptably along the hypothesized continuum. Analyses yielded different difficulty estimates for the maximum score (eg, "Independent performance") for items with comparable content from different instruments. Items showed little differential item functioning across age, diagnosis, or severity groups, and 92% of the participants fit the model. CONCLUSIONS: ADL and IADL items from existing rehabilitation outcomes instruments that depend on skilled upper limb and hand use can be located along a single continuum, along with the new personal care and instrumental items of the AM-PAC addressing gaps in content. Results support the validity of the proposed definition of the Personal Care and Instrumental Activities dimension of function as a guide for future development of rehabilitation outcome instruments, such as linked, setting-specific short forms and computerized adaptive testing approaches.10a*Self Efficacy10a*Sickness Impact Profile10aActivities of Daily Living/*classification/psychology10aAdult10aAged10aAged, 80 and over10aDisability Evaluation10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods/statistics & numerical data10aQuestionnaires/*standards10aRecovery of Function/physiology10aRehabilitation/*standards/statistics & numerical data10aReproducibility of Results10aResearch Support, U.S. Gov't, Non-P.H.S.10aResearch Support, U.S. Gov't, P.H.S.10aSensitivity and Specificity1 aCoster, W J1 aHaley, S M1 aAndres, P L1 aLudlow, L H1 aBond, T L1 aNi, P S uhttp://www.iacat.org/content/refining-conceptual-basis-rehabilitation-outcome-measurement-personal-care-and-instrumental02888nas a2200301 4500008004100000020002200041245013700063210006900200250001500269260000800284300001000292490000700302520186600309653001102175653003302186653001102219653004602230653002402276653002902300653003002329653002902359100001502388700001602403700001602419700001602435700001002451856012502461 2004 eng d a0003-9993 (Print)00aScore comparability of short forms and computerized adaptive testing: Simulation study with the activity measure for post-acute care0 aScore comparability of short forms and computerized adaptive tes a2004/04/15 cApr a661-60 v853 aOBJECTIVE: To compare simulated short-form and computerized adaptive testing (CAT) scores to scores obtained from complete item sets for each of the 3 domains of the Activity Measure for Post-Acute Care (AM-PAC). DESIGN: Prospective study. SETTING: Six postacute health care networks in the greater Boston metropolitan area, including inpatient acute rehabilitation, transitional care units, home care, and outpatient services. PARTICIPANTS: A convenience sample of 485 adult volunteers who were receiving skilled rehabilitation services. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Inpatient and community-based short forms and CAT applications were developed for each of 3 activity domains (physical & mobility, personal care & instrumental, applied cognition) using item pools constructed from new items and items from existing postacute care instruments. RESULTS: Simulated CAT scores correlated highly with score estimates from the total item pool in each domain (4- and 6-item CAT r range,.90-.95; 10-item CAT r range,.96-.98). Scores on the 10-item short forms constructed for inpatient and community settings also provided good estimates of the AM-PAC item pool scores for the physical & movement and personal care & instrumental domains, but were less consistent in the applied cognition domain. Confidence intervals around individual scores were greater in the short forms than for the CATs. CONCLUSIONS: Accurate scoring estimates for AM-PAC domains can be obtained with either the setting-specific short forms or the CATs. The strong relationship between CAT and item pool scores can be attributed to the CAT's ability to select specific items to match individual responses. The CAT may have additional advantages over short forms in practicality, efficiency, and the potential for providing more precise scoring estimates for individuals.10aBoston10aFactor Analysis, Statistical10aHumans10aOutcome Assessment (Health Care)/*methods10aProspective Studies10aQuestionnaires/standards10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aCoster, W J1 aAndres, P L1 aKosinski, M1 aNi, P uhttp://www.iacat.org/content/score-comparability-short-forms-and-computerized-adaptive-testing-simulation-study-activity00456nas a2200109 4500008004100000245007900041210006900120260001700189100002300206700001800229856009900247 2004 eng d00aA sequential Bayesian procedure for item calibration in multistage testing0 asequential Bayesian procedure for item calibration in multistage aSan Diego CA1 avan der Linden, WJ1 aMead, Alan, D uhttp://www.iacat.org/content/sequential-bayesian-procedure-item-calibration-multistage-testing01571nas a2200133 4500008004100000020001300041245007500054210006900129300001200198490000800210520110300218100001501321856010101336 2004 eng d a0378375800aSequential estimation in variable length computerized adaptive testing0 aSequential estimation in variable length computerized adaptive t a249-2640 v1213 aWith the advent of modern computer technology, there have been growing e3orts in recent years to computerize standardized tests, including the popular Graduate Record Examination (GRE), the Graduate Management Admission Test (GMAT) and the Test of English as a Foreign Language (TOEFL). Many of such computer-based tests are known as the computerized adaptive tests, a major feature of which is that, depending on their performance in the course of testing, di3erent examinees may be given with di3erent sets of items (questions). In doing so, items can be e>ciently utilized to yield maximum accuracy for estimation of examinees’ ability traits. We consider, in this article, one type of such tests where test lengths vary with examinees to yield approximately same predetermined accuracy for all ability traits. A comprehensive large sample theory is developed for the expected test length and the sequential point and interval estimates of the latent trait. Extensive simulations are conducted with results showing that the large sample approximations are adequate for realistic sample sizes. 1 aChang, I Y uhttp://www.iacat.org/content/sequential-estimation-variable-length-computerized-adaptive-testing01264nas a2200133 4500008004100000245007500041210006900116260000800185300001200193490000700205520080400212100001601016856009801032 2004 eng d00aA sharing item response theory model for computerized adaptive testing0 asharing item response theory model for computerized adaptive tes cWin a439-4600 v293 aA new sharing item response theory (SIRT) model is presented which explicitly models the effects of sharing item content between informants and testtakers. This model is used to construct adaptive item selection and scoring rules that provide increased precision and reduced score gains in instances where sharing occurs. The adaptive item selection rules are expressed as functions of the item’s exposure rate in addition to other commonly used properties (characterized by difficulty, discrimination, and guessing parameters). Based on the results of simulated item responses, the new item selection and scoring algorithms compare favorably to the Sympson-Hetter exposure control method. The new SIRT approach provides higher reliability and lower score gains in instances where sharing occurs.1 aSegall, D O uhttp://www.iacat.org/content/sharing-item-response-theory-model-computerized-adaptive-testing00541nas a2200181 4500008004100000245005000041210004800091300001000139490000700149653003400156100001400190700001500204700001500219700001400234700002600248700001300274856007200287 2004 eng d00aSiette: a web-based tool for adaptive testing0 aSiette a webbased tool for adaptive testing a29-610 v1410acomputerized adaptive testing1 aConejo, R1 aGuzmán, E1 aMillán, E1 aTrella, M1 aPérez-De-La-Cruz, JL1 aRíos, A uhttp://www.iacat.org/content/siette-web-based-tool-adaptive-testing00606nas a2200109 4500008004100000245009200041210006900133260014600202100001800348700001900366856011100385 2004 eng d00aState-of-the-art and adaptive open-closed items in adaptive foreign language assessment0 aStateoftheart and adaptive openclosed items in adaptive foreign  aProceedings 4th Hellenic Conference with ternational Participation: Informational and Communication Technologies in Education, Athens,747-7561 aGiouroglou, H1 aEconomides, AA uhttp://www.iacat.org/content/state-art-and-adaptive-open-closed-items-adaptive-foreign-language-assessment00429nas a2200121 4500008004100000022001400041245006600055210006600121490000600187100001000193700001800203856008600221 2004 eng d a1575-910500aStatistics for detecting disclosed items in a CAT environment0 aStatistics for detecting disclosed items in a CAT environment0 v51 aLu, Y1 aHambleton, RK uhttp://www.iacat.org/content/statistics-detecting-disclosed-items-cat-environment01895nas a2200181 4500008004100000020002200041245012000063210006900183260002600252300001200278490000700290520119300297653003401490653003701524653001801561100001401579856012001593 2004 eng d a0146-6216 (Print)00aStrategies for controlling item exposure in computerized adaptive testing with the generalized partial credit model0 aStrategies for controlling item exposure in computerized adaptiv bSage Publications: US a165-1850 v283 aChoosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline condition, the randomesque, modified-within-.10-logits, Sympson-Hetter, conditional Sympson-Hetter, a-stratified with multiple-stratification, and enhanced a-stratified with multiple-stratification procedures were implemented to control exposure rates. Two variations of the randomesque and modified-within-.10-logits procedures were examined, which varied the size of the item group from which the next item to be administered was randomly selected. The results indicate that although the conditional Sympson-Hetter provides somewhat lower maximum exposure rates, the randomesque and modified-within-.10-logits procedures with the six-item group variation have great utility for controlling overlap rates and increasing pool utilization and should be given further consideration. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10ageneralized partial credit model10aitem exposure1 aDavis, LL uhttp://www.iacat.org/content/strategies-controlling-item-exposure-computerized-adaptive-testing-generalized-partial01590nas a2200121 4500008003900000245012000039210006900159300001200228490000700240520114100247100002701388856005301415 2004 d00aStrategies for Controlling Item Exposure in Computerized Adaptive Testing With the Generalized Partial Credit Model0 aStrategies for Controlling Item Exposure in Computerized Adaptiv a165-1850 v283 a

Choosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline condition, the randomesque, modified-within-.10-logits, Sympson-Hetter, conditional Sympson-Hetter, a-stratified with multiple-stratification, and enhanced a-stratified with multiple-stratification procedures were implemented to control exposure rates. Two variations of the randomesque and modified-within-.10-logits procedures were examined, which varied the size of the item group from which the next item to be administered was randomly selected. The results indicate that although the conditional Sympson-Hetter provides somewhat lower maximum exposure rates, the randomesque and modified-within-.10-logits procedures with the six-item group variation have great utility for controlling overlap rates and increasing pool utilization and should be given further consideration.

1 aDavis, Laurie Laughlin uhttp://apm.sagepub.com/content/28/3/165.abstract03122nas a2200121 4500008004100000245009500041210006900136300000900205490000700214520263700221100002502858856011702883 2004 eng d00aStrategies for controlling testlet exposure rates in computerized adaptive testing systems0 aStrategies for controlling testlet exposure rates in computerize a58350 v643 aExposure control procedures in computerized adaptive testing (CAT) systems protect item pools from being compromised, however, this impacts measurement precision. Previous research indicates that exposure control procedures perform differently for dichotomously scored versus polytomously scored CAT systems. For dichotomously scored CATs, conditional selection procedures are often the optimal choice, while randomization procedures perform best for polytomously scored CATs. CAT systems modeled with testlet response theory have not been examined to determine optimal exposure control procedures. This dissertation examined various exposure control procedures in testlet-based CAT systems using the three-parameter logistic testlet response theory model and the partial credit model. The exposure control procedures were the randomesque procedure, the modified within .10 logits procedure, two levels of the progressive restricted procedure, and two levels of the Sympson-Hetter procedure. Each of these was compared to a baseline no exposure control procedure, maximum information. The testlets were reading passages with six to ten multiple-choice items. The CAT systems consisted of maximum information testlet selection contingent on an exposure control procedure and content balancing for passage type and the number of items per passage; expected a posteriori ability estimation; and a fixed length stopping rule of seven testlets totaling fifty multiple-choice items. Measurement precision and exposure rates were examined to evaluate the effectiveness of the exposure control procedures for each measurement model. The exposure control procedures yielded similar results for measurement precision within the models. The exposure rates distinguished which exposure control procedures were most effective. The Sympson-Hetter conditions, which are conditional procedures, maintained the pre-specified maximum exposure rate, but performed very poorly in terms of pool utilization. The randomization procedures, randomesque and modified within .10 logits, yielded low maximum exposure rates, but used only about 70% of the testlet pool. Surprisingly, the progressive restricted procedure, which is a combination of both a conditional and randomization procedure, yielded the best results in its ability to maintain and control the maximum exposure rate and it used the entire testlet pool. The progressive restricted conditions were the optimal procedures for both the partial credit CAT systems and the three-parameter logistic testlet response theory CAT systems. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aBoyd, Aimee Michelle uhttp://www.iacat.org/content/strategies-controlling-testlet-exposure-rates-computerized-adaptive-testing-systems00380nas a2200109 4500008004100000245005200041210005000093260001700143100001900160700001500179856007600194 2004 eng d00aA study of multiple stage adaptive test designs0 astudy of multiple stage adaptive test designs aSan Diego CA1 aArmstrong, R D1 aEdmonds, J uhttp://www.iacat.org/content/study-multiple-stage-adaptive-test-designs00433nas a2200121 4500008004100000245006600041210006600107300001200173490001000185100001300195700001500208856008800223 2004 eng d00aTest difficulty and stereotype threat on the GRE General Test0 aTest difficulty and stereotype threat on the GRE General Test a563-5970 v34(3)1 aStricker1 aBejar, I I uhttp://www.iacat.org/content/test-difficulty-and-stereotype-threat-gre-general-test01418nas a2200145 4500008004100000245007600041210006900117260000800186300001200194490000700206520092600213100001401139700001701153856010201170 2004 eng d00aTesting vocabulary knowledge: Size, strength, and computer adaptiveness0 aTesting vocabulary knowledge Size strength and computer adaptive cSep a399-4360 v543 a(from the journal abstract) In this article, we describe the development and trial of a bilingual computerized test of vocabulary size, the number of words the learner knows, and strength, a combination of four aspects of knowledge of meaning that are assumed to constitute a hierarchy of difficulty: passive recognition (easiest), active recognition, passive recall, and active recall (hardest). The participants were 435 learners of English as a second language. We investigated whether the above hierarchy was valid and which strength modality correlated best with classroom language performance. Results showed that the hypothesized hierarchy was present at all word frequency levels, that passive recall was the best predictor of classroom language performance, and that growth in vocabulary knowledge was different for the different strength modalities. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aLaufer, B1 aGoldstein, Z uhttp://www.iacat.org/content/testing-vocabulary-knowledge-size-strength-and-computer-adaptiveness00543nas a2200097 4500008004100000245008700041210006900128260012200197100001900319856010700338 2004 eng d00aUnderstanding computerized adaptive testing: From Robbins-Munro to Lord and beyond0 aUnderstanding computerized adaptive testing From RobbinsMunro to aD. Kaplan (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 117-133). New York: Sage.1 aChang, Hua-Hua uhttp://www.iacat.org/content/understanding-computerized-adaptive-testing-robbins-munro-lord-and-beyond01879nas a2200169 4500008004100000245013100041210006900172300001200241490000700253520122700260653003001487653002501517653001501542653001601557100001601573856012001589 2004 eng d00aUsing patterns of summed scores in paper-and-pencil tests and computer-adaptive tests to detect misfitting item score patterns0 aUsing patterns of summed scores in paperandpencil tests and comp a119-1360 v413 aTwo new methods have been proposed to determine unexpected sum scores on subtests (testlets) both for paper-and-pencil tests and computer adaptive tests. A method based on a conservative bound using the hypergeometric distribution, denoted ρ, was compared with a method where the probability for each score combination was calculated using a highest density region (HDR). Furthermore, these methods were compared with the standardized log-likelihood statistic with and without a correction for the estimated latent trait value (denoted as l-super(*)-sub(z) and l-sub(z), respectively). Data were simulated on the basis of the one-parameter logistic model, and both parametric and nonparametric logistic regression was used to obtain estimates of the latent trait. Results showed that it is important to take the trait level into account when comparing subtest scores. In a nonparametric item response theory (IRT) context, on adapted version of the HDR method was a powerful alterative to ρ. In a parametric IRT context, results showed that l-super(*)-sub(z) had the highest power when the data were simulated conditionally on the estimated latent trait level. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aComputer Assisted Testing10aItem Response Theory10aperson Fit10aTest Scores1 aMeijer, R R uhttp://www.iacat.org/content/using-patterns-summed-scores-paper-and-pencil-tests-and-computer-adaptive-tests-detect01413nas a2200121 4500008003900000245011400039210006900153300001200222490000700234520097400241100002301215856005301238 2004 d00aUsing Set Covering with Item Sampling to Analyze the Infeasibility of Linear Programming Test Assembly Models0 aUsing Set Covering with Item Sampling to Analyze the Infeasibili a355-3750 v283 a

This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be infeasible. Causes of infeasibility can be difficult to find. A method is proposed that constitutes a helpful tool for test assemblers to detect infeasibility before hand and, in the case of infeasibility, give insight into its causes. This method is based on SCIS. Although SCIS can help to detect feasibility or infeasibility, its power lies in pinpointing causes of infeasibility such as irreducible infeasible sets of constraints. Methods to resolve infeasibility are also given, minimizing the model deviations. A simulation study is presented, offering a guide to test assemblers to analyze and solve infeasibility.

1 aHuitzing, Hiddo, A uhttp://apm.sagepub.com/content/28/5/355.abstract00638nas a2200193 4500008004100000245009100041210006900132300000900201490000700210100001400217700001600231700001400247700001700261700002000278700001400298700001500312700001200327856010500339 2004 eng d00aValidating the German computerized adaptive test for anxiety on healthy sample (A-CAT)0 aValidating the German computerized adaptive test for anxiety on  a15150 v131 aBecker, J1 aWalter, O B1 aFliege, H1 aBjorner, J B1 aKocalevent, R D1 aSchmid, G1 aKlapp, B F1 aRose, M uhttp://www.iacat.org/content/validating-german-computerized-adaptive-test-anxiety-healthy-sample-cat00478nas a2200109 4500008004100000245009600041210006900137260001500206100001200221700001700233856011800250 2003 eng d00aAccuracy of reading and mathematics ability estimates under the shadow-test constraint MCAT0 aAccuracy of reading and mathematics ability estimates under the  aChicago IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/accuracy-reading-and-mathematics-ability-estimates-under-shadow-test-constraint-mcat01390nas a2200121 4500008004100000245010300041210006900144260011000213300000900323520079300332100001701125856012601142 2003 eng d00aAn adaptation of stochastic curtailment to truncate Wald’s SPRT in computerized adaptive testing0 aadaptation of stochastic curtailment to truncate Wald s SPRT in  aLos AngelesbNational Center for Research on Evaluation, Standards, and Student TestingcSteptember, 2003 a1-263 a

Computerized adaptive testing (CAT) has been shown to increase eÆciency in educational measurement. One common application of CAT is to classify students as either pro cient or not proficient in ability. A truncated form of Wald's sequential probability ratio test (SPRT), in which examination is halted after a prespeci ed number of questions, has been proposed to provide a diagnosis of prociency. This article studies the further truncation provided by stochastic curtailment, where an exam is stopped early if completion of the remaining questions would be unlikely to alter the classi cation of the examinee. In a simulation study presented, the increased truncation is shown to offer substantial improvement in test length with only a slight decrease in accuracy.

1 aFinkelman, M uhttp://www.iacat.org/content/adaptation-stochastic-curtailment-truncate-wald%E2%80%99s-sprt-computerized-adaptive-testing00550nas a2200121 4500008004100000245006500041210006500106260011000171100001700281700001900298700002000317856009100337 2003 eng d00aAdaptive exploration of assessment results under uncertainty0 aAdaptive exploration of assessment results under uncertainty aProceedings 3rd IEEE ternational Conference on Advanced Learning Technologies, ICALT '03, 460-461, 2003.1 aLamboudis, D1 aEconomides, AA1 aPapastergiou, A uhttp://www.iacat.org/content/adaptive-exploration-assessment-results-under-uncertainty00477nas a2200097 4500008004100000245012000041210006900161260001500230100001600245856011800261 2003 eng d00aAn adaptive exposure control algorithm for computerized adaptive testing using a sharing item response theory model0 aadaptive exposure control algorithm for computerized adaptive te aChicago IL1 aSegall, D O uhttp://www.iacat.org/content/adaptive-exposure-control-algorithm-computerized-adaptive-testing-using-sharing-item00474nas a2200121 4500008004100000245008000041210006900121300001200190490000700202100002300209700001900232856010100251 2003 eng d00aAlpha-stratified adaptive testing with large numbers of content constraints0 aAlphastratified adaptive testing with large numbers of content c a107-1200 v271 avan der Linden, WJ1 aChang, Hua-Hua uhttp://www.iacat.org/content/alpha-stratified-adaptive-testing-large-numbers-content-constraints00352nas a2200109 4500008004100000245004500041210004100086260001500127100001900142700001400161856006700175 2003 eng d00aThe assembly of multiple form structures0 aassembly of multiple form structures aChicago IL1 aArmstrong, R D1 aLittle, J uhttp://www.iacat.org/content/assembly-multiple-form-structures00463nas a2200109 4500008004100000245007000041210006600111260005300177100001900230700001700249856008700266 2003 eng d00aThe assembly of multiple stage adaptive tests with discrete items0 aassembly of multiple stage adaptive tests with discrete items aNewtown, PA: Law School Admission Council Report1 aArmstrong, R D1 aEdmonds, J J uhttp://www.iacat.org/content/assembly-multiple-stage-adaptive-tests-discrete-items00406nas a2200109 4500008004100000245006200041210006200103260001500165100001900180700001300199856008400212 2003 eng d00aAssessing CAT security breaches by the item pooling index0 aAssessing CAT security breaches by the item pooling index aChicago IL1 aChang, Hua-Hua1 aZhang, J uhttp://www.iacat.org/content/assessing-cat-security-breaches-item-pooling-index01227nas a2200193 4500008004100000245002900041210002900070260003200099300001200131520066800143653003000811653003200841653001400873653004500887100001200932700001500944700001600959856005800975 2003 eng d00aAssessing question banks0 aAssessing question banks aLondon, UKbKogan Page Ltd. a171-2303 aIn Chapter 14, Joanna Bull and James Daziel provide a comprehensive treatment of the issues surrounding the use of Question Banks and Computer Assisted Assessment, and provide a number of excellent examples of implementations. In their review of the technologies employed in Computer Assisted Assessment the authors include Computer Adaptive Testing and data generation. The authors reveal significant issues involving the impact of Intellectual Property rights and computer assisted assessment and make important suggestions for strategies to overcome these obstacles. (PsycINFO Database Record (c) 2005 APA )http://www-jime.open.ac.uk/2003/1/ (journal abstract)10aComputer Assisted Testing10aCurriculum Based Assessment10aEducation10aTechnology computerized adaptive testing1 aBull, J1 aDalziel, J1 aVreeland, T uhttp://www.iacat.org/content/assessing-question-banks00418nas a2200097 4500008004100000245008000041210006900121260001500190100001600205856009900221 2003 eng d00aAssessing the efficiency of item selection in computerized adaptive testing0 aAssessing the efficiency of item selection in computerized adapt aChicago IL1 aWeissman, A uhttp://www.iacat.org/content/assessing-efficiency-item-selection-computerized-adaptive-testing00411nas a2200121 4500008003900000245006100039210005900100300001400159490000700173100001000180700001600190856008300206 2003 d00aa-Stratified multistage CAT design with content-blocking0 aaStratified multistage CAT design with contentblocking a359–3780 v561 aYi, Q1 aChang, H -H uhttp://www.iacat.org/content/stratified-multistage-cat-design-content-blocking00567nas a2200097 4500008004100000245008000041210006900121260015300190100002300343856010300366 2003 eng d00aBayesian checks on outlying response times in computerized adaptive testing0 aBayesian checks on outlying response times in computerized adapt aH. Yanai, A. Okada, K. Shigemasu, Y. Kano, Y. and J. J. Meulman, (Eds.), New developments in psychometrics (pp. 215-222). New York: Springer-Verlag.1 avan der Linden, WJ uhttp://www.iacat.org/content/bayesian-checks-outlying-response-times-computerized-adaptive-testing00492nas a2200121 4500008004100000245009400041210006900135300001500204490000700219100002000226700001500246856010900261 2003 eng d00aA Bayesian method for the detection of item preknowledge in computerized adaptive testing0 aBayesian method for the detection of item preknowledge in comput a2, 121-1370 v271 aMcLeod L. D., C1 aThissen, D uhttp://www.iacat.org/content/bayesian-method-detection-item-preknowledge-computerized-adaptive-testing-001923nas a2200241 4500008004100000245009400041210006900135300001200204490000700216520110100223653002101324653001301345653003001358653005701388653000901445653003201454653002601486653002001512100001401532700001301546700001501559856010701574 2003 eng d00aA Bayesian method for the detection of item preknowledge in computerized adaptive testing0 aBayesian method for the detection of item preknowledge in comput a121-1370 v273 aWith the increased use of continuous testing in computerized adaptive testing, new concerns about test security have evolved, such as how to ensure that items in an item pool are safeguarded from theft. In this article, procedures to detect test takers using item preknowledge are explored. When test takers use item preknowledge, their item responses deviate from the underlying item response theory (IRT) model, and estimated abilities may be inflated. This deviation may be detected through the use of person-fit indices. A Bayesian posterior log odds ratio index is proposed for detecting the use of item preknowledge. In this approach to person fit, the estimated probability that each test taker has preknowledge of items is updated after each item response. These probabilities are based on the IRT parameters, a model specifying the probability that each item has been memorized, and the test taker's item responses. Simulations based on an operational computerized adaptive test (CAT) pool are used to demonstrate the use of the odds ratio index. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aCheating10aComputer Assisted Testing10aIndividual Differences computerized adaptive testing10aItem10aItem Analysis (Statistical)10aMathematical Modeling10aResponse Theory1 aMcLeod, L1 aLewis, C1 aThissen, D uhttp://www.iacat.org/content/bayesian-method-detection-item-preknowledge-computerized-adaptive-testing00418nas a2200097 4500008004100000245007500041210006900116260001500185100001600200856010400216 2003 eng d00aCalibrating CAT item pools and online pretest items using MCMC methods0 aCalibrating CAT item pools and online pretest items using MCMC m aChicago IL1 aSegall, D O uhttp://www.iacat.org/content/calibrating-cat-item-pools-and-online-pretest-items-using-mcmc-methods00483nas a2200109 4500008004100000245009300041210006900134260001500203100001700218700001600235856012200251 2003 eng d00aCalibrating CAT pools and online pretest items using marginal maximum likelihood methods0 aCalibrating CAT pools and online pretest items using marginal ma aChicago IL1 aPommerich, M1 aSegall, D O uhttp://www.iacat.org/content/calibrating-cat-pools-and-online-pretest-items-using-marginal-maximum-likelihood-methods00508nas a2200109 4500008004100000245012000041210006900161260001500230100001500245700001600260856012200276 2003 eng d00aCalibrating CAT pools and online pretest items using nonparametric and adjusted marginal maximum likelihood methods0 aCalibrating CAT pools and online pretest items using nonparametr aChicago IL1 aKrass, I A1 aWilliams, B uhttp://www.iacat.org/content/calibrating-cat-pools-and-online-pretest-items-using-nonparametric-and-adjusted-marginal02654nas a2200385 4500008004100000245014400041210006900185300001200254490000700266520138100273653002101654653003301675653002901708653001501737653001001752653000901762653002201771653002601793653003301819653002501852653001901877653001001896653002501906653001601931653002401947653002601971653002701997653003202024653001302056653002802069100001702097700001602114700001402130856012402144 2003 eng d00aCalibration of an item pool for assessing the burden of headaches: an application of item response theory to the Headache Impact Test (HIT)0 aCalibration of an item pool for assessing the burden of headache a913-9330 v123 aBACKGROUND: Measurement of headache impact is important in clinical trials, case detection, and the clinical monitoring of patients. Computerized adaptive testing (CAT) of headache impact has potential advantages over traditional fixed-length tests in terms of precision, relevance, real-time quality control and flexibility. OBJECTIVE: To develop an item pool that can be used for a computerized adaptive test of headache impact. METHODS: We analyzed responses to four well-known tests of headache impact from a population-based sample of recent headache sufferers (n = 1016). We used confirmatory factor analysis for categorical data and analyses based on item response theory (IRT). RESULTS: In factor analyses, we found very high correlations between the factors hypothesized by the original test constructers, both within and between the original questionnaires. These results suggest that a single score of headache impact is sufficient. We established a pool of 47 items which fitted the generalized partial credit IRT model. By simulating a computerized adaptive health test we showed that an adaptive test of only five items had a very high concordance with the score based on all items and that different worst-case item selection scenarios did not lead to bias. CONCLUSION: We have established a headache impact item pool that can be used in CAT of headache impact.10a*Cost of Illness10a*Decision Support Techniques10a*Sickness Impact Profile10aAdolescent10aAdult10aAged10aComparative Study10aDisability Evaluation10aFactor Analysis, Statistical10aHeadache/*psychology10aHealth Surveys10aHuman10aLongitudinal Studies10aMiddle Aged10aMigraine/psychology10aModels, Psychological10aPsychometrics/*methods10aQuality of Life/*psychology10aSoftware10aSupport, Non-U.S. Gov't1 aBjorner, J B1 aKosinski, M1 aWare, Jr. uhttp://www.iacat.org/content/calibration-item-pool-assessing-burden-headaches-application-item-response-theory-headache00525nas a2200145 4500008004100000245008400041210006900125300001200194490000700206100001300213700001400226700001300240700001700253856010900270 2003 eng d00aCan an item response theory-based pain item bank enhance measurement precision?0 aCan an item response theorybased pain item bank enhance measurem aD34-D360 v251 aLai, J-S1 aDineen, K1 aCella, D1 aVon Roenn, J uhttp://www.iacat.org/content/can-item-response-theory-based-pain-item-bank-enhance-measurement-precision00429nas a2200097 4500008004100000245008100041210006900122260001900191100001700210856010400227 2003 eng d00aCan We Assess Pre-K Kids With Computer-Based Tests: STAR Early Literacy Data0 aCan We Assess PreK Kids With ComputerBased Tests STAR Early Lite aSan Antonio TX1 aMcBride, J R uhttp://www.iacat.org/content/can-we-assess-pre-k-kids-computer-based-tests-star-early-literacy-data00478nas a2200109 4500008004100000245007400041210006800115260005500183100001600238700001400254856010000268 2003 eng d00aCAT-ASVAB prototype Internet delivery system: Final report (FR-03-06)0 aCATASVAB prototype Internet delivery system Final report FR0306 aArlington VA: Human Resources Rsearch Organization1 aSticha, P J1 aBarber, G uhttp://www.iacat.org/content/cat-asvab-prototype-internet-delivery-system-final-report-fr-03-0600433nas a2200109 4500008004100000245004900041210004900090260007200139100001800211700001900229856007500248 2003 eng d00aCognitive CAT in foreign language assessment0 aCognitive CAT in foreign language assessment aPowerful ICT Tools for Learning and Teaching, PEG '03, CD-ROM, 20031 aGiouroglou, H1 aEconomides, AA uhttp://www.iacat.org/content/cognitive-cat-foreign-language-assessment01840nas a2200205 4500008004100000245009000041210006900131300001100200490000700211520111400218653002101332653003001353653001601383653003201399653001601431653004501447100001501492700001601507856011101523 2003 eng d00aA comparative study of item exposure control methods in computerized adaptive testing0 acomparative study of item exposure control methods in computeriz a71-1030 v403 aThis study compared the properties of five methods of item exposure control within the purview of estimating examinees' abilities in a computerized adaptive testing (CAT) context. Each exposure control algorithm was incorporated into the item selection procedure and the adaptive testing progressed based on the CAT design established for this study. The merits and shortcomings of these strategies were considered under different item pool sizes and different desired maximum exposure rates and were evaluated in light of the observed maximum exposure rates, the test overlap rates, and the conditional standard errors of measurement. Each method had its advantages and disadvantages, but no one possessed all of the desired characteristics. There was a clear and logical trade-off between item exposure control and measurement precision. The M. L. Stocking and C. Lewis conditional multinomial procedure and, to a slightly lesser extent, the T. Davey and C. G. Parshall method seemed to be the most promising considering all of the factors that this study addressed. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aEducational10aItem Analysis (Statistical)10aMeasurement10aStrategies computerized adaptive testing1 aChang, S-W1 aAnsley, T N uhttp://www.iacat.org/content/comparative-study-item-exposure-control-methods-computerized-adaptive-testing00576nas a2200121 4500008004100000245016100041210006900202260001500271100001400286700001400300700002100314856011900335 2003 eng d00aA comparison of exposure control procedures in CAT systems based on different measurement models for testlets using the verbal reasoning section of the MCAT0 acomparison of exposure control procedures in CAT systems based o aChicago IL1 aBoyd, A M1 aDodd, B G1 aFitzpatrick, S J uhttp://www.iacat.org/content/comparison-exposure-control-procedures-cat-systems-based-different-measurement-models00553nas a2200133 4500008004100000245011800041210006900159260001500228100001400243700001400257700001400271700001400285856012000299 2003 eng d00aA comparison of item exposure control procedures using a CAT system based on the generalized partial credit model0 acomparison of item exposure control procedures using a CAT syste aChicago IL1 aBurt, W M1 aKim, S -J1 aDavis, LL1 aDodd, B G uhttp://www.iacat.org/content/comparison-item-exposure-control-procedures-using-cat-system-based-generalized-partial00418nas a2200097 4500008004100000245007700041210006900118260002000187100001500207856009800222 2003 eng d00aA comparison of learning potential results at various educational levels0 acomparison of learning potential results at various educational  a25-27 June 20031 aDe Beer, M uhttp://www.iacat.org/content/comparison-learning-potential-results-various-educational-levels00509nas a2200133 4500008004100000245008600041210006900127260001500196100001300211700001500224700001500239700001400254856010700268 2003 eng d00aComparison of multi-stage tests with computer adaptive and paper and pencil tests0 aComparison of multistage tests with computer adaptive and paper  aChicago IL1 aRotou, O1 aPatsula, L1 aSteffen, M1 aRizavi, S uhttp://www.iacat.org/content/comparison-multi-stage-tests-computer-adaptive-and-paper-and-pencil-tests00452nas a2200109 4500008003900000245008900039210006900128300001200197490000700209100001700216856010900233 2003 d00aA computer adaptive testing simulation applied to the FIM instrument motor component0 acomputer adaptive testing simulation applied to the FIM instrume a384-3930 v841 aDijkers, M P uhttp://www.iacat.org/content/computer-adaptive-testing-simulation-applied-fim-instrument-motor-component03603nas a2200121 4500008004100000245008800041210006900129300000800198490000700206520312600213100002903339856011303368 2003 eng d00aComputer-adaptive test for measuring personality factors using item response theory0 aComputeradaptive test for measuring personality factors using it a9990 v643 aThe aim of the present research was to develop a computer adaptive test with the graded response model to measure the Five Factor Model of personality attributes. In the first of three studies, simulated items and simulated examinees were used to investigate systematically the impact of several variables on the accuracy and efficiency of a computer adaptive test. Item test banks containing more items, items with greater trait discrimination, and more response options resulted in increased accuracy and efficiency of the computer adaptive test. It was also found that large stopping rule values required fewer items before stopping but had less accuracy compared to smaller stopping rule values. This demonstrated a trade-off between accuracy and efficiency such that greater measurement accuracy can be obtained at a cost of decreased test efficiency. In the second study, the archival responses of 501 participants to five 30-item test banks measuring the Five Factor Model of personality were utilized in simulations of a computer adaptive personality test. The computer adaptive test estimates of participant trait scores were highly correlated with the item response theory trait estimates, and the magnitude of the correlation was related directly to the stopping rule value with higher correlations and less measurement error being associated with smaller stopping rule values. It was also noted that the performance of the computer adaptive test was dependent on the personality factor being measured whereby Conscientiousness required the most number of items to be administered and Neuroticism required the least. The results confirmed that a simulated computer adaptive test using archival personality data could accurately and efficiently attain trait estimates. In the third study, 276 student participants selected response options with a click of a mouse in a computer adaptive personality test (CAPT) measuring the Big Five factors of the Five Factor Model of personality structure. Participant responses to alternative measures of the Big Five were also collected using conventional paper-and-pencil personality questionnaires. It was found that the CAPT obtained trait estimates that were very accurate even with very few administered items. Similarly, the CAPT trait estimates demonstrated moderate to high concurrent validity with the alternative Big Five measures, and the strength of the estimates varied as a result of the similarity of the personality items and assessment methodology. It was also found that the computer adaptive test was accurately able to detect, with relatively few items, the relations between the measured personality traits and several socially interesting variables such as smoking behavior, alcohol consumption rating, and number of dates per month. Implications of the results of this research are discussed in terms of the utility of computer adaptive testing of personality characteristics. As well, methodological limitations of the studies are noted and directions for future research are considered. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aMacdonald, Paul Lawrence uhttp://www.iacat.org/content/computer-adaptive-test-measuring-personality-factors-using-item-response-theory01761nas a2200313 4500008004100000245007700041210006900118300001200187490000700199520083400206653002101040653001501061653001701076653001601093653003001109653001701139653001501156653002501171653002001196653001501216653002501231653001801256653000901274100001801283700001201301700001601313700001601329856010201345 2003 eng d00aComputerized adaptive rating scales for measuring managerial performance0 aComputerized adaptive rating scales for measuring managerial per a237-2460 v113 aComputerized adaptive rating scales (CARS) had been developed to measure contextual or citizenship performance. This rating format used a paired-comparison protocol, presenting pairs of behavioral statements scaled according to effectiveness levels, and an iterative item response theory algorithm to obtain estimates of ratees' citizenship performance (W. C. Borman et al, 2001). In the present research, we developed CARS to measure the entire managerial performance domain, including task and citizenship performance, thus addressing a major limitation of the earlier CARS. The paper describes this development effort, including an adjustment to the algorithm that reduces substantially the number of item pairs required to obtain almost as much precision in the performance estimates. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aAlgorithms10aAssociations10aCitizenship10aComputer Assisted Testing10aConstruction10aContextual10aItem Response Theory10aJob Performance10aManagement10aManagement Personnel10aRating Scales10aTest1 aSchneider, RJ1 aGoff, M1 aAnderson, S1 aBorman, W C uhttp://www.iacat.org/content/computerized-adaptive-rating-scales-measuring-managerial-performance00405nas a2200109 4500008004100000245003400041210003400075260009400109100001500203700001200218856006500230 2003 eng d00aComputerized adaptive testing0 aComputerized adaptive testing aR. Fernández-Ballesteros (Ed.): Encyclopaedia of Psychological Assessment. London: Sage.1 aPonsoda, V1 aOlea, J uhttp://www.iacat.org/content/computerized-adaptive-testing-000509nas a2200133 4500008004100000245008300041210006900124260001500193100001500208700001900223700001300242700001200255856010800267 2003 eng d00aComputerized adaptive testing: A comparison of three content balancing methods0 aComputerized adaptive testing A comparison of three content bala aChicago IL1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T1 aWen, z. uhttp://www.iacat.org/content/computerized-adaptive-testing-comparison-three-content-balancing-methods-001114nas a2200145 4500008004100000245008300041210006900124300000900193490000600202520060700208100001500815700001900830700001300849856010600862 2003 eng d00aComputerized adaptive testing: A comparison of three content balancing methods0 aComputerized adaptive testing A comparison of three content bala a1-150 v23 aContent balancing is often a practical consideration in the design of computerized adaptive testing (CAT). This study compared three content balancing methods, namely, the constrained CAT (CCAT), the modified constrained CAT (MCCAT), and the modified multinomial model (MMM), under various conditions of test length and target maximum exposure rate. Results of a series of simulation studies indicate that there is no systematic effect of content balancing method in measurement efficiency and pool utilization. However, among the three methods, the MMM appears to consistently over-expose fewer items.1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/computerized-adaptive-testing-comparison-three-content-balancing-methods00449nas a2200121 4500008004100000245007200041210006900113300001200182490000700194100001500201700001200216856009900228 2003 eng d00aComputerized adaptive testing using the nearest-neighbors criterion0 aComputerized adaptive testing using the nearestneighbors criteri a204-2160 v271 aCheng, P E1 aLiou, M uhttp://www.iacat.org/content/computerized-adaptive-testing-using-nearest-neighbors-criterion-001931nas a2200229 4500008004100000245007200041210006900113300001200182490000700194520116000201653001801361653002101379653003001400653001801430653002501448653002501473653005701498653002201555100001501577700001201592856009701604 2003 eng d00aComputerized adaptive testing using the nearest-neighbors criterion0 aComputerized adaptive testing using the nearestneighbors criteri a204-2160 v273 aItem selection procedures designed for computerized adaptive testing need to accurately estimate every taker's trait level (θ) and, at the same time, effectively use all items in a bank. Empirical studies showed that classical item selection procedures based on maximizing Fisher or other related information yielded highly varied item exposure rates; with these procedures, some items were frequently used whereas others were rarely selected. In the literature, methods have been proposed for controlling exposure rates; they tend to affect the accuracy in θ estimates, however. A modified version of the maximum Fisher information (MFI) criterion, coined the nearest neighbors (NN) criterion, is proposed in this study. The NN procedure improves to a moderate extent the undesirable item exposure rates associated with the MFI criterion and keeps sufficient precision in estimates. The NN criterion will be compared with a few other existing methods in an empirical study using the mean squared errors in θ estimates and plots of item exposure rates associated with different distributions. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10a(Statistical)10aAdaptive Testing10aComputer Assisted Testing10aItem Analysis10aItem Response Theory10aStatistical Analysis10aStatistical Estimation computerized adaptive testing10aStatistical Tests1 aCheng, P E1 aLiou, M uhttp://www.iacat.org/content/computerized-adaptive-testing-using-nearest-neighbors-criterion01591nas a2200145 4500008004100000245005200041210005200093300001200145490000700157520113200164653003401296100001601330700002301346856007601369 2003 eng d00aComputerized adaptive testing with item cloning0 aComputerized adaptive testing with item cloning a247-2610 v273 a(from the journal abstract) To increase the number of items available for adaptive testing and reduce the cost of item writing, the use of techniques of item cloning has been proposed. An important consequence of item cloning is possible variability between the item parameters. To deal with this variability, a multilevel item response (IRT) model is presented which allows for differences between the distributions of item parameters of families of item clones. A marginal maximum likelihood and a Bayesian procedure for estimating the hyperparameters are presented. In addition, an item-selection procedure for computerized adaptive testing with item cloning is presented which has the following two stages: First, a family of item clones is selected to be optimal at the estimate of the person parameter. Second, an item is randomly selected from the family for administration. Results from simulation studies based on an item pool from the Law School Admission Test (LSAT) illustrate the accuracy of these item pool calibration and adaptive testing procedures. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGlas, C A W1 avan der Linden, WJ uhttp://www.iacat.org/content/computerized-adaptive-testing-item-cloning00463nas a2200109 4500008004100000245008200041210006900123260001500192100002300207700001800230856010500248 2003 eng d00aConstraining item exposure in computerized adaptive testing with shadow tests0 aConstraining item exposure in computerized adaptive testing with aChicago IL1 avan der Linden, WJ1 aVeldkamp, B P uhttp://www.iacat.org/content/constraining-item-exposure-computerized-adaptive-testing-shadow-tests-000466nas a2200121 4500008004100000245007000041210006900111260001500180100001300195700001600208700002300224856009700247 2003 eng d00aConstructing rotating item pools for constrained adaptive testing0 aConstructing rotating item pools for constrained adaptive testin aChicago IL1 aAriel, A1 aVeldkamp, B1 avan der Linden, WJ uhttp://www.iacat.org/content/constructing-rotating-item-pools-constrained-adaptive-testing-000443nas a2200097 4500008004100000245008400041210006900125100002300194700001800217856011000235 2003 eng d00aControlling item exposure and item eligibility in computerized adaptive testing0 aControlling item exposure and item eligibility in computerized a1 avan der Linden, WJ1 aVeldkamp, B P uhttp://www.iacat.org/content/controlling-item-exposure-and-item-eligibility-computerized-adaptive-testing00493nas a2200097 4500008004100000245013500041210006900176260001500245100001600260856011900276 2003 eng d00aCriterion item characteristic curve function for evaluating the differential weight procedure adjusted to on-line item calibration0 aCriterion item characteristic curve function for evaluating the  aChicago IL1 aSamejima, F uhttp://www.iacat.org/content/criterion-item-characteristic-curve-function-evaluating-differential-weight-procedure01804nas a2200277 4500008004100000245007600041210006900117300001100186490000600197520090300203653001501106653002901121653003001150653002001180653001101200653005001211653001801261653003201279653004101311653001801352100001401370700001301384700001301397700001901410856009701429 2003 eng d00aDeveloping an initial physical function item bank from existing sources0 aDeveloping an initial physical function item bank from existing  a124-360 v43 aThe objective of this article is to illustrate incremental item banking using health-related quality of life data collected from two samples of patients receiving cancer treatment. The kinds of decisions one faces in establishing an item bank for computerized adaptive testing are also illustrated. Pre-calibration procedures include: identifying common items across databases; creating a new database with data from each pool; reverse-scoring "negative" items; identifying rating scales used in items; identifying pivot points in each rating scale; pivot anchoring items at comparable rating scale categories; and identifying items in each instrument that measure the construct of interest. A series of calibrations were conducted in which a small proportion of new items were added to the common core and misfitting items were identified and deleted until an initial item bank has been developed.10a*Databases10a*Sickness Impact Profile10aAdaptation, Psychological10aData Collection10aHumans10aNeoplasms/*physiopathology/psychology/therapy10aPsychometrics10aQuality of Life/*psychology10aResearch Support, U.S. Gov't, P.H.S.10aUnited States1 aBode, R K1 aCella, D1 aLai, J S1 aHeinemann, A W uhttp://www.iacat.org/content/developing-initial-physical-function-item-bank-existing-sources00509nas a2200121 4500008004100000245009900041210006900140100001300209700001600222700001800238700001500256856011600271 2003 eng d00aDevelopment and psychometric evaluation of the Flexilevel Scale of Shoulder Function (FLEX-SF)0 aDevelopment and psychometric evaluation of the Flexilevel Scale 1 aCook, KF1 aRoddey, T S1 aGartsman, G M1 aOlson, S L uhttp://www.iacat.org/content/development-and-psychometric-evaluation-flexilevel-scale-shoulder-function-flex-sf00385nas a2200085 4500008004100000245007700041210006900118100001500187856009700202 2003 eng d00aDevelopment of the Learning Potential Computerised Adaptive Test (LPCAT)0 aDevelopment of the Learning Potential Computerised Adaptive Test1 aDe Beer, M uhttp://www.iacat.org/content/development-learning-potential-computerised-adaptive-test-lpcat02792nas a2200121 4500008004100000245013500041210006900176300000900245490000700254520226900261100001502530856012502545 2003 eng d00aDevelopment, reliability, and validity of a computerized adaptive version of the Schedule for Nonadaptive and Adaptive Personality0 aDevelopment reliability and validity of a computerized adaptive  a34850 v633 aComputerized adaptive testing (CAT) and Item Response Theory (IRT) techniques were applied to the Schedule for Nonadaptive and Adaptive Personality (SNAP) to create a more efficient measure with little or no cost to test reliability or validity. The SNAP includes 15 factor analytically derived and relatively unidimensional traits relevant to personality disorder. IRT item parameters were calibrated on item responses from a sample of 3,995 participants who completed the traditional paper-and-pencil (P&P) SNAP in a variety of university, community, and patient settings. Computerized simulations were conducted to test various adaptive testing algorithms, and the results informed the construction of the CAT version of the SNAP (SNAP-CAT). A validation study of the SNAP-CAT was conducted on a sample of 413 undergraduates who completed the SNAP twice, separated by one week. Participants were randomly assigned to one of four groups who completed (1) a modified P&P version of the SNAP (SNAP-PP) twice (n = 106), (2) the SNAP-PP first and the SNAP-CAT second (n = 105), (3) the SNAP-CAT first and the SNAP-PP second (n = 102), and (4) the SNAP-CAT twice (n = 100). Results indicated that the SNAP-CAT was 58% and 60% faster than the traditional P&P version, at Times 1 and 2, respectively, and mean item savings across scales were 36% and 37%, respectively. These savings came with minimal cost to reliability or validity, and the two test forms were largely equivalent. Descriptive statistics, rank-ordering of scores, internal factor structure, and convergent/discriminant validity were highly comparable across testing modes and methods of scoring, and very few differences between forms replicated across testing sessions. In addition, participants overwhelmingly preferred the computerized version to the P&P version. However, several specific problems were identified for the Self-harm and Propriety scales of the SNAP-CAT that appeared to be broadly related to IRT calibration difficulties. Reasons for these anomalous findings are discussed, and follow-up studies are suggested. Despite these specific problems, the SNAP-CAT appears to be a viable alternative to the traditional P&P SNAP. (PsycINFO Database Record (c) 2003 APA, all rights reserved).1 aSimms, L J uhttp://www.iacat.org/content/development-reliability-and-validity-computerized-adaptive-version-schedule-nonadaptive-and00527nas a2200121 4500008003900000245008900039210007000128260004600198100001700244700001300261700001700274856011400291 2003 d00aEffect of extra time on GRE® Quantitative and Verbal Scores (Research Report 03-13)0 aEffect of extra time on GRE® Quantitative and Verbal Scores Rese aPrinceton NJ: Educational Testing service1 aBridgeman, B1 aCline, F1 aHessinger, J uhttp://www.iacat.org/content/effect-extra-time-gre%C2%AE-quantitative-and-verbal-scores-research-report-03-1300545nas a2200109 4500008004100000245015000041210006900191260001500260100001200275700001700287856013100304 2003 eng d00aThe effect of item selection method on the variability of CAT’s ability estimates when item parameters are contaminated with measurement errors0 aeffect of item selection method on the variability of CAT s abil aChicago IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/effect-item-selection-method-variability-cat%E2%80%99s-ability-estimates-when-item-parameters-are00501nas a2200109 4500008004100000245006800041210006400109260010600173100001200279700001300291856008700304 2003 eng d00aThe effects of model misfit in computerized classification test0 aeffects of model misfit in computerized classification test aPaper presented at the annual meeting of the National Council on Measurement in Education, Chicago IL1 aJiao, H1 aLau, A C uhttp://www.iacat.org/content/effects-model-misfit-computerized-classification-test02705nas a2200121 4500008004100000245014800041210006900189300000800258490000700266520217600273100001202449856012202461 2003 eng d00aThe effects of model specification error in item response theory-based computerized classification test using sequential probability ratio test0 aeffects of model specification error in item response theorybase a4780 v643 aThis study investigated the effects of model specification error on classification accuracy, error rates, and average test length in Item Response Theory (IRT) based computerized classification test (CCT) using sequential probability ratio test (SPRT) in making binary decisions from examinees' dichotomous responses. This study consisted of three sub-studies. In each sub-study, one of the three unidimensional dichotomous IRT models, the 1-parameter logistic (IPL), the 2-parameter logistic (2PL), and the 3-parameter logistic (3PL) model was set as the true model and the other two models were treated as the misfit models. Item pool composition, test length, and stratum depth were manipulated to simulate different test conditions. To ensure the validity of the study results, the true model based CCTs using the true and the recalibrated item parameters were compared first to study the effect of estimation error in item parameters in CCTs. Then, the true model and the misfit model based CCTs were compared to accomplish the research goal, The results indicated that estimation error in item parameters did not affect classification results based on CCTs using SPRT. The effect of model specification error depended on the true model, the misfit model, and the item pool composition. When the IPL or the 2PL IRT model was the true model, the use of another IRT model had little impact on the CCT results. When the 3PL IRT model was the true model, the use of the 1PL model raised the false positive error rates. The influence of using the 2PL instead of the 3PL model depended on the item pool composition. When the item discrimination parameters varied greatly from uniformity of one, the use of the 2PL IRT model raised the false negative error rates to above the nominal level. In the simulated test conditions with test length and item exposure constraints, using a misfit model in CCTs most often affected the average test length. Its effects on error rates and classification accuracy were negligible. It was concluded that in CCTs using SPRT, IRT model selection and evaluation is indispensable (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aJiao, H uhttp://www.iacat.org/content/effects-model-specification-error-item-response-theory-based-computerized-classification00468nas a2200133 4500008004100000245006800041210006800109260001500177100001000192700001600202700001200218700001300230856009100243 2003 eng d00aEffects of test administration mode on item parameter estimates0 aEffects of test administration mode on item parameter estimates aChicago IL1 aYi, Q1 aHarris, D J1 aWang, T1 aBan, J-C uhttp://www.iacat.org/content/effects-test-administration-mode-item-parameter-estimates00408nas a2200109 4500008004100000245006600041210006600107260001500173100001000188700001300198856008700211 2003 eng d00aEvaluating a new approach to detect aberrant responses in CAT0 aEvaluating a new approach to detect aberrant responses in CAT aChicago IL1 aLu, Y1 aRobin, F uhttp://www.iacat.org/content/evaluating-new-approach-detect-aberrant-responses-cat00440nas a2200109 4500008004100000245007800041210006900119260001500188100001300203700001000216856010400226 2003 eng d00aEvaluating computer-based test security by generalized item overlap rates0 aEvaluating computerbased test security by generalized item overl aChicago IL1 aZhang, J1 aLu, T uhttp://www.iacat.org/content/evaluating-computer-based-test-security-generalized-item-overlap-rates00545nas a2200145 4500008004100000245009500041210006900136260001500205100001000220700001600230700001400246700001300260700001500273856011100288 2003 eng d00aEvaluating computerized adaptive testing design for the MCAT with realistic simulated data0 aEvaluating computerized adaptive testing design for the MCAT wit aChicago IL1 aLu, Y1 aPitoniak, M1 aRizavi, S1 aWay, W D1 aSteffan, M uhttp://www.iacat.org/content/evaluating-computerized-adaptive-testing-design-mcat-realistic-simulated-data00424nas a2200097 4500008004100000245007800041210006900119260001500188100001900203856010400222 2003 eng d00aEvaluating stability of online item calibrations under varying conditions0 aEvaluating stability of online item calibrations under varying c aChicago IL1 aThomasson, G L uhttp://www.iacat.org/content/evaluating-stability-online-item-calibrations-under-varying-conditions00524nas a2200109 4500008004100000245014200041210006900183260001500252100001300267700001300280856012100293 2003 eng d00aEvaluating the comparability of English- and French-speaking examinees on a science achievement test administered using two-stage testing0 aEvaluating the comparability of English and Frenchspeaking exami aChicago IL1 aPuhan, G1 aGierl, M uhttp://www.iacat.org/content/evaluating-comparability-english-and-french-speaking-examinees-science-achievement-test00431nas a2200109 4500008003900000245007600039210006900115260001500184100001600199700001800215856008800233 2003 d00aThe evaluation of exposure control procedures for an operational CAT. 0 aevaluation of exposure control procedures for an operational CAT aChicago IL1 aFrench, B F1 aThompson, T T uhttp://www.iacat.org/content/evaluation-exposure-control-procedures-operational-cat01816nas a2200253 4500008004100000245013100041210006900172300001000241490000600251520095700257653001501214653002901229653002501258653001501283653002001298653001101318653003101329100001401360700001601374700001401390700001401404700002101418856012301439 2003 eng d00aAn examination of exposure control and content balancing restrictions on item selection in CATs using the partial credit model0 aexamination of exposure control and content balancing restrictio a24-420 v43 aThe purpose of the present investigation was to systematically examine the effectiveness of the Sympson-Hetter technique and rotated content balancing relative to no exposure control and no content rotation conditions in a computerized adaptive testing system (CAT) based on the partial credit model. A series of simulated fixed and variable length CATs were run using two data sets generated to multiple content areas for three sizes of item pools. The 2 (exposure control) X 2 (content rotation) X 2 (test length) X 3 (item pool size) X 2 (data sets) yielded a total of 48 conditions. Results show that while both procedures can be used with no deleterious effect on measurement precision, the gains in exposure control, pool utilization, and item overlap appear quite modest. Difficulties involved with setting the exposure control parameters in small item pools make questionable the utility of the Sympson-Hetter technique with similar item pools.10a*Computers10a*Educational Measurement10a*Models, Theoretical10aAutomation10aDecision Making10aHumans10aReproducibility of Results1 aDavis, LL1 aPastor, D A1 aDodd, B G1 aChiang, C1 aFitzpatrick, S J uhttp://www.iacat.org/content/examination-exposure-control-and-content-balancing-restrictions-item-selection-cats-using00386nas a2200097 4500008004100000245006100041210006000102260002100162100001500183856009000198 2003 eng d00aExposure control using adaptive multi-stage item bundles0 aExposure control using adaptive multistage item bundles aChicago, IL. USA1 aLuecht, RM uhttp://www.iacat.org/content/exposure-control-using-adaptive-multi-stage-item-bundles00382nas a2200097 4500008004100000245006100041210006000102260001500162100001500177856009200192 2003 eng d00aExposure control using adaptive multi-stage item bundles0 aExposure control using adaptive multistage item bundles aChicago IL1 aLuecht, RM uhttp://www.iacat.org/content/exposure-control-using-adaptive-multi-stage-item-bundles-003166nas a2200361 4500008004100000245012500041210006900166300001200235490000700247520200400254653002902258653001502287653001002302653000902312653002202321653002002343653003302363653002402396653001102420653001002431653000902441653001602450653002502466653002602491653004302517653003202560653001902592653002802611100001702639700001602656700001402672856011802686 2003 eng d00aThe feasibility of applying item response theory to measures of migraine impact: a re-analysis of three clinical studies0 afeasibility of applying item response theory to measures of migr a887-9020 v123 aBACKGROUND: Item response theory (IRT) is a powerful framework for analyzing multiitem scales and is central to the implementation of computerized adaptive testing. OBJECTIVES: To explain the use of IRT to examine measurement properties and to apply IRT to a questionnaire for measuring migraine impact--the Migraine Specific Questionnaire (MSQ). METHODS: Data from three clinical studies that employed the MSQ-version 1 were analyzed by confirmatory factor analysis for categorical data and by IRT modeling. RESULTS: Confirmatory factor analyses showed very high correlations between the factors hypothesized by the original test constructions. Further, high item loadings on one common factor suggest that migraine impact may be adequately assessed by only one score. IRT analyses of the MSQ were feasible and provided several suggestions as to how to improve the items and in particular the response choices. Out of 15 items, 13 showed adequate fit to the IRT model. In general, IRT scores were strongly associated with the scores proposed by the original test developers and with the total item sum score. Analysis of response consistency showed that more than 90% of the patients answered consistently according to a unidimensional IRT model. For the remaining patients, scores on the dimension of emotional function were less strongly related to the overall IRT scores that mainly reflected role limitations. Such response patterns can be detected easily using response consistency indices. Analysis of test precision across score levels revealed that the MSQ was most precise at one standard deviation worse than the mean impact level for migraine patients that are not in treatment. Thus, gains in test precision can be achieved by developing items aimed at less severe levels of migraine impact. CONCLUSIONS: IRT proved useful for analyzing the MSQ. The approach warrants further testing in a more comprehensive item pool for headache impact that would enable computerized adaptive testing.10a*Sickness Impact Profile10aAdolescent10aAdult10aAged10aComparative Study10aCost of Illness10aFactor Analysis, Statistical10aFeasibility Studies10aFemale10aHuman10aMale10aMiddle Aged10aMigraine/*psychology10aModels, Psychological10aPsychometrics/instrumentation/*methods10aQuality of Life/*psychology10aQuestionnaires10aSupport, Non-U.S. Gov't1 aBjorner, J B1 aKosinski, M1 aWare, Jr. uhttp://www.iacat.org/content/feasibility-applying-item-response-theory-measures-migraine-impact-re-analysis-three00520nas a2200157 4500008004100000245007400041210006900115490000700184100001500191700001200206700001100218700001100229700001800240700001600258856008800274 2003 eng d00aA feasibility study of on-the-fly item generation in adaptive testing0 afeasibility study of onthefly item generation in adaptive testin0 v2 1 aBejar, I I1 aLawless1 aMorley1 aWagner1 aBennett R. E.1 aRevuelta, J uhttp://www.iacat.org/content/feasibility-study-fly-item-generation-adaptive-testing00504nas a2200109 4500008004100000245010400041210006900145260001500214100001800229700002300247856012400270 2003 eng d00aImplementing an alternative to Sympson-Hetter item-exposure control in constrained adaptive testing0 aImplementing an alternative to SympsonHetter itemexposure contro aChicago IL1 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/implementing-alternative-sympson-hetter-item-exposure-control-constrained-adaptive-testing00514nas a2200121 4500008004100000245010300041210006900144300001200213490000700225100002300232700001900255856011800274 2003 eng d00aImplementing content constraints in alpha-stratified adaptive testing using a shadow test approach0 aImplementing content constraints in alphastratified adaptive tes a107-1200 v271 avan der Linden, WJ1 aChang, Hua-Hua uhttp://www.iacat.org/content/implementing-content-constraints-alpha-stratified-adaptive-testing-using-shadow-test00538nas a2200121 4500008004100000245013200041210006900173260001500242100001000257700001200267700001200279856012500291 2003 eng d00aImplementing the a-stratified method with b blocking in computerized adaptive testing with the generalized partial credit model0 aImplementing the astratified method with b blocking in computeri aChicago IL1 aYi, Q1 aWang, T1 aWang, S uhttp://www.iacat.org/content/implementing-stratified-method-b-blocking-computerized-adaptive-testing-generalized-partial01586nas a2200145 4500008003900000245011200039210006900151300001200220490000700232520109100239100002101330700001901351700001701370856005301387 2003 d00aIncorporation Of Content Balancing Requirements In Stratification Designs For Computerized Adaptive Testing0 aIncorporation Of Content Balancing Requirements In Stratificatio a257-2700 v633 a

In computerized adaptive testing, the multistage a-stratified design advocates a new philosophy on pool management and item selection in which, contradictory to common practice, less discriminating items are used first. The method is effective in reducing item-overlap rate and enhancing pool utilization. This stratification method has been extended in different ways to deal with the practical issues of content constraints and the positive correlation between item difficulty and discrimination. Nevertheless, these modified designs on their own do not automatically satisfy content requirements. In this study, three stratification designs were examined in conjunction with three well developed content balancing methods. The performance of each of these nine combinational methods was evaluated in terms of their item security, measurement efficiency, and pool utilization. Results showed substantial differences in item-overlap rate and pool utilization among different methods. An optimal combination of stratification design and content balancing method is recommended.

1 aLeung, Chi-Keung1 aChang, Hua-Hua1 aHau, Kit-Tai uhttp://epm.sagepub.com/content/63/2/257.abstract00961nas a2200157 4500008004100000245011200041210006900153300001100222490000700233520035900240653003400599100001500633700001900648700001300667856012300680 2003 eng d00aIncorporation of Content Balancing Requirements in Stratification Designs for Computerized Adaptive Testing0 aIncorporation of Content Balancing Requirements in Stratificatio a257-700 v633 aStudied three stratification designs for computerized adaptive testing in conjunction with three well-developed content balancing methods. Simulation study results show substantial differences in item overlap rate and pool utilization among different methods. Recommends an optimal combination of stratification design and content balancing method. (SLD)10acomputerized adaptive testing1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/incorporation-content-balancing-requirements-stratification-designs-computerized-adaptive00537nas a2200109 4500008004100000245014400041210006900185260001500254100001200269700001700281856012900298 2003 eng d00aIncreasing the homogeneity of CAT’s item-exposure rates by minimizing or maximizing varied target functions while assembling shadow tests0 aIncreasing the homogeneity of CAT s itemexposure rates by minimi aChicago IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/increasing-homogeneity-cat%E2%80%99s-item-exposure-rates-minimizing-or-maximizing-varied-target00366nas a2200097 4500008004100000245005500041210005500096260002000151100001600171856008100187 2003 eng d00aInformation theoretic approaches to item selection0 aInformation theoretic approaches to item selection aSardinia, Italy1 aWeissman, A uhttp://www.iacat.org/content/information-theoretic-approaches-item-selection00377nas a2200097 4500008004100000245006200041210006100103260001500164100002000179856008000199 2003 eng d00aIssues in maintaining scale consistency for the CAT-ASVAB0 aIssues in maintaining scale consistency for the CATASVAB aChicago IL1 aNicewander, W A uhttp://www.iacat.org/content/issues-maintaining-scale-consistency-cat-asvab02748nas a2200349 4500008004100000245015800041210006900199260000800268300001200276490000700288520160300295653003001898653002001928653001001948653003201958653001101990653001102001653000902012653001602021653002802037653001802065653003702083653004102120653002802161100001302189700001502202700001302217700001502230700001402245700001902259856012002278 2003 eng d00aItem banking to improve, shorten and computerized self-reported fatigue: an illustration of steps to create a core item bank from the FACIT-Fatigue Scale0 aItem banking to improve shorten and computerized selfreported fa cAug a485-5010 v123 aFatigue is a common symptom among cancer patients and the general population. Due to its subjective nature, fatigue has been difficult to effectively and efficiently assess. Modern computerized adaptive testing (CAT) can enable precise assessment of fatigue using a small number of items from a fatigue item bank. CAT enables brief assessment by selecting questions from an item bank that provide the maximum amount of information given a person's previous responses. This article illustrates steps to prepare such an item bank, using 13 items from the Functional Assessment of Chronic Illness Therapy Fatigue Subscale (FACIT-F) as the basis. Samples included 1022 cancer patients and 1010 people from the general population. An Item Response Theory (IRT)-based rating scale model, a polytomous extension of the Rasch dichotomous model was utilized. Nine items demonstrating acceptable psychometric properties were selected and positioned on the fatigue continuum. The fatigue levels measured by these nine items along with their response categories covered 66.8% of the general population and 82.6% of the cancer patients. Although the operational CAT algorithms to handle polytomously scored items are still in progress, we illustrated how CAT may work by using nine core items to measure level of fatigue. Using this illustration, a fatigue measure comparable to its full-length 13-item scale administration was obtained using four items. The resulting item bank can serve as a core to which will be added a psychometrically sound and operational item bank covering the entire fatigue continuum.10a*Health Status Indicators10a*Questionnaires10aAdult10aFatigue/*diagnosis/etiology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/complications10aPsychometrics10aResearch Support, Non-U.S. Gov't10aResearch Support, U.S. Gov't, P.H.S.10aSickness Impact Profile1 aLai, J-S1 aCrane, P K1 aCella, D1 aChang, C-H1 aBode, R K1 aHeinemann, A W uhttp://www.iacat.org/content/item-banking-improve-shorten-and-computerized-self-reported-fatigue-illustration-steps01747nas a2200217 4500008004100000245008700041210006900128300001200197490000700209520100200216653002101218653003001239653002601269653002501295653002001320653001401340653004901354100001401403700001401417856009801431 2003 eng d00aItem exposure constraints for testlets in the verbal reasoning section of the MCAT0 aItem exposure constraints for testlets in the verbal reasoning s a335-3560 v273 aThe current study examined item exposure control procedures for testlet scored reading passages in the Verbal Reasoning section of the Medical College Admission Test with four computerized adaptive testing (CAT) systems using the partial credit model. The first system used a traditional CAT using maximum information item selection. The second used random item selection to provide a baseline for optimal exposure rates. The third used a variation of Lunz and Stahl's randomization procedure. The fourth used Luecht and Nungester's computerized adaptive sequential testing (CAST) system. A series of simulated fixed-length CATs was run to determine the optimal item length selection procedure. Results indicated that both the randomization procedure and CAST performed well in terms of exposure control and measurement precision, with the CAST system providing the best overall solution when all variables were taken into consideration. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aEntrance Examinations10aItem Response Theory10aRandom Sampling10aReasoning10aVerbal Ability computerized adaptive testing1 aDavis, LL1 aDodd, B G uhttp://www.iacat.org/content/item-exposure-constraints-testlets-verbal-reasoning-section-mcat00355nas a2200097 4500008004100000245005300041210005300094260001500147100001700162856007800179 2003 eng d00aItem pool design for computerized adaptive tests0 aItem pool design for computerized adaptive tests aChicago IL1 aReckase, M D uhttp://www.iacat.org/content/item-pool-design-computerized-adaptive-tests00448nas a2200097 4500008004100000245003700041210003700078260015200115100001800267856006500285 2003 eng d00aItem selection in polytomous CAT0 aItem selection in polytomous CAT aH. Yanai, A. Okada, K. Shigemasu, Y Kano, and J. J. Meulman (eds.), New developments in psychometrics (pp. 207-214). Tokyo, Japan: Springer-Verlag.1 aVeldkamp, B P uhttp://www.iacat.org/content/item-selection-polytomous-cat-000520nas a2200169 4500008004100000245003700041210003700078260004900115300001400164653003400178100001800212700001300230700001700243700001200260700001500272856006300287 2003 eng d00aItem selection in polytomous CAT0 aItem selection in polytomous CAT aTokyo, JapanbPsychometric Society, Springer a207–21410acomputerized adaptive testing1 aVeldkamp, B P1 aOkada, A1 aShigenasu, K1 aKano, Y1 aMeulman, J uhttp://www.iacat.org/content/item-selection-polytomous-cat00452nas a2200145 4500008004100000245005100041210005100092260001500143100001500158700001400173700001200187700001500199700001500214856007700229 2003 eng d00aMaintaining scale in computer adaptive testing0 aMaintaining scale in computer adaptive testing aChicago IL1 aSmith, R L1 aRizavi, S1 aPaez, R1 aDamiano, M1 aHerbert, E uhttp://www.iacat.org/content/maintaining-scale-computer-adaptive-testing00424nas a2200109 4500008004100000245006500041210006200106260002700168100001900195700001500214856008500229 2003 eng d00aA method to determine targets for multi-stage adaptive tests0 amethod to determine targets for multistage adaptive tests aUnpublished manuscript1 aArmstrong, R D1 aRoussos, L uhttp://www.iacat.org/content/method-determine-targets-multi-stage-adaptive-tests00377nas a2200109 4500008004100000245005500041210005500096260001500151100001000166700001400176856007700190 2003 eng d00aMethods for item set selection in adaptive testing0 aMethods for item set selection in adaptive testing aChicago IL1 aLu, Y1 aRizavi, S uhttp://www.iacat.org/content/methods-item-set-selection-adaptive-testing00489nas a2200109 4500008004100000245009900041210006900140260001600209100001200225700001700237856012500254 2003 eng d00aMultidimensional computerized adaptive testing in recovering reading and mathematics abilities0 aMultidimensional computerized adaptive testing in recovering rea aChicago, IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-recovering-reading-and-mathematics-abilities00521nas a2200097 4500008004100000245008500041210006900126260010600195100001400301856010800315 2003 eng d00aA multidimensional IRT mechanism for better understanding adaptive test behavior0 amultidimensional IRT mechanism for better understanding adaptive aPaper presented at the annual meeting of the National Council on Measurement in Education, Chicago IL1 aJodoin, M uhttp://www.iacat.org/content/multidimensional-irt-mechanism-better-understanding-adaptive-test-behavior00393nas a2200109 4500008004100000245006000041210006000101260001500161100001100176700001200187856008400199 2003 eng d00aOnline calibration and scale stability of a CAT program0 aOnline calibration and scale stability of a CAT program aChicago IL1 aGuo, F1 aWang, G uhttp://www.iacat.org/content/online-calibration-and-scale-stability-cat-program00427nas a2200109 4500008004100000245007600041210006900117300001100186490000700197100001400204856009900218 2003 eng d00aAn optimal design approach to criterion-referenced computerized testing0 aoptimal design approach to criterionreferenced computerized test a97-1000 v281 aWiberg, M uhttp://www.iacat.org/content/optimal-design-approach-criterion-referenced-computerized-testing01436nas a2200205 4500008004100000245008800041210007000129300001200199490000700211520067700218653002100895653003000916653002400946653002500970653002600995653005201021100001901073700002301092856011501115 2003 eng d00aOptimal stratification of item pools in α-stratified computerized adaptive testing0 aOptimal stratification of item pools in αstratified computerized a262-2740 v273 aA method based on 0-1 linear programming (LP) is presented to stratify an item pool optimally for use in α-stratified adaptive testing. Because the 0-1 LP model belongs to the subclass of models with a network flow structure, efficient solutions are possible. The method is applied to a previous item pool from the computerized adaptive testing (CAT) version of the Graduate Record Exams (GRE) Quantitative Test. The results indicate that the new method performs well in practical situations. It improves item exposure control, reduces the mean squared error in the θ estimates, and increases test reliability. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aItem Content (Test)10aItem Response Theory10aMathematical Modeling10aTest Construction computerized adaptive testing1 aChang, Hua-Hua1 avan der Linden, WJ uhttp://www.iacat.org/content/optimal-stratification-item-pools-%CE%B1-stratified-computerized-adaptive-testing00430nas a2200109 4500008004100000245006900041210006900110260001800179100001600197700001700213856009000230 2003 eng d00aOptimal testing with easy items in computerized adaptive testing0 aOptimal testing with easy items in computerized adaptive testing aManchester UK1 aEggen, Theo1 aVerschoor, A uhttp://www.iacat.org/content/optimal-testing-easy-items-computerized-adaptive-testing00436nas a2200109 4500008004100000245007300041210006900114260001500183100001400198700001300212856010100225 2003 eng d00aPredicting item exposure parameters in computerized adaptive testing0 aPredicting item exposure parameters in computerized adaptive tes aChicago IL1 aChen, S-Y1 aDoong, H uhttp://www.iacat.org/content/predicting-item-exposure-parameters-computerized-adaptive-testing-000524nas a2200133 4500008004100000245009600041210006900137300001200206490000700218100001600225700001800241700001200259856011900271 2003 eng d00aPsychometric and psychological effects of item selection and review on computerized testing0 aPsychometric and psychological effects of item selection and rev a791-8080 v631 aRevuelta, J1 aXiménez, M C1 aOlea, J uhttp://www.iacat.org/content/psychometric-and-psychological-effects-item-selection-and-review-computerized-testing01785nas a2200145 4500008003900000245009600039210006900135300001200204490000700216520130200223100002101525700002401546700001601570856005301586 2003 d00aPsychometric and Psychological Effects of Item Selection and Review on Computerized Testing0 aPsychometric and Psychological Effects of Item Selection and Rev a791-8080 v633 a

Psychometric properties of computerized testing, together with anxiety and comfort of examinees, are investigated in relation to item selection routine and the opportunity for response review. Two different hypotheses involving examinee anxiety were used to design test properties: perceived control and perceived performance. The study involved three types of administration of a computerized English test for Spanish speakers (adaptive, easy adaptive, and fixed) and four review conditions (no review, review at end, review by blocks of 5 items, and review item-by-item). These were applied to a sample of 557 first-year psychology undergraduate students to examine main and interaction effects of test type and review on psychometric and psychological variables. Statistically significant effects were found in test precision among the different types of test. Response review improved ability estimates and increased testing time. No psychological effects on anxiety were found. Examinees in all review conditions considered more important the possibility of review than those who were not allowed to review. These results concur with previous findings on examinees' preference for item review and raise some issues that should be addressed in the field of tests with item review.

1 aRevuelta, Javier1 aXiménez, Carmen, M1 aOlea, Julio uhttp://epm.sagepub.com/content/63/5/791.abstract02714nas a2200121 4500008004100000245010500041210006900146300000900215490000700224520221900231100001602450856012602466 2003 eng d00aPsychometric properties of several computer-based test designs with ideal and constrained item pools0 aPsychometric properties of several computerbased test designs wi a29780 v643 aThe purpose of this study was to compare linear fixed length test (LFT), multi stage test (MST), and computer adaptive test (CAT) designs under three levels of item pool quality, two levels of match between test and item pool content specifications, two levels of test length, and several levels of exposure control expected to be practical for a number of testing programs. This design resulted in 132 conditions that were evaluated using a simulation study with 9000 examinees on several measures of overall measurement precision including reliability, the mean error and root mean squared error between true and estimated ability levels, classification precision including decision accuracy, false positive and false negative rates, and Kappa for cut scores corresponding to 30%, 50%, and 85% failure rates, and conditional measurement precision with the conditional root mean squared error between true and estimated ability levels conditioned on 25 true ability levels. Test reliability, overall and conditional measurement precision, and classification precision increased with item pool quality and test length, and decreased with less adequate match between item pool and test specification match. In addition, as the maximum exposure rate decreased and the type of exposure control implemented became more restrictive, test reliability, overall and conditional measurement precision, and classification precision decreased. Within item pool quality, match between test and item pool content specifications, test length, and exposure control, CAT designs showed superior psychometric properties as compared to MST designs which in turn were superior to LFT designs. However, some caution is warranted in interpreting these results since the ability of the automated test assembly software to construct test that met specifications was limited in conditions where pool usage was high. The practical importance of the differences between test designs on the evaluation criteria studied is discussed with respect to the inferences test users seek to make from test scores and nonpsychometric factors that may be important in some testing programs. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aJodoin, M G uhttp://www.iacat.org/content/psychometric-properties-several-computer-based-test-designs-ideal-and-constrained-item-pools00516nas a2200121 4500008004100000245009800041210006900139260001500208100001600223700001800239700001700257856012000274 2003 eng d00aRecalibration of IRT item parameters in CAT: Sparse data matrices and missing data treatments0 aRecalibration of IRT item parameters in CAT Sparse data matrices aChicago IL1 aHarmes, J C1 aParshall, C G1 aKromrey, J D uhttp://www.iacat.org/content/recalibration-irt-item-parameters-cat-sparse-data-matrices-and-missing-data-treatments01801nas a2200241 4500008004100000245009300041210006900134300001200203490000700215520098200222653001801204653002101222653003001243653001901273653004601292653001801338653002501356653001501381100001401396700001901410700001501429856011501444 2003 eng d00aThe relationship between item exposure and test overlap in computerized adaptive testing0 arelationship between item exposure and test overlap in computeri a129-1450 v403 aThe purpose of this article is to present an analytical derivation for the mathematical form of an average between-test overlap index as a function of the item exposure index, for fixed-length computerized adaptive tests (CATs). This algebraic relationship is used to investigate the simultaneous control of item exposure at both the item and test levels. The results indicate that, in fixed-length CATs, control of the average between-test overlap is achieved via the mean and variance of the item exposure rates of the items that constitute the CAT item pool. The mean of the item exposure rates is easily manipulated. Control over the variance of the item exposure rates can be achieved via the maximum item exposure rate (r-sub(max)). Therefore, item exposure control methods which implement a specification of r-sub(max) (e.g., J. B. Sympson and R. D. Hetter, 1985) provide the most direct control at both the item and test levels. (PsycINFO Database Record (c) 2005 APA )10a(Statistical)10aAdaptive Testing10aComputer Assisted Testing10aHuman Computer10aInteraction computerized adaptive testing10aItem Analysis10aItem Analysis (Test)10aTest Items1 aChen, S-Y1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/relationship-between-item-exposure-and-test-overlap-computerized-adaptive-testing00519nas a2200133 4500008004100000245009300041210006900134300001200203490000700215100001200222700001900234700001500253856011700268 2003 eng d00aThe relationship between item exposure and test overlap in computerized adaptive testing0 arelationship between item exposure and test overlap in computeri a129-1450 v401 aChen, S1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/relationship-between-item-exposure-and-test-overlap-computerized-adaptive-testing-000519nas a2200133 4500008004100000245009300041210006900134300001200203490000700215100001200222700001900234700001500253856011700268 2003 eng d00aThe relationship between item exposure and test overlap in computerized adaptive testing0 arelationship between item exposure and test overlap in computeri a129-1450 v401 aChen, S1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/relationship-between-item-exposure-and-test-overlap-computerized-adaptive-testing-100465nas a2200109 4500008004100000245007700041210006900118260003000187100002300217700001800240856009700258 2003 eng d00aA sequential Bayes procedure for item calibration in multi-stage testing0 asequential Bayes procedure for item calibration in multistage te aManuscript in preparation1 avan der Linden, WJ1 aMead, Alan, D uhttp://www.iacat.org/content/sequential-bayes-procedure-item-calibration-multi-stage-testing00457nas a2200121 4500008004100000245007300041210006900114260001500183100001000198700001900208700001500227856009300242 2003 eng d00aA simulation study to compare CAT strategies for cognitive diagnosis0 asimulation study to compare CAT strategies for cognitive diagnos aChicago IL1 aXu, X1 aChang, Hua-Hua1 aDouglas, J uhttp://www.iacat.org/content/simulation-study-compare-cat-strategies-cognitive-diagnosis01711nas a2200169 4500008004100000245015800041210006900199300001000268490000700278520105400285100001901339700001801358700001601376700001201392700001601404856012101420 2003 eng d00aSmall sample estimation in dichotomous item response models: Effect of priors based on judgmental information on the accuracy of item parameter estimates0 aSmall sample estimation in dichotomous item response models Effe a27-510 v273 aLarge item banks with properly calibrated test items are essential for ensuring the validity of computer-based tests. At the same time, item calibrations with small samples are desirable to minimize the amount of pretesting and limit item exposure. Bayesian estimation procedures show considerable promise with small examinee samples. The purposes of the study were (a) to examine how prior information for Bayesian item parameter estimation can be specified and (b) to investigate the relationship between sample size and the specification of prior information on the accuracy of item parameter estimates. The results of the simulation study were clear: Estimation of item response theory (IRT) model item parameters can be improved considerably. Improvements in the one-parameter model were modest; considerable improvements with the two- and three-parameter models were observed. Both the study of different forms of priors and ways to improve the judgmental data used in forming the priors appear to be promising directions for future research. 1 aSwaminathan, H1 aHambleton, RK1 aSireci, S G1 aXing, D1 aRizavi, S M uhttp://www.iacat.org/content/small-sample-estimation-dichotomous-item-response-models-effect-priors-based-judgmental01520nas a2200157 4500008004100000245009500041210006900136300001200205490000700217520090100224653002101125653003001146653004501176100002301221856011801244 2003 eng d00aSome alternatives to Sympson-Hetter item-exposure control in computerized adaptive testing0 aSome alternatives to SympsonHetter itemexposure control in compu a249-2650 v283 aTheHetter and Sympson (1997; 1985) method is a method of probabilistic item-exposure control in computerized adaptive testing. Setting its control parameters to admissible values requires an iterative process of computer simulations that has been found to be time consuming, particularly if the parameters have to be set conditional on a realistic set of values for the examinees’ ability parameter. Formal properties of the method are identified that help us explain why this iterative process can be slow and does not guarantee admissibility. In addition, some alternatives to the SH method are introduced. The behavior of these alternatives was estimated for an adaptive test from an item pool from the Law School Admission Test (LSAT). Two of the alternatives showed attractive behavior and converged smoothly to admissibility for all items in a relatively small number of iteration steps. 10aAdaptive Testing10aComputer Assisted Testing10aTest Items computerized adaptive testing1 avan der Linden, WJ uhttp://www.iacat.org/content/some-alternatives-sympson-hetter-item-exposure-control-computerized-adaptive-testing00403nas a2200097 4500008004100000245006100041210005900102260004100161100001600202856008700218 2003 eng d00aStandard-setting issues in computerized-adaptive testing0 aStandardsetting issues in computerizedadaptive testing aHalifax, Nova Scotia, May 30th, 20031 aGushta, M M uhttp://www.iacat.org/content/standard-setting-issues-computerized-adaptive-testing02980nas a2200121 4500008004100000245010700041210006900148300000900217490000700226520249100233100001202724856012202736 2003 eng d00aStatistical detection and estimation of differential item functioning in computerized adaptive testing0 aStatistical detection and estimation of differential item functi a27360 v643 aDifferential item functioning (DIF) is an important issue in large scale standardized testing. DIF refers to the unexpected difference in item performances among groups of equally proficient examinees, usually classified by ethnicity or gender. Its presence could seriously affect the validity of inferences drawn from a test. Various statistical methods have been proposed to detect and estimate DIF. This dissertation addresses DIF analysis in the context of computerized adaptive testing (CAT), whose item selection algorithm adapts to the ability level of each individual examinee. In a CAT, a DIF item may be more consequential and more detrimental be cause fewer items are administered in a CAT than in a traditional paper-and-pencil test and because the remaining sequence of items presented to examinees depends in part on their responses to the DIF item. Consequently, an efficient, stable and flexible method to detect and estimate CAT DIF becomes necessary and increasingly important. We propose simultaneous implementations of online calibration and DIF testing. The idea is to perform online calibration of an item of interest separately in the focal and reference groups. Under any specific parametric IRT model, we can use the (online) estimated latent traits as covariates and fit a nonlinear regression model to each of the two groups. Because of the use of the estimated, not the true , the regression fit has to adjust for the covariate "measurement errors". It turns out that this situation fits nicely into the framework of nonlinear error-in-variable modelling, which has been extensively studied in statistical literature. We develop two bias-correction methods using asymptotic expansion and conditional score theory. After correcting the bias caused by measurement error, one can perform a significance test to detect DIF with the parameter estimates for different groups. This dissertation also discusses some general techniques to handle measurement error modelling with different IRT models, including the three-parameter normal ogive model and polytomous response models. Several methods of estimating DIF are studied as well. Large sample properties are established to justify the proposed methods. Extensive simulation studies show that the resulting methods perform well in terms of Type-I error rate control, accuracy in estimating DIF and power against both unidirectional and crossing DIF. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aFeng, X uhttp://www.iacat.org/content/statistical-detection-and-estimation-differential-item-functioning-computerized-adaptive02967nas a2200121 4500008004100000245010900041210006900150300000800219490000700227520247100234100001402705856012602719 2003 eng d00aStrategies for controlling item exposure in computerized adaptive testing with polytomously scored items0 aStrategies for controlling item exposure in computerized adaptiv a4580 v643 aChoosing a strategy for controlling the exposure of items to examinees has become an integral part of test development for computerized adaptive testing (CAT). Item exposure can be controlled through the use of a variety of algorithms which modify the CAT item selection process. This may be done through a randomization, conditional selection, or stratification approach. The effectiveness of each procedure as well as the degree to which measurement precision is sacrificed has been extensively studied with dichotomously scored item pools. However, only recently have researchers begun to examine these procedures in polytomously scored item pools. The current study investigated the performance of six different exposure control mechanisms under three polytomous IRT models in terms of measurement precision, test security, and ease of implementation. The three models examined in the current study were the partial credit, generalized partial credit, and graded response models. In addition to a no exposure control baseline condition, the randomesque, within .10 logits, Sympson-Hetter, conditional Sympson-Hetter, a-Stratified, and enhanced a-Stratified procedures were implemented to control item exposure rates. The a-Stratified and enhanced a-Stratified procedures were not evaluated with the partial credit model. Two variations of the randomesque and within .10 logits procedures were also examined which varied the size of the item group from which the next item to be administered was randomly selected. The results of this study were remarkably similar for all three models and indicated that the randomesque and within .10 logits procedures, when implemented with the six item group variation, provide the best option for controlling exposure rates when impact to measurement precision and ease of implementation are considered. The three item group variations of the procedures were, however, ineffective in controlling exposure, overlap, and pool utilization rates to desired levels. The Sympson-Hetter and conditional Sympson-Hetter procedures were difficult and time consuming to implement, and while they did control exposure rates to the target level, their performance in terms of item overlap (for the Sympson-Hetter) and pool utilization were disappointing. The a-Stratified and enhanced a-Stratified procedures both turned in surprisingly poor performances across all variables. (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aDavis, LL uhttp://www.iacat.org/content/strategies-controlling-item-exposure-computerized-adaptive-testing-polytomously-scored-items00479nas a2200097 4500008004100000245012000041210006900161260001500230100001400245856012200259 2003 eng d00aStrategies for controlling item exposure in computerized adaptive testing with the generalized partial credit model0 aStrategies for controlling item exposure in computerized adaptiv aChicago IL1 aDavis, LL uhttp://www.iacat.org/content/strategies-controlling-item-exposure-computerized-adaptive-testing-generalized-partial-000507nam a2200097 4500008004100000245009500041210006900136260007100205100001400276856011900290 2003 eng d00aStrategies for controlling testlet exposure rates in computerized adaptive testing systems0 aStrategies for controlling testlet exposure rates in computerize aUnpublished Ph.D. Dissertation, The University of Texas at Austin.1 aBoyd, A M uhttp://www.iacat.org/content/strategies-controlling-testlet-exposure-rates-computerized-adaptive-testing-systems-000823nas a2200133 4500008004100000245005300041210005300094300001200147490000700159520041300166100001300579700001500592856008200607 2003 eng d00aStudent modeling and ab initio language learning0 aStudent modeling and ab initio language learning a519-5350 v313 aProvides examples of student modeling techniques that have been employed in computer-assisted language learning over the past decade. Describes two systems for learning German: "German Tutor" and "Geroline." Shows how a student model can support computerized adaptive language testing for diagnostic purposes in a Web-based language learning environment that does not rely on parsing technology. (Author/VWL)1 aHeift, T1 aSchulze, M uhttp://www.iacat.org/content/student-modeling-and-ab-initio-language-learning00580nas a2200145 4500008004100000245012200041210006900163300001300232490000800245100001700253700001500270700001400285700001200299856012300311 2003 eng d00aA study of the feasibility of Internet administration of a computerized health survey: The Headache Impact Test (HIT)0 astudy of the feasibility of Internet administration of a compute a 953-9610 v 121 aBayliss, M S1 aDewey, J E1 aDunlap, I1 aet. al. uhttp://www.iacat.org/content/study-feasibility-internet-administration-computerized-health-survey-headache-impact-test01601nas a2200205 4500008004100000245009400041210006900135260001000204300001200214490000800226520086400234653003001098653000901128653003401137653001101171653003501182653004501217100001801262856011501280 2003 eng d00aTen recommendations for advancing patient-centered outcomes measurement for older persons0 aTen recommendations for advancing patientcentered outcomes measu cSep 2 a403-4090 v1393 aThe past 50 years have seen great progress in the measurement of patient-based outcomes for older populations. Most of the measures now used were created under the umbrella of a set of assumptions and procedures known as classical test theory. A recent alternative for health status assessment is item response theory. Item response theory is superior to classical test theory because it can eliminate test dependency and achieve more precise measurement through computerized adaptive testing. Computerized adaptive testing reduces test administration times and allows varied and precise estimates of ability. Several key challenges must be met before computerized adaptive testing becomes a productive reality. I discuss these challenges for the health assessment of older persons in the form of 10 "Ds": things we need to deliberate, debate, decide, and do.10a*Health Status Indicators10aAged10aGeriatric Assessment/*methods10aHumans10aPatient-Centered Care/*methods10aResearch Support, U.S. Gov't, Non-P.H.S.1 aMcHorney, C A uhttp://www.iacat.org/content/ten-recommendations-advancing-patient-centered-outcomes-measurement-older-persons00455nas a2200109 4500008004100000245008200041210006900123260001500192100001500207700001600222856010700238 2003 eng d00aTest information targeting strategies for adaptive multistage testlet designs0 aTest information targeting strategies for adaptive multistage te aChicago IL1 aLuecht, RM1 aBurgin, W L uhttp://www.iacat.org/content/test-information-targeting-strategies-adaptive-multistage-testlet-designs00437nas a2200109 4500008004100000245006900041210006700110260002700177100001200204700001500216856009600231 2003 eng d00aTests adaptativos informatizados (Computerized adaptive testing)0 aTests adaptativos informatizados Computerized adaptive testing aMadrid: UNED Ediciones1 aOlea, J1 aPonsoda, V uhttp://www.iacat.org/content/tests-adaptativos-informatizados-computerized-adaptive-testing00500nas a2200109 4500008004100000245010900041210006900150260001500219100001900234700001200253856012500265 2003 eng d00aTest-score comparability, ability estimation, and item-exposure control in computerized adaptive testing0 aTestscore comparability ability estimation and itemexposure cont aChicago IL1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/test-score-comparability-ability-estimation-and-item-exposure-control-computerized-adaptive01549nas a2200193 4500008004100000245026000041210006900301300001000370490000700380520067700387653002101064653002201085653001701107653001501124653004801139100002201187700002201209856012401231 2003 eng d00aTiming behavior in computerized adaptive testing: Response times for correct and incorrect answers are not related to general fluid intelligence/Zum Zeitverhalten beim computergestützten adaptiveb Testen: Antwortlatenzen bei richtigen und falschen Lösun0 aTiming behavior in computerized adaptive testing Response times  a57-630 v243 aExamined the effects of general fluid intelligence on item response times for correct and false responses in computerized adaptive testing. After performing the CFT3 intelligence test, 80 individuals (aged 17-44 yrs) completed perceptual and cognitive discrimination tasks. Results show that response times were related neither to the proficiency dimension reflected by the task nor to the individual level of fluid intelligence. Furthermore, the false > correct-phenomenon as well as substantial positive correlations between item response times for false and correct responses were shown to be independent of intelligence levels. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aCognitive Ability10aIntelligence10aPerception10aReaction Time computerized adaptive testing1 aRammsayer, Thomas1 aBrandler, Susanne uhttp://www.iacat.org/content/timing-behavior-computerized-adaptive-testing-response-times-correct-and-incorrect-answers00484nas a2200109 4500008004100000245010200041210006900143260001500212100001200227700001400239856012100253 2003 eng d00aTo stratify or not: An investigation of CAT item selection procedures under practical constraints0 aTo stratify or not An investigation of CAT item selection proced aChicago IL1 aDeng, H1 aAnsley, T uhttp://www.iacat.org/content/stratify-or-not-investigation-cat-item-selection-procedures-under-practical-constraints00545nas a2200097 4500008004100000245014400041210006900185260006700254100001100321856011500332 2003 eng d00aUsing moving averages to assess test and item security in computer-based testing (Center for Educational Assessment Research Report No 468)0 aUsing moving averages to assess test and item security in comput aAmherst, MA: University of Massachusetts, School of Education.1 aHan, N uhttp://www.iacat.org/content/using-moving-averages-assess-test-and-item-security-computer-based-testing-center01516nas a2200229 4500008004100000245008700041210006900128300001200197490000700209520075300216653002100969653001300990653003001003653003401033653001101067653001501078653001501093653001801108100002301126700002701149856011001176 2003 eng d00aUsing response times to detect aberrant responses in computerized adaptive testing0 aUsing response times to detect aberrant responses in computerize a251-2650 v683 aA lognormal model for response times is used to check response times for aberrances in examinee behavior on computerized adaptive tests. Both classical procedures and Bayesian posterior predictive checks are presented. For a fixed examinee, responses and response times are independent; checks based on response times offer thus information independent of the results of checks on response patterns. Empirical examples of the use of classical and Bayesian checks for detecting two different types of aberrances in response times are presented. The detection rates for the Bayesian checks outperformed those for the classical checks, but at the cost of higher false-alarm rates. A guideline for the choice between the two types of checks is offered.10aAdaptive Testing10aBehavior10aComputer Assisted Testing10acomputerized adaptive testing10aModels10aperson Fit10aPrediction10aReaction Time1 avan der Linden, WJ1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/using-response-times-detect-aberrant-responses-computerized-adaptive-testing00511nas a2200109 4500008004100000245012600041210006900167260001900236100001200255700001200267856012200279 2002 eng d00aAccuracy of the ability estimate and the item exposure rate under multidimensional adaptive testing with item constraints0 aAccuracy of the ability estimate and the item exposure rate unde aNew Orleans LA1 aLi, Y H1 aYu, N Y uhttp://www.iacat.org/content/accuracy-ability-estimate-and-item-exposure-rate-under-multidimensional-adaptive-testing00527nas a2200121 4500008004100000245009600041210006900137260004600206100001100252700001300263700001600276856011300292 2002 eng d00aAdaptive testing without IRT in the presence of multidimensionality (Research Report 02-09)0 aAdaptive testing without IRT in the presence of multidimensional aPrinceton NJ: Educational Testing Service1 aYan, D1 aLewis, C1 aStocking, M uhttp://www.iacat.org/content/adaptive-testing-without-irt-presence-multidimensionality-research-report-02-0902859nas a2200265 4500008004100000245006600041210006600107260000800173300000900181490000700190520208800197653002102285653002902306653003002335653001202365653001102377653001302388653003102401653001902432100001302451700001502464700001302479700001502492856008602507 2002 eng d00aAdvances in quality of life measurements in oncology patients0 aAdvances in quality of life measurements in oncology patients cJun a60-80 v293 aAccurate assessment of the quality of life (QOL) of patients can provide important clinical information to physicians, especially in the area of oncology. Changes in QOL are important indicators of the impact of a new cytotoxic therapy, can affect a patient's willingness to continue treatment, and may aid in defining response in the absence of quantifiable endpoints such as tumor regression. Because QOL is becoming an increasingly important aspect in the management of patients with malignant disease, it is vital that the instruments used to measure QOL are reliable and accurate. Assessment of QOL involves a multidimensional approach that includes physical, functional, social, and emotional well-being, and the most comprehensive instruments measure at least three of these domains. Instruments to measure QOL can be generic (eg, the Nottingham Health Profile), targeted toward specific illnesses (eg, Functional Assessment of Cancer Therapy - Lung), or be a combination of generic and targeted. Two of the most widely used examples of the combination, or hybrid, instruments are the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 Items and the Functional Assessment of Chronic Illness Therapy. A consequence of the increasing international collaboration in clinical trials has been the growing necessity for instruments that are valid across languages and cultures. To assure the continuing reliability and validity of QOL instruments in this regard, item response theory can be applied. Techniques such as item response theory may be used in the future to construct QOL item banks containing large sets of validated questions that represent various levels of QOL domains. As QOL becomes increasingly important in understanding and approaching the overall management of cancer patients, the tools available to clinicians and researchers to assess QOL will continue to evolve. While the instruments currently available provide reliable and valid measurement, further improvements in precision and application are anticipated.10a*Quality of Life10a*Sickness Impact Profile10aCross-Cultural Comparison10aCulture10aHumans10aLanguage10aNeoplasms/*physiopathology10aQuestionnaires1 aCella, D1 aChang, C-H1 aLai, J S1 aWebster, K uhttp://www.iacat.org/content/advances-quality-life-measurements-oncology-patients03319nas a2200133 4500008004100000245005900041210005900100300001000159490000700169520289000176100001903066700001603085856008403101 2002 eng d00aApplicable adaptive testing models for school teachers0 aApplicable adaptive testing models for school teachers a55-590 v393 aThe purpose of this study was to investigate the attitudinal effects on SPRT adaptive testing environment for junior high school students. Subjects were 39 eighth graders from a selected junior high school. Major instruments for the study were the Junior High School Natural Sciences Adaptive Testing System driven by the SPRT algorithm, and a self-developed attitudinal questionnaire, factors examined include: test anxiety, examinee preference, adaptability of the test, and acceptance of the test result. The major findings were that overall, junior high school students" attitudes towards computerized adaptive tests were positive, no significant correlations existed between test attitude and the test length. The results indicated that junior high school students generally have positive attitudes towards adaptive testing.Modèles de tests d"adaptation à l"usage des enseignants. L"objectif de cette étude était d"enquêter sur les effets causés par une passation de tests d"adaptation ( selon l"algorithme "Sequential Probability Radio Test " (SPRT) ) dans une classe de trente-neuf élèves de huitième année du secondaire inférieur. Les principaux instruments utilisés ont été ceux du système de tests d"adaptation (avec le SPRT) et destiné aux classes de sciences naturelles du degré secondaire inférieur. Un questionnaire d"attitude, développé par nos soins, a également été utilisé pour examiner les facteurs suivants: test d"anxiété, préférence des candidats, adaptabilité du test et acceptation des résultats. Les principales conclusions ont été que, dans l"ensemble, l"attitude des élèves du secondaire inférieur face aux tests d"adaptation informatisés a été positive, aucune corrélation significative existant entre cette attitude et la longueur des tests. Les résultats démontrent aussi que les élèves du secondaire ont une attitude généralement positive envers les tests d"adaptation.Test Modelle zur Anwendung durch Klassenlehrer Zweck dieser Untersuchung war, die Auswirkungen über die Einstellung von Jun. High School Schülern im Zusammenhang mit dem SPRT Testumfeld zu untersuchen. 39 Achtklässler einer Jun. High School nahmen an dem Test teil. Die Untersuchung stützte sich hauptsächlich auf das Jun. High School Natural. Sciences Adaptive Testing System, das auf dem SPRT Rechnungsverfahren basiert sowie einem selbst erstellten Fragebogen mit folgenden Faktoren: Testängste, Präferenzen der Testperson, Geeignetheit des Tests, Anerkennung des Testergebnisses. Es stellte sich heraus, dass die Einstellung der Studenten zu den Computer adaptierten Tests im allgemeinen positiv waren; es ergaben sich keine bedeutsamen Wechselwirkungen zwischen persönlicher Testeinstellung und Testlänge. Die Ergebnisse belegen, dass Jun. High School Schüler im allgemeinen eine positive Haltung zu adaptierten Tests haben. 1 aChang-Hwa, W A1 aChuang, C-L uhttp://www.iacat.org/content/applicable-adaptive-testing-models-school-teachers00537nas a2200121 4500008004100000245014000041210006900181300001000250490000700260100001300267700001600280856011900296 2002 eng d00aApplication of an empirical Bayes enhancement of Mantel-Haenszel differential item functioning analysis to a computerized adaptive test0 aApplication of an empirical Bayes enhancement of MantelHaenszel  a57-760 v261 aZwick, R1 aThayer, D T uhttp://www.iacat.org/content/application-empirical-bayes-enhancement-mantel-haenszel-differential-item-functioning00470nam a2200097 4500008004100000245008000041210006900121260006500190100001600255856010100271 2002 eng d00aAssessing the efficiency of item selection in computerized adaptive testing0 aAssessing the efficiency of item selection in computerized adapt aUnpublished doctoral dissertation, University of Pittsburgh.1 aWeissman, A uhttp://www.iacat.org/content/assessing-efficiency-item-selection-computerized-adaptive-testing-001982nas a2200289 4500008004100000245007600041210006900117260000800186300001200194490000700206520114900213653002401362653001301386653002101399653002001420653001501440653001001455653001001465653001101475653001101486653000901497653002401506653002601530100001601556700001501572856010501587 2002 eng d00aAssessing tobacco beliefs among youth using item response theory models0 aAssessing tobacco beliefs among youth using item response theory cNov aS21-S390 v683 aSuccessful intervention research programs to prevent adolescent smoking require well-chosen, psychometrically sound instruments for assessing smoking prevalence and attitudes. Twelve thousand eight hundred and ten adolescents were surveyed about their smoking beliefs as part of the Teenage Attitudes and Practices Survey project, a prospective cohort study of predictors of smoking initiation among US adolescents. Item response theory (IRT) methods are used to frame a discussion of questions that a researcher might ask when selecting an optimal item set. IRT methods are especially useful for choosing items during instrument development, trait scoring, evaluating item functioning across groups, and creating optimal item subsets for use in specialized applications such as computerized adaptive testing. Data analytic steps for IRT modeling are reviewed for evaluating item quality and differential item functioning across subgroups of gender, age, and smoking status. Implications and challenges in the use of these methods for tobacco onset research and for assessing the developmental trajectories of smoking among youth are discussed.10a*Attitude to Health10a*Culture10a*Health Behavior10a*Questionnaires10aAdolescent10aAdult10aChild10aFemale10aHumans10aMale10aModels, Statistical10aSmoking/*epidemiology1 aPanter, A T1 aReeve, B B uhttp://www.iacat.org/content/assessing-tobacco-beliefs-among-youth-using-item-response-theory-models00618nas a2200157 4500008004100000245012800041210006900169300001300238490000700251100001700258700001600275700001500291700002100306700001300327856012000340 2002 eng d00aCan examinees use judgments of item difficulty to improve proficiency estimates on computerized adaptive vocabulary tests? 0 aCan examinees use judgments of item difficulty to improve profic a 311-3300 v391 aVispoel, W P1 aClough, S J1 aBleiler, T1 aHendrickson, A B1 aIhrig, D uhttp://www.iacat.org/content/can-examinees-use-judgments-item-difficulty-improve-proficiency-estimates-computerized00536nas a2200121 4500008004100000245011500041210006900156260001900225100001500244700001900259700001300278856012300291 2002 eng d00aComparing three item selection approaches for computerized adaptive testing with content balancing requirement0 aComparing three item selection approaches for computerized adapt aNew Orleans LA1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/comparing-three-item-selection-approaches-computerized-adaptive-testing-content-balancing00441nas a2200109 4500008004100000245007500041210006900116260001900185100001500204700001300219856009900232 2002 eng d00aA comparison of computer mastery models when pool characteristics vary0 acomparison of computer mastery models when pool characteristics  aNew Orleans LA1 aSmith, R L1 aLewis, C uhttp://www.iacat.org/content/comparison-computer-mastery-models-when-pool-characteristics-vary02085nas a2200229 4500008004100000245012900041210006900170300001200239490000700251520124000258653001801498653002101516653004501537653003001582653001801612653002501630653002601655100001601681700001401697700001901711856012501730 2002 eng d00aA comparison of item selection techniques and exposure control mechanisms in CATs using the generalized partial credit model0 acomparison of item selection techniques and exposure control mec a147-1630 v263 aThe use of more performance items in large-scale testing has led to an increase in the research investigating the use of polytomously scored items in computer adaptive testing (CAT). Because this research has to be complemented with information pertaining to exposure control, the present research investigated the impact of using five different exposure control algorithms in two sized item pools calibrated using the generalized partial credit model. The results of the simulation study indicated that the a-stratified design, in comparison to a no-exposure control condition, could be used to reduce item exposure and overlap, increase pool utilization, and only minorly degrade measurement precision. Use of the more restrictive exposure control algorithms, such as the Sympson-Hetter and conditional Sympson-Hetter, controlled exposure to a greater extent but at the cost of measurement precision. Because convergence of the exposure control parameters was problematic for some of the more restrictive exposure control algorithms, use of the more simplistic exposure control mechanisms, particularly when the test length to item pool size ratio is large, is recommended. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10a(Statistical)10aAdaptive Testing10aAlgorithms computerized adaptive testing10aComputer Assisted Testing10aItem Analysis10aItem Response Theory10aMathematical Modeling1 aPastor, D A1 aDodd, B G1 aChang, Hua-Hua uhttp://www.iacat.org/content/comparison-item-selection-techniques-and-exposure-control-mechanisms-cats-using-generalized00450nas a2200109 4500008004100000245009000041210006900131300001200200490000700212100001800219856010300237 2002 eng d00aA comparison of non-deterministic procedures for the adaptive assessment of knowledge0 acomparison of nondeterministic procedures for the adaptive asses a495-5030 v441 aHockemeyer, C uhttp://www.iacat.org/content/comparison-non-deterministic-procedures-adaptive-assessment-knowledge00533nas a2200121 4500008004100000245010900041210006900150260001900219100001400238700001700252700001800269856012400287 2002 eng d00aComparison of the psychometric properties of several computer-based test designs for credentialing exams0 aComparison of the psychometric properties of several computerbas aNew Orleans LA1 aJodoin, M1 aZenisky, A L1 aHambleton, RK uhttp://www.iacat.org/content/comparison-psychometric-properties-several-computer-based-test-designs-credentialing-exams01502nas a2200133 4500008004100000245011800041210006900159300000900228490000700237520094700244653003401191100001801225856012501243 2002 eng d00aComputer adaptive testing: The impact of test characteristics on perceived performance and test takers' reactions0 aComputer adaptive testing The impact of test characteristics on  a34100 v623 aThis study examined the relationship between characteristics of adaptive testing and test takers' subsequent reactions to the test. Participants took a computer adaptive test in which two features, the difficulty of the initial item and the difficulty of subsequent items, were manipulated. These two features of adaptive testing determined the number of items answered correctly by examinees and their subsequent reactions to the test. The data show that the relationship between test characteristics and reactions was fully mediated by perceived performance on the test. In addition, the impact of feedback on reactions to adaptive testing was also evaluated. In general, feedback that was consistent with perceptions of performance had a positive impact on reactions to the test. Implications for adaptive test design concerning maximizing test takers' reactions are discussed. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aTonidandel, S uhttp://www.iacat.org/content/computer-adaptive-testing-impact-test-characteristics-perceived-performance-and-test-takers00567nas a2200133 4500008003900000245012000039210006900159300001200228490000700240100001800247700001900265700001500284856013400299 2002 d00aComputer-adaptive testing: The impact of test characteristics on perceived performance and test takers’ reactions0 aComputeradaptive testing The impact of test characteristics on p a320-3320 v871 aTonidandel, S1 aQuiñones, M A1 aAdams, A A uhttp://www.iacat.org/content/computer-adaptive-testing-impact-test-characteristics-perceived-performance-and-test-takers%E2%80%9900689nas a2200145 4500008004100000245003400041210003400075300001100109490000700120520029200127653003400419100001200453700001500465856006300480 2002 eng d00aComputerised adaptive testing0 aComputerised adaptive testing a619-220 v333 aConsiders the potential of computer adaptive testing (CAT). Discusses the use of CAT instead of traditional paper and pencil tests, identifies decisions that impact the efficacy of CAT, and concludes that CAT is beneficial when used to its full potential on certain types of tests. (LRW)10acomputerized adaptive testing1 aLatu, E1 aChapman, E uhttp://www.iacat.org/content/computerised-adaptive-testing00493nas a2200097 4500008004100000245012700041210006900168260002000237100001600257856012200273 2002 eng d00aConfirmatory item factor analysis using Markov chain Monte Carlo estimation with applications to online calibration in CAT0 aConfirmatory item factor analysis using Markov chain Monte Carlo aNew Orleans, LA1 aSegall, D O uhttp://www.iacat.org/content/confirmatory-item-factor-analysis-using-markov-chain-monte-carlo-estimation-applications00538nas a2200109 4500008004100000245011000041210006900151260004200220100002300262700001800285856012500303 2002 eng d00aConstraining item exposure in computerized adaptive testing with shadow tests (Research Report No. 02-06)0 aConstraining item exposure in computerized adaptive testing with aUniversity of Twente, The Netherlands1 avan der Linden, WJ1 aVeldkamp, B P uhttp://www.iacat.org/content/constraining-item-exposure-computerized-adaptive-testing-shadow-tests-research-report-no-0200466nas a2200109 4500008004100000245008400041210006900125260001900194100001600213700001700229856011000246 2002 eng d00aContent-stratified random item selection in computerized classification testing0 aContentstratified random item selection in computerized classifi aNew Orleans LA1 aGuille, R S1 aNorcini, J J uhttp://www.iacat.org/content/content-stratified-random-item-selection-computerized-classification-testing00578nas a2200109 4500008004100000245006000041210006000101260018900161100001300350700001400363856009100377 2002 eng d00aControlling item exposure and maintaining item security0 aControlling item exposure and maintaining item security aC. N. Mills, M. T. Potenza, and J. J. Fremer (Eds.), Computer-Based Testing: Building the Foundation for Future Assessments (pp. 165-191). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.1 aDavey, T1 aNering, M uhttp://www.iacat.org/content/controlling-item-exposure-and-maintaining-item-security-001447nas a2200241 4500008004100000245008000041210006900121300001200190490000700202520067300209653003000882653002800912653002500940653002300965653001600988653002201004653002101026100001301047700001601060700001001076700001601086856010301102 2002 eng d00aData sparseness and on-line pretest item calibration-scaling methods in CAT0 aData sparseness and online pretest item calibrationscaling metho a207-2180 v393 aCompared and evaluated 3 on-line pretest item calibration-scaling methods (the marginal maximum likelihood estimate with 1 expectation maximization [EM] cycle [OEM] method, the marginal maximum likelihood estimate with multiple EM cycles [MEM] method, and M. L. Stocking's Method B) in terms of item parameter recovery when the item responses to the pretest items in the pool are sparse. Simulations of computerized adaptive tests were used to evaluate the results yielded by the three methods. The MEM method produced the smallest average total error in parameter estimation, and the OEM method yielded the largest total error (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aEducational Measurement10aItem Response Theory10aMaximum Likelihood10aMethodology10aScaling (Testing)10aStatistical Data1 aBan, J-C1 aHanson, B A1 aYi, Q1 aHarris, D J uhttp://www.iacat.org/content/data-sparseness-and-line-pretest-item-calibration-scaling-methods-cat01641nas a2200133 4500008004100000245008400041210006900125300001200194490000700206520114900213100002701362700001601389856010201405 2002 eng d00aDetection of person misfit in computerized adaptive tests with polytomous items0 aDetection of person misfit in computerized adaptive tests with p a164-1800 v263 aItem scores that do not fit an assumed item response theory model may cause the latent trait value to be inaccurately estimated. For a computerized adaptive test (CAT) using dichotomous items, several person-fit statistics for detecting mis.tting item score patterns have been proposed. Both for paper-and-pencil (P&P) tests and CATs, detection ofperson mis.t with polytomous items is hardly explored. In this study, the nominal and empirical null distributions ofthe standardized log-likelihood statistic for polytomous items are compared both for P&P tests and CATs. Results showed that the empirical distribution of this statistic differed from the assumed standard normal distribution for both P&P tests and CATs. Second, a new person-fit statistic based on the cumulative sum (CUSUM) procedure from statistical process control was proposed. By means ofsimulated data, critical values were determined that can be used to classify a pattern as fitting or misfitting. The effectiveness of the CUSUM to detect simulees with item preknowledge was investigated. Detection rates using the CUSUM were high for realistic numbers ofdisclosed items. 1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/detection-person-misfit-computerized-adaptive-tests-polytomous-items00466nas a2200097 4500008004100000245008700041210006900128260003900197100001500236856011700251 2002 eng d00aDeveloping tailored instruments: Item banking and computerized adaptive assessment0 aDeveloping tailored instruments Item banking and computerized ad a” Bethesda, Maryland, June 23-251 aThissen, D uhttp://www.iacat.org/content/developing-tailored-instruments-item-banking-and-computerized-adaptive-assessment-300481nas a2200109 4500008004100000245009900041210006900140260001900209100001400228700001400242856011500256 2002 eng d00aThe development and evaluation of a computer-adaptive testing application for English language0 adevelopment and evaluation of a computeradaptive testing applica aUnited Kingdom1 aLilley, M1 aBarker, T uhttp://www.iacat.org/content/development-and-evaluation-computer-adaptive-testing-application-english-language02894nas a2200349 4500008004100000245008300041210006900124260000800193300001100201490000700212520176600219653003001985653002802015653001502043653001002058653000902068653002202077653001102099653001902110653001102129653000902140653001602149653006202165653006102227653003302288653003602321653003102357653002602388100001402414700001602428856010002444 2002 eng d00aDevelopment of an index of physical functional health status in rehabilitation0 aDevelopment of an index of physical functional health status in  cMay a655-650 v833 aOBJECTIVE: To describe (1) the development of an index of physical functional health status (FHS) and (2) its hierarchical structure, unidimensionality, reproducibility of item calibrations, and practical application. DESIGN: Rasch analysis of existing data sets. SETTING: A total of 715 acute, orthopedic outpatient centers and 62 long-term care facilities in 41 states participating with Focus On Therapeutic Outcomes, Inc. PATIENTS: A convenience sample of 92,343 patients (40% male; mean age +/- standard deviation [SD], 48+/-17y; range, 14-99y) seeking rehabilitation between 1993 and 1999. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Patients completed self-report health status surveys at admission and discharge. The Medical Outcomes Study 36-Item Short-Form Health Survey's physical functioning scale (PF-10) is the foundation of the physical FHS. The Oswestry Low Back Pain Disability Questionnaire, Neck Disability Index, Lysholm Knee Questionnaire, items pertinent to patients with upper-extremity impairments, and items pertinent to patients with more involved neuromusculoskeletal impairments were cocalibrated into the PF-10. RESULTS: The final FHS item bank contained 36 items (patient separation, 2.3; root mean square measurement error, 5.9; mean square +/- SD infit, 0.9+/-0.5; outfit, 0.9+/-0.9). Analyses supported empirical item hierarchy, unidimensionality, reproducibility of item calibrations, and content and construct validity of the FHS-36. CONCLUSIONS: Results support the reliability and validity of FHS-36 measures in the present sample. Analyses show the potential for a dynamic, computer-controlled, adaptive survey for FHS assessment applicable for group analysis and clinical decision making for individual patients.10a*Health Status Indicators10a*Rehabilitation Centers10aAdolescent10aAdult10aAged10aAged, 80 and over10aFemale10aHealth Surveys10aHumans10aMale10aMiddle Aged10aMusculoskeletal Diseases/*physiopathology/*rehabilitation10aNervous System Diseases/*physiopathology/*rehabilitation10aPhysical Fitness/*physiology10aRecovery of Function/physiology10aReproducibility of Results10aRetrospective Studies1 aHart, D L1 aWright, B D uhttp://www.iacat.org/content/development-index-physical-functional-health-status-rehabilitation00325nas a2200097 4500008004100000245004300041210003900084260002200123100001700145856006500162 2002 eng d00aThe Development of STAR Early Literacy0 aDevelopment of STAR Early Literacy aDesert Springs CA1 aMcBride, J R uhttp://www.iacat.org/content/development-star-early-literacy00554nas a2200097 4500008003900000245013500039210006900174260007200243100001500315856012600330 2002 d00aDEVELOPMENT, RELIABILITY, AND VALIDITY OF A COMPUTERIZED ADAPTIVE VERSION OF THE SCHEDULE FOR NONADAPTIVE AND ADAPTIVE PERSONALITY0 aDEVELOPMENT RELIABILITY AND VALIDITY OF A COMPUTERIZED ADAPTIVE  aUnpublished Ph. D. dissertation, University of Iowa, Iowa City Iowa1 aSimms, L J uhttp://www.iacat.org/content/development-reliability-and-validity-computerized-adaptive-version-schedule-nonadaptive-an-002777nas a2200133 4500008004100000245009800041210006900139300000900208490000700217520225500224653003402479100001602513856011402529 2002 eng d00aThe effect of test characteristics on aberrant response patterns in computer adaptive testing0 aeffect of test characteristics on aberrant response patterns in  a33630 v623 aThe advantages that computer adaptive testing offers over linear tests have been well documented. The Computer Adaptive Test (CAT) design is more efficient than the Linear test design as fewer items are needed to estimate an examinee's proficiency to a desired level of precision. In the ideal situation, a CAT will result in examinees answering different number of items according to the stopping rule employed. Unfortunately, the realities of testing conditions have necessitated the imposition of time and minimum test length limits on CATs. Such constraints might place a burden on the CAT test taker resulting in aberrant response behaviors by some examinees. Occurrence of such response patterns results in inaccurate estimation of examinee proficiency levels. This study examined the effects of test lengths, time limits and the interaction of these factors with the examinee proficiency levels on the occurrence of aberrant response patterns. The focus of the study was on the aberrant behaviors caused by rushed guessing due to restrictive time limits. Four different testing scenarios were examined; fixed length performance tests with and without content constraints, fixed length mastery tests and variable length mastery tests without content constraints. For each of these testing scenarios, the effect of two test lengths, five different timing conditions and the interaction between these factors with three ability levels on ability estimation were examined. For fixed and variable length mastery tests, decision accuracy was also looked at in addition to the estimation accuracy. Several indices were used to evaluate the estimation and decision accuracy for different testing conditions. The results showed that changing time limits had a significant impact on the occurrence of aberrant response patterns conditional on ability. Increasing test length had negligible if not negative effect on ability estimation when rushed guessing occured. In case of performance testing high ability examinees while in classification testing middle ability examinees suffered the most. The decision accuracy was considerably affected in case of variable length classification tests. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aRizavi, S M uhttp://www.iacat.org/content/effect-test-characteristics-aberrant-response-patterns-computer-adaptive-testing01638nas a2200217 4500008004100000245009700041210006900138300001200207490000700219520087500226653002101101653003001122653002501152653002301177653002501200653002801225653002701253100001301280700001501293856011201308 2002 eng d00aAn EM approach to parameter estimation for the Zinnes and Griggs paired comparison IRT model0 aEM approach to parameter estimation for the Zinnes and Griggs pa a208-2270 v263 aBorman et al. recently proposed a computer adaptive performance appraisal system called CARS II that utilizes paired comparison judgments of behavioral stimuli. To implement this approach,the paired comparison ideal point model developed by Zinnes and Griggs was selected. In this article,the authors describe item response and information functions for the Zinnes and Griggs model and present procedures for estimating stimulus and person parameters. Monte carlo simulations were conducted to assess the accuracy of the parameter estimation procedures. The results indicated that at least 400 ratees (i.e.,ratings) are required to obtain reasonably accurate estimates of the stimulus parameters and their standard errors. In addition,latent trait estimation improves as test length increases. The implications of these results for test construction are also discussed. 10aAdaptive Testing10aComputer Assisted Testing10aItem Response Theory10aMaximum Likelihood10aPersonnel Evaluation10aStatistical Correlation10aStatistical Estimation1 aStark, S1 aDrasgow, F uhttp://www.iacat.org/content/em-approach-parameter-estimation-zinnes-and-griggs-paired-comparison-irt-model00478nas a2200097 4500008004100000245010600041210006900147260001900216100001900235856012600254 2002 eng d00aAn empirical comparison of achievement level estimates from adaptive tests and paper-and-pencil tests0 aempirical comparison of achievement level estimates from adaptiv aNew Orleans LA1 aKingsbury, G G uhttp://www.iacat.org/content/empirical-comparison-achievement-level-estimates-adaptive-tests-and-paper-and-pencil-tests-000528nas a2200109 4500008004100000245010600041210006900147260002500216653003400241100001900275856012400294 2002 eng d00aAn empirical comparison of achievement level estimates from adaptive tests and paper-and-pencil tests0 aempirical comparison of achievement level estimates from adaptiv aNew Orleans, LA. USA10acomputerized adaptive testing1 aKingsbury, G G uhttp://www.iacat.org/content/empirical-comparison-achievement-level-estimates-adaptive-tests-and-paper-and-pencil-tests00624nas a2200097 4500008004100000245021100041210006900252260006700321100001700388856012100405 2002 eng d00aAn empirical investigation of selected multi-stage testing design variables on test assembly and decision accuracy outcomes for credentialing exams (Center for Educational Assessment Research Report No 469)0 aempirical investigation of selected multistage testing design va aAmherst, MA: University of Massachusetts, School of Education.1 aZenisky, A L uhttp://www.iacat.org/content/empirical-investigation-selected-multi-stage-testing-design-variables-test-assembly-and00372nas a2200097 4500008004100000245005900041210005900100260001900159100001600178856008000194 2002 eng d00aEmploying new ideas in CAT to a simulated reading test0 aEmploying new ideas in CAT to a simulated reading test aNew Orleans LA1 aThompson, T uhttp://www.iacat.org/content/employing-new-ideas-cat-simulated-reading-test00685nas a2200121 4500008004400000245026000044210007100304300001000375490001200385100001500397700001500412856013600427 2002 Frendh 00aÉtude de la distribution d'échantillonnage de l'estimateur du niveau d'habileté en testing adaptatif en fonction de deux règles d'arrêt dans le contexte de l'application du modèle de Rasch [Study of the sampling distribution of the proficiecy estima0 aÉtude de la distribution déchantillonnage de lestimateur du nive a23-400 v24(2-3)1 aRaîche, G1 aBlais, J-G uhttp://www.iacat.org/content/%C3%A9tude-de-la-distribution-d%C3%A9chantillonnage-de-lestimateur-du-niveau-dhabilet%C3%A9-en-testing01310nas a2200169 4500008004100000245009500041210006900136300001200205490000700217520070700224653003400931100001400965700001600979700001600995700001701011856011201028 2002 eng d00aEvaluation of selection procedures for computerized adaptive testing with polytomous items0 aEvaluation of selection procedures for computerized adaptive tes a393-4110 v263 aIn the present study, a procedure that has been used to select dichotomous items in computerized adaptive testing was applied to polytomous items. This procedure was designed to select the item with maximum weighted information. In a simulation study, the item information function was integrated over a fixed interval of ability values and the item with the maximum area was selected. This maximum interval information item selection procedure was compared to a maximum point information item selection procedure. Substantial differences between the two item selection procedures were not found when computerized adaptive tests were evaluated on bias and the root mean square of the ability estimate. 10acomputerized adaptive testing1 aRijn, P W1 aEggen, Theo1 aHemker, B T1 aSanders, P F uhttp://www.iacat.org/content/evaluation-selection-procedures-computerized-adaptive-testing-polytomous-items00547nas a2200145 4500008004100000245009500041210006900136300001200205490000700217100001400224700001600238700001600254700001700270856011400287 2002 eng d00aEvaluation of selection procedures for computerized adaptive testing with polytomous items0 aEvaluation of selection procedures for computerized adaptive tes a393-4110 v261 aRijn, P W1 aEggen, Theo1 aHemker, B T1 aSanders, P F uhttp://www.iacat.org/content/evaluation-selection-procedures-computerized-adaptive-testing-polytomous-items-000392nas a2200097 4500008004100000245006600041210006200107260002000169100001600189856008900205 2002 eng d00aAn examination of decision-theory adaptive testing procedures0 aexamination of decisiontheory adaptive testing procedures aNew Orleans, LA1 aRudner, L M uhttp://www.iacat.org/content/examination-decision-theory-adaptive-testing-procedures00442nas a2200121 4500008004100000245006100041210005800102260002700160100001600187700001700203700001600220856008400236 2002 eng d00aAn exploration of potentially problematic adaptive tests0 aexploration of potentially problematic adaptive tests aResearch Report 02-05)1 aStocking, M1 aSteffen, M L1 aEignor, D R uhttp://www.iacat.org/content/exploration-potentially-problematic-adaptive-tests00407nas a2200109 4500008004100000245006200041210006200103260001900165100001700184700001300201856008300214 2002 eng d00aFairness issues in adaptive tests with strict time limits0 aFairness issues in adaptive tests with strict time limits aNew Orleans LA1 aBridgeman, B1 aCline, F uhttp://www.iacat.org/content/fairness-issues-adaptive-tests-strict-time-limits00572nas a2200145 4500008004100000245011700041210006900158300000800227490001000235100001500245700001500260700001300275700001300288856012500301 2002 eng d00aFeasibility and acceptability of computerized adaptive testing (CAT) for fatigue monitoring in clinical practice0 aFeasibility and acceptability of computerized adaptive testing C a1340 v11(7)1 aDavis, K M1 aChang, C-H1 aLai, J-S1 aCella, D uhttp://www.iacat.org/content/feasibility-and-acceptability-computerized-adaptive-testing-cat-fatigue-monitoring-clinical00694nas a2200157 4500008003900000245010200039210006900141260011300210100001500323700001700338700001600355700001600371700001700387700001600404856011600420 2002 d00aA feasibility study of on-the-fly item generation in adaptive testing (GRE Board Report No 98-12)0 afeasibility study of onthefly item generation in adaptive testin aEducational Testing Service RR02-23. Princeton NJ: Educational Testing Service. Note = “{PDF file, 193 KB}1 aBejar, I I1 aLawless, R R1 aMorley, M E1 aWagner, M E1 aBennett, R E1 aRevuelta, J uhttp://www.iacat.org/content/feasibility-study-fly-item-generation-adaptive-testing-gre-board-report-no-98-12-000463nas a2200109 4500008004100000245009200041210006900133260001900202100001100221700000900232856011200241 2002 eng d00aA further study on adjusting CAT item selection starting point for individual examinees0 afurther study on adjusting CAT item selection starting point for aNew Orleans LA1 aFan, M1 aZhu. uhttp://www.iacat.org/content/further-study-adjusting-cat-item-selection-starting-point-individual-examinees01778nas a2200217 4500008004100000245006200041210006200103260005600165300001200221520108400233653002401317653001601341653001401357653002201371653001501393653001801408653001301426100001901439700001601458856008601474 2002 eng d00aGenerating abstract reasoning items with cognitive theory0 aGenerating abstract reasoning items with cognitive theory aMahwah, N.J. USAbLawrence Erlbaum Associates, Inc. a219-2503 a(From the chapter) Developed and evaluated a generative system for abstract reasoning items based on cognitive theory. The cognitive design system approach was applied to generate matrix completion problems. Study 1 involved developing the cognitive theory with 191 college students who were administered Set I and Set II of the Advanced Progressive Matrices. Study 2 examined item generation by cognitive theory. Study 3 explored the psychometric properties and construct representation of abstract reasoning test items with 728 young adults. Five structurally equivalent forms of Abstract Reasoning Test (ART) items were prepared from the generated item bank and administered to the Ss. In Study 4, the nomothetic span of construct validity of the generated items was examined with 728 young adults who were administered ART items, and 217 young adults who were administered ART items and the Advanced Progressive Matrices. Results indicate the matrix completion items were effectively generated by the cognitive design system approach. (PsycINFO Database Record (c) 2005 APA )10aCognitive Processes10aMeasurement10aReasoning10aTest Construction10aTest Items10aTest Validity10aTheories1 aEmbretson, S E1 aKyllomen, P uhttp://www.iacat.org/content/generating-abstract-reasoning-items-cognitive-theory00444nas a2200085 4500008003900000245010900039210006900148100001500217856012600232 2002 d00aHistorique et concepts propres au testing adaptatif [Adaptive testing: Historical accounts and concepts]0 aHistorique et concepts propres au testing adaptatif Adaptive tes1 aBlais, J G uhttp://www.iacat.org/content/historique-et-concepts-propres-au-testing-adaptatif-adaptive-testing-historical-accounts-a-002013nas a2200205 4500008004100000245008200041210006900123300001200192490000700204520132300211653002101534653001501555653003001570653001101600653000901611653004701620100001901667700001301686856010801699 2002 eng d00aHypergeometric family and item overlap rates in computerized adaptive testing0 aHypergeometric family and item overlap rates in computerized ada a387-3980 v673 aA computerized adaptive test (CAT) is usually administered to small groups of examinees at frequent time intervals. It is often the case that examinees who take the test earlier share information with examinees who will take the test later, thus increasing the risk that many items may become known. Item overlap rate for a group of examinees refers to the number of overlapping items encountered by these examinees divided by the test length. For a specific item pool, different item selection algorithms may yield different item overlap rates. An important issue in designing a good CAT item selection algorithm is to keep item overlap rate below a preset level. In doing so, it is important to investigate what the lowest rate could be for all possible item selection algorithms. In this paper we rigorously prove that if every item had an equal possibility to be selected from the pool in a fixed-length CAT, the number of overlapping item among any α randomly sampled examinees follows the hypergeometric distribution family for α ≥ 1. Thus, the expected values of the number of overlapping items among any randomly sampled α examinee can be calculated precisely. These values may serve as benchmarks in controlling item overlap rates for fixed-length adaptive tests. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aAlgorithms10aComputer Assisted Testing10aTaking10aTest10aTime On Task computerized adaptive testing1 aChang, Hua-Hua1 aZhang, J uhttp://www.iacat.org/content/hypergeometric-family-and-item-overlap-rates-computerized-adaptive-testing00483nas a2200109 4500008004100000245009700041210006900138260001900207100001900226700001300245856011500258 2002 eng d00aIdentify the lower bounds for item sharing and item pooling in computerized adaptive testing0 aIdentify the lower bounds for item sharing and item pooling in c aNew Orleans LA1 aChang, Hua-Hua1 aZhang, J uhttp://www.iacat.org/content/identify-lower-bounds-item-sharing-and-item-pooling-computerized-adaptive-testing00479nas a2200097 4500008004100000245011200041210006900153260001900222100001800241856012200259 2002 eng d00aImpact of item quality and item bank size on the psychometric quality of computer-based credentialing exams0 aImpact of item quality and item bank size on the psychometric qu aNew Orleans LA1 aHambleton, RK uhttp://www.iacat.org/content/impact-item-quality-and-item-bank-size-psychometric-quality-computer-based-credentialing00553nas a2200121 4500008004100000245013500041210006900176260001900245100001800264700001400282700001700296856011800313 2002 eng d00aImpact of selected factors on the psychometric quality of credentialing examinations administered with a sequential testlet design0 aImpact of selected factors on the psychometric quality of creden aNew Orleans LA1 aHambleton, RK1 aJodoin, M1 aZenisky, A L uhttp://www.iacat.org/content/impact-selected-factors-psychometric-quality-credentialing-examinations-administered00517nas a2200109 4500008004100000245012800041210006900169260001600238100001200254700001800266856012300284 2002 eng d00aImpact of test design, item quality and item bank size on the psychometric properties of computer-based credentialing exams0 aImpact of test design item quality and item bank size on the psy aNew Orleans1 aXing, D1 aHambleton, RK uhttp://www.iacat.org/content/impact-test-design-item-quality-and-item-bank-size-psychometric-properties-computer-based02791nas a2200133 4500008004100000245010200041210006900143300000900212490000700221520226500228653003402493100002002527856011002547 2002 eng d00aThe implications of the use of non-optimal items in a Computer Adaptive Testing (CAT) environment0 aimplications of the use of nonoptimal items in a Computer Adapti a16060 v633 aThis study describes the effects of manipulating item difficulty in a computer adaptive testing (CAT) environment. There are many potential benefits when using CATS as compared to traditional tests. These include increased security, shorter tests, and more precise measurement. According to IRT, the theory underlying CAT, as the computer continually recalculates ability, items that match that current estimate of ability are administered. Such items provide maximum information about examinees during the test. Herein, however, lies a potential problem. These optimal CAT items result in an examinee having only a 50% chance of a correct response. Some examinees may consider such items unduly challenging. Further, when test anxiety is a factor, it is possible that test scores may be negatively affected. This research was undertaken to determine the effects of administering easier CAT items on ability estimation and test length using computer simulations. Also considered was the administration of different numbers of initial items prior to the start of the adaptive portion of the test, using three different levels of measurement precision. Results indicate that regardless of the number of initial items administered, the level of precision employed, or the modifications made to item difficulty, the approximation of estimated ability to true ability is good in all cases. Additionally, the standard deviations of the ability estimates closely approximate the theoretical levels of precision used as stopping rules for the simulated CATs. Since optimal CAT items are not used, each item administered provides less information about examinees than optimal CAT items. This results in longer tests. Fortunately, using easier items that provide up to a 66.4% chance of a correct response results in tests that only modestly increase in length, across levels of precision. For larger standard errors, even easier items (up to a 73.5% chance of a correct response) result in only negligible to modest increases in test length. Examinees who find optimal CAT items difficult or examinees with test anxiety may find CATs that implement easier items enhance the already existing benefits of CAT. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGrodenchik, D J uhttp://www.iacat.org/content/implications-use-non-optimal-items-computer-adaptive-testing-cat-environment00471nas a2200097 4500008004100000245011200041210006900153260002000222100001000242856012100252 2002 eng d00aIncorporating the Sympson-Hetter exposure control method into the a-stratified method with content blocking0 aIncorporating the SympsonHetter exposure control method into the aNew Orleans, LA1 aYi, Q uhttp://www.iacat.org/content/incorporating-sympson-hetter-exposure-control-method-stratified-method-content-blocking01217nas a2200217 4500008004100000245005100041210005100092300001200143490000700155520060500162653002600767653003000793653001600823653001300839653001300852653001100865653001200876653001500888100001600903856008000919 2002 eng d00aInformation technology and literacy assessment0 aInformation technology and literacy assessment a369-3730 v183 aThis column discusses information technology and literacy assessment in the past and present. The author also describes computer-based assessments today including the following topics: computer-scored testing, computer-administered formal assessment, Internet formal assessment, computerized adaptive tests, placement tests, informal assessment, electronic portfolios, information management, and Internet information dissemination. A model of the major present-day applications of information technologies in reading and literacy assessment is also included. (PsycINFO Database Record (c) 2005 APA )10aComputer Applications10aComputer Assisted Testing10aInformation10aInternet10aLiteracy10aModels10aSystems10aTechnology1 aBalajthy, E uhttp://www.iacat.org/content/information-technology-and-literacy-assessment00524nas a2200121 4500008004100000245005100041210005100092260013700143100001800280700001300298700001500311856007600326 2002 eng d00aInnovative item types for computerized testing0 aInnovative item types for computerized testing aIn W. J. van der Linden and C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice. Norwell MA: Kluwer (in press).1 aParshall, C G1 aDavey, T1 aPashley, P uhttp://www.iacat.org/content/innovative-item-types-computerized-testing00520nas a2200133 4500008004100000245009700041210006900138260001900207100001500226700001100241700001300252700001100265856011000276 2002 eng d00aAn investigation of procedures for estimating error indexes in proficiency estimation in CAT0 ainvestigation of procedures for estimating error indexes in prof aNew Orleans LA1 aShyu, C -Y1 aFan, M1 aThompson1 aHsu, Y uhttp://www.iacat.org/content/investigation-procedures-estimating-error-indexes-proficiency-estimation-cat01183nas a2200133 4500008004100000245006200041210005900103300001200162490000700174520073400181653003400915100001600949856008400965 2002 eng d00aAn item response model for characterizing test compromise0 aitem response model for characterizing test compromise a163-1790 v273 aThis article presents an item response model for characterizing test-compromise that enables the estimation of item-preview and score-gain distributions observed in on-demand high-stakes testing programs. Model parameters and posterior distributions are estimated by Markov Chain Monte Carlo (MCMC) procedures. Results of a simulation study suggest that when at least some of the items taken by a small sample of test takers are known to be secure (uncompromised), the procedure can provide useful summaries of test-compromise and its impact on test scores. The article includes discussions of operational use of the proposed procedure, possible model violations and extensions, and application to computerized adaptive testing. 10acomputerized adaptive testing1 aSegall, D O uhttp://www.iacat.org/content/item-response-model-characterizing-test-compromise00554nas a2200133 4500008004100000245012100041210006900162300001200231490000700243100001500250700001900265700001300284856012300297 2002 eng d00aItem selection in computerized adaptive testing: Improving the a-stratified design with the Sympson-Hetter algorithm0 aItem selection in computerized adaptive testing Improving the as a376-3920 v261 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/item-selection-computerized-adaptive-testing-improving-stratified-design-sympson-hetter-000578nas a2200145 4500008004100000020001400041245012100055210006900176300001200245490000700257100001500264700001900279700001300298856012100311 2002 eng d a0146-621600aItem selection in computerized adaptive testing: Improving the a-stratified design with the Sympson-Hetter algorithm0 aItem selection in computerized adaptive testing Improving the as a376-3920 v261 aLeung, C K1 aChang, Hua-Hua1 aHau, K T uhttp://www.iacat.org/content/item-selection-computerized-adaptive-testing-improving-stratified-design-sympson-hetter00466nas a2200085 4500008004400000245011400044210007100158100001500229856013600244 2002 Frendh 00aLa simulation d’un test adaptatif basé sur le modèle de Rasch [Simulation of a Rasch-based adaptive test]0 aLa simulation d un test adaptatif basé sur le modèle de Rasch Si1 aRaîche, G uhttp://www.iacat.org/content/la-simulation-d%E2%80%99un-test-adaptatif-bas%C3%A9-sur-le-mod%C3%A8le-de-rasch-simulation-rasch-based00474nas a2200097 4500008004100000245004400041210004200085260016300127100001500290856007100305 2002 eng d00aLe testing adaptatif [Adaptive testing]0 aLe testing adaptatif Adaptive testing aD. R. Bertrand and J.G. Blais (Eds) : Les théories modernes de la mesure [Modern theories of measurement]. Sainte-Foy: Presses de l’Université du Québec.1 aRaîche, G uhttp://www.iacat.org/content/le-testing-adaptatif-adaptive-testing00409nas a2200097 4500008004100000245007500041210006900116100001700185700001700202856009200219 2002 eng d00aMapping the Development of Pre-reading Skills with STAR Early Literacy0 aMapping the Development of Prereading Skills with STAR Early Lit1 aMcBride, J R1 aTardrew, S P uhttp://www.iacat.org/content/mapping-development-pre-reading-skills-star-early-literacy01693nas a2200277 4500008004100000020001000041245006500051210006400116260009700180300001100277520074500288653002101033653002201054653002501076653002801101653002501129653001601154653001801170653005501188653001501243653001201258100001801270700002301288700001301311856009101324 2002 eng d a02-0900aMathematical-programming approaches to test item pool design0 aMathematicalprogramming approaches to test item pool design aTwente, The NetherlandsbUniversity of Twente, Faculty of Educational Science and Technology a93-1083 a(From the chapter) This paper presents an approach to item pool design that has the potential to improve on the quality of current item pools in educational and psychological testing and hence to increase both measurement precision and validity. The approach consists of the application of mathematical programming techniques to calculate optimal blueprints for item pools. These blueprints can be used to guide the item-writing process. Three different types of design problems are discussed, namely for item pools for linear tests, item pools computerized adaptive testing (CAT), and systems of rotating item pools for CAT. The paper concludes with an empirical example of the problem of designing a system of rotating item pools for CAT.10aAdaptive Testing10aComputer Assisted10aComputer Programming10aEducational Measurement10aItem Response Theory10aMathematics10aPsychometrics10aStatistical Rotation computerized adaptive testing10aTest Items10aTesting1 aVeldkamp, B P1 avan der Linden, WJ1 aAriel, A uhttp://www.iacat.org/content/mathematical-programming-approaches-test-item-pool-design02415nas a2200277 4500008004100000245012200041210006900163260000800232300001000240490000700250520148700257653002101744653002101765653002001786653001001806653002201816653002901838653001101867653001801878653001901896653004101915653003201956100001301988700001802001856011802019 2002 eng d00aMeasuring quality of life in chronic illness: the functional assessment of chronic illness therapy measurement system0 aMeasuring quality of life in chronic illness the functional asse cDec aS10-70 v833 aWe focus on quality of life (QOL) measurement as applied to chronic illness. There are 2 major types of health-related quality of life (HRQOL) instruments-generic health status and targeted. Generic instruments offer the opportunity to compare results across patient and population cohorts, and some can provide normative or benchmark data from which to interpret results. Targeted instruments ask questions that focus more on the specific condition or treatment under study and, as a result, tend to be more responsive to clinically important changes than generic instruments. Each type of instrument has a place in the assessment of HRQOL in chronic illness, and consideration of the relative advantages and disadvantages of the 2 options best drives choice of instrument. The Functional Assessment of Chronic Illness Therapy (FACIT) system of HRQOL measurement is a hybrid of the 2 approaches. The FACIT system combines a core general measure with supplemental measures targeted toward specific diseases, conditions, or treatments. Thus, it capitalizes on the strengths of each type of measure. Recently, FACIT questionnaires were administered to a representative sample of the general population with results used to derive FACIT norms. These normative data can be used for benchmarking and to better understand changes in HRQOL that are often seen in clinical trials. Future directions in HRQOL assessment include test equating, item banking, and computerized adaptive testing.10a*Chronic Disease10a*Quality of Life10a*Rehabilitation10aAdult10aComparative Study10aHealth Status Indicators10aHumans10aPsychometrics10aQuestionnaires10aResearch Support, U.S. Gov't, P.H.S.10aSensitivity and Specificity1 aCella, D1 aNowinski, C J uhttp://www.iacat.org/content/measuring-quality-life-chronic-illness-functional-assessment-chronic-illness-therapy00302nas a2200097 4500008004100000245003200041210003000073260003000103100001200133856005900145 2002 eng d00aMIRTCAT [computer software]0 aMIRTCAT computer software aUpper Marlboro MD: Author1 aLi, Y H uhttp://www.iacat.org/content/mirtcat-computer-software00499nas a2200097 4500008004100000245010600041210006900147260004100216100002300257856012100280 2002 eng d00aModifications of the Sympson-Hetter method for item-exposure control in computerized adaptive testing0 aModifications of the SympsonHetter method for itemexposure contr aManuscript submitted for publication1 avan der Linden, WJ uhttp://www.iacat.org/content/modifications-sympson-hetter-method-item-exposure-control-computerized-adaptive-testing03062nas a2200325 4500008004100000020004100041245008100082210006900163250001500232260000800247300001100255490000700266520201300273653001502286653001002301653004002311653005702351653003302408653001102441653001102452653001802463653000902481653002802490653001202518653005502530100001502585700001802600700001502618856010302633 2002 eng d a0025-7079 (Print)0025-7079 (Linking)00aMultidimensional adaptive testing for mental health problems in primary care0 aMultidimensional adaptive testing for mental health problems in  a2002/09/10 cSep a812-230 v403 aOBJECTIVES: Efficient and accurate instruments for assessing child psychopathology are increasingly important in clinical practice and research. For example, screening in primary care settings can identify children and adolescents with disorders that may otherwise go undetected. However, primary care offices are notorious for the brevity of visits and screening must not burden patients or staff with long questionnaires. One solution is to shorten assessment instruments, but dropping questions typically makes an instrument less accurate. An alternative is adaptive testing, in which a computer selects the items to be asked of a patient based on the patient's previous responses. This research used a simulation to test a child mental health screen based on this technology. RESEARCH DESIGN: Using half of a large sample of data, a computerized version was developed of the Pediatric Symptom Checklist (PSC), a parental-report psychosocial problem screen. With the unused data, a simulation was conducted to determine whether the Adaptive PSC can reproduce the results of the full PSC with greater efficiency. SUBJECTS: PSCs were completed by parents on 21,150 children seen in a national sample of primary care practices. RESULTS: Four latent psychosocial problem dimensions were identified through factor analysis: internalizing problems, externalizing problems, attention problems, and school problems. A simulated adaptive test measuring these traits asked an average of 11.6 questions per patient, and asked five or fewer questions for 49% of the sample. There was high agreement between the adaptive test and the full (35-item) PSC: only 1.3% of screening decisions were discordant (kappa = 0.93). This agreement was higher than that obtained using a comparable length (12-item) short-form PSC (3.2% of decisions discordant; kappa = 0.84). CONCLUSIONS: Multidimensional adaptive testing may be an accurate and efficient technology for screening for mental health problems in primary care settings.10aAdolescent10aChild10aChild Behavior Disorders/*diagnosis10aChild Health Services/*organization & administration10aFactor Analysis, Statistical10aFemale10aHumans10aLinear Models10aMale10aMass Screening/*methods10aParents10aPrimary Health Care/*organization & administration1 aGardner, W1 aKelleher, K J1 aPajer, K A uhttp://www.iacat.org/content/multidimensional-adaptive-testing-mental-health-problems-primary-care01159nas a2200133 4500008004100000245007100041210006900112300001200181490000700193520069200200100001800892700002300910856009200933 2002 eng d00aMultidimensional adaptive testing with constraints on test content0 aMultidimensional adaptive testing with constraints on test conte a575-5880 v673 aThe case of adaptive testing under a multidimensional response model with large numbers of constraints on the content of the test is addressed. The items in the test are selected using a shadow test approach. The 0–1 linear programming model that assembles the shadow tests maximizes posterior expected Kullback-Leibler information in the test. The procedure is illustrated for five different cases of multidimensionality. These cases differ in (a) the numbers of ability dimensions that are intentional or should be considered as ldquonuisance dimensionsrdquo and (b) whether the test should or should not display a simple structure with respect to the intentional ability dimensions.1 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-constraints-test-content00460nas a2200121 4500008004100000245007300041210006900114260001900183100001400202700001900216700001300235856009000248 2002 eng d00aOptimum number of strata in the a-stratified adaptive testing design0 aOptimum number of strata in the astratified adaptive testing des aNew Orleans LA1 aWen, J -B1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/optimum-number-strata-stratified-adaptive-testing-design01631nas a2200241 4500008004100000245005900041210005800100300001200158490000700170520087100177653002101048653003401069653002801103653002001131653003201151653002501183653001501208653002701223653002201250653001601272100001601288856008501304 2002 eng d00aOutlier detection in high-stakes certification testing0 aOutlier detection in highstakes certification testing a219-2330 v393 aDiscusses recent developments of person-fit analysis in computerized adaptive testing (CAT). Methods from statistical process control are presented that have been proposed to classify an item score pattern as fitting or misfitting the underlying item response theory model in CAT Most person-fit research in CAT is restricted to simulated data. In this study, empirical data from a certification test were used. Alternatives are discussed to generate norms so that bounds can be determined to classify an item score pattern as fitting or misfitting. Using bounds determined from a sample of a high-stakes certification test, the empirical analysis showed that different types of misfit can be distinguished Further applications using statistical process control methods to detect misfitting item score patterns are discussed. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10acomputerized adaptive testing10aEducational Measurement10aGoodness of Fit10aItem Analysis (Statistical)10aItem Response Theory10aperson Fit10aStatistical Estimation10aStatistical Power10aTest Scores1 aMeijer, R R uhttp://www.iacat.org/content/outlier-detection-high-stakes-certification-testing00558nas a2200109 4500008004100000245016800041210006900209260002000278100001400298700001500312856012100327 2002 eng d00aPractical considerations about expected a posteriori estimation in adaptive testing: Adaptive a prior, adaptive corrections for bias, adaptive integration interval0 aPractical considerations about expected a posteriori estimation  aNew Orleans, LA1 aRaiche, G1 aBlais, J G uhttp://www.iacat.org/content/practical-considerations-about-expected-posteriori-estimation-adaptive-testing-adaptive00458nas a2200097 4500008004100000245008900041210006900130260001900199100002300218856011900241 2002 eng d00aA “rearrangement procedure” for administering adaptive tests with review options0 arearrangement procedure for administering adaptive tests with re aNew Orleans LA1 aPapanastasiou, E C uhttp://www.iacat.org/content/%E2%80%9Crearrangement-procedure%E2%80%9D-administering-adaptive-tests-review-options00459nas a2200109 4500008004100000245008600041210006900127260001900196100001500215700001600230856010300246 2002 eng d00aRedeveloping the exposure control parameters of CAT items when a pool is modified0 aRedeveloping the exposure control parameters of CAT items when a aNew Orleans LA1 aChang, S-W1 aHarris, D J uhttp://www.iacat.org/content/redeveloping-exposure-control-parameters-cat-items-when-pool-modified00532nas a2200109 4500008004100000245014600041210006900187260001900256100001200275700001200287856012300299 2002 eng d00aRelative precision of ability estimation in polytomous CAT: A comparison under the generalized partial credit model and graded response model0 aRelative precision of ability estimation in polytomous CAT A com aNew Orleans LA1 aWang, S1 aWang, T uhttp://www.iacat.org/content/relative-precision-ability-estimation-polytomous-cat-comparison-under-generalized-partial00492nas a2200097 4500008004100000245012000041210006900161260002400230100001600254856012400270 2002 eng d00aReliability and decision accuracy of linear parallel form and multi stage tests with realistic and ideal item pools0 aReliability and decision accuracy of linear parallel form and mu aWinchester, England1 aJodoin, M G uhttp://www.iacat.org/content/reliability-and-decision-accuracy-linear-parallel-form-and-multi-stage-tests-realistic-and00568nas a2200133 4500008004100000245012500041210006900166260001900235100001400254700001800268700001600286700001200302856012000314 2002 eng d00aThe robustness of the unidimensional 3PL IRT model when applied to two-dimensional data in computerized adaptive testing0 arobustness of the unidimensional 3PL IRT model when applied to t aNew Orleans LA1 aZhao, J C1 aMcMorris, R F1 aPruzek, R M1 aChen, R uhttp://www.iacat.org/content/robustness-unidimensional-3pl-irt-model-when-applied-two-dimensional-data-computerized00372nas a2200133 4500008004100000245003800041210003600079300001200115490000700127100001400134700001500148700001200163856006300175 2002 eng d00aSelf-adapted testing: An overview0 aSelfadapted testing An overview a107-1220 v121 aWise, S L1 aPonsoda, V1 aOlea, J uhttp://www.iacat.org/content/self-adapted-testing-overview00510nas a2200097 4500008004100000245014600041210006900187100001500256700001500271856012600286 2002 eng d00aSome features of the estimated sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules0 aSome features of the estimated sampling distribution of the abil1 aRaîche, G1 aBlais, J G uhttp://www.iacat.org/content/some-features-estimated-sampling-distribution-ability-estimate-computerized-adaptive-testing00531nas a2200109 4500008004100000245013600041210006900177260002000246100001500266700001400281856012600295 2002 eng d00aSome features of the sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules0 aSome features of the sampling distribution of the ability estima aNew Orleans, LA1 aBlais, J-G1 aRaiche, G uhttp://www.iacat.org/content/some-features-sampling-distribution-ability-estimate-computerized-adaptive-testing-according00449nas a2200097 4500008004100000245007500041210006900116260003300185100003000218856010300248 2002 eng d00aSTAR Math 2 Computer-Adaptive Math Test and Database: Technical Manual0 aSTAR Math 2 ComputerAdaptive Math Test and Database Technical Ma aWisconsin Rapids, WI: Author1 aRenaissance-Learning-Inc. uhttp://www.iacat.org/content/star-math-2-computer-adaptive-math-test-and-database-technical-manual00504nas a2200121 4500008004100000245009700041210006900138260001900207100001100226700001000237700001300247856012200260 2002 eng d00aStatistical indexes for monitoring item behavior under computer adaptive testing environment0 aStatistical indexes for monitoring item behavior under computer  aNew Orleans LA1 aZhu, R1 aYu, F1 aLiu, S M uhttp://www.iacat.org/content/statistical-indexes-monitoring-item-behavior-under-computer-adaptive-testing-environment00524nam a2200097 4500008004100000245010900041210006900150260006700219100001400286856012600300 2002 eng d00aStrategies for controlling item exposure in computerized adaptive testing with polytomously scored items0 aStrategies for controlling item exposure in computerized adaptiv aUnpublished doctoral dissertation, University of Texas, Austin1 aDavis, LL uhttp://www.iacat.org/content/strategies-controlling-item-exposure-computerized-adaptive-testing-polytomously-scored-ite-000562nas a2200121 4500008004100000245009500041210006900136260008200205100001300287700001200300700001300312856011500325 2002 eng d00aA strategy for controlling item exposure in multidimensional computerized adaptive testing0 astrategy for controlling item exposure in multidimensional compu aAvailable from http://www3. tat.sinica.edu.tw/library/c_tec_rep/c-2002-11.pdf1 aLee, Y H1 aIp, E H1 aFuh, C D uhttp://www.iacat.org/content/strategy-controlling-item-exposure-multidimensional-computerized-adaptive-testing02034nas a2200253 4500008004100000245010900041210006900150300000900219490000600228520114100234653002101375653001501396653003901411653002201450653002501472653001801497653002201515653005501537653001501592653001201607100001701619700002501636856011901661 2002 eng d00aA structure-based approach to psychological measurement: Matching measurement models to latent structure0 astructurebased approach to psychological measurement Matching me a4-160 v93 aThe present article sets forth the argument that psychological assessment should be based on a construct's latent structure. The authors differentiate dimensional (continuous) and taxonic (categorical) structures at the latent and manifest levels and describe the advantages of matching the assessment approach to the latent structure of a construct. A proper match will decrease measurement error, increase statistical power, clarify statistical relationships, and facilitate the location of an efficient cutting score when applicable. Thus, individuals will be placed along a continuum or assigned to classes more accurately. The authors briefly review the methods by which latent structure can be determined and outline a structure-based approach to assessment that builds on dimensional scaling models, such as item response theory, while incorporating classification methods as appropriate. Finally, the authors empirically demonstrate the utility of their approach and discuss its compatibility with traditional assessment methods and with computerized adaptive testing. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aAssessment10aClassification (Cognitive Process)10aComputer Assisted10aItem Response Theory10aPsychological10aScaling (Testing)10aStatistical Analysis computerized adaptive testing10aTaxonomies10aTesting1 aRuscio, John1 aRuscio, Ayelet Meron uhttp://www.iacat.org/content/structure-based-approach-psychological-measurement-matching-measurement-models-latent00735nas a2200121 4500008004100000245003700041210003700078300001000115490000600125520040700131100001300538856006200551 2002 eng d00aTechnology solutions for testing0 aTechnology solutions for testing a20-230 v43 aNorthwest Evaluation Association in Portland, Oregon, consults with state and local educators on assessment issues. Describes several approaches in place at school districts that are using some combination of computer-based tests to measure student growth. The computerized adaptive test adjusts items based on a student's answer in "real time." On-demand testing provides almost instant scoring. (MLF)1 aOlson, A uhttp://www.iacat.org/content/technology-solutions-testing00537nas a2200109 4500008004100000245005100041210005000092260017700142100001500319700001700334856007600351 2002 eng d00aTest models for complex computer-based testing0 aTest models for complex computerbased testing aC. N. Mille,. M. T. Potenza, J. J. Fremer, and W. C. Ward (Eds.). Computer-based testing: Building the foundation for future assessments (pp. 67-88). Hillsdale NJ: Erlbaum.1 aLuecht, RM1 aClauser, B E uhttp://www.iacat.org/content/test-models-complex-computer-based-testing00432nas a2200121 4500008004100000245006200041210006000103260001600163100001500179700001700194700001800211856008100229 2002 eng d00aA testlet assembly design for the uniform CPA examination0 atestlet assembly design for the uniform CPA examination aNew Orleans1 aLuecht, RM1 aBrumfield, T1 aBreithaupt, K uhttp://www.iacat.org/content/testlet-assembly-design-uniform-cpa-examination00471nas a2200109 4500008004100000245008900041210006900130260001900199100001900218700001200237856011200249 2002 eng d00aTo weight or not to weight – balancing influence of initial and later items in CAT0 aTo weight or not to weight balancing influence of initial and la aNew Orleans LA1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/weight-or-not-weight-%E2%80%93-balancing-influence-initial-and-later-items-cat00454nas a2200133 4500008004100000245005900041210005900100260001900159100001500178700001400193700001200207700001300219856008800232 2002 eng d00aUpdated item parameter estimates using sparse CAT data0 aUpdated item parameter estimates using sparse CAT data aNew Orleans LA1 aSmith, R L1 aRizavi, S1 aPaez, R1 aRotou, O uhttp://www.iacat.org/content/updated-item-parameter-estimates-using-sparse-cat-data00517nas a2200121 4500008004100000245009900041210006900140260001900209100001700228700001600245700001500261856011900276 2002 eng d00aUsing judgments of item difficulty to change answers on computerized adaptive vocabulary tests0 aUsing judgments of item difficulty to change answers on computer aNew Orleans LA1 aVispoel, W P1 aClough, S J1 aBleiler, T uhttp://www.iacat.org/content/using-judgments-item-difficulty-change-answers-computerized-adaptive-vocabulary-tests00509nas a2200109 4500008004100000245011100041210006900152260001900221100002000240700001500260856012400275 2002 eng d00aUsing testlet response theory to evaluate the equivalence of automatically generated multiple-choice items0 aUsing testlet response theory to evaluate the equivalence of aut aNew Orleans LA1 aWilliamson, D M1 aBejar, I I uhttp://www.iacat.org/content/using-testlet-response-theory-evaluate-equivalence-automatically-generated-multiple-choice00538nas a2200097 4500008004100000245016800041210006900209260002700278100001500305856012000320 2002 eng d00aUtility of Learning Potential Computerised Adaptive Test (LPCAT) scores in predicting academic performance of bridging students: A comparison with other predictors0 aUtility of Learning Potential Computerised Adaptive Test LPCAT s aPretoria, South Africa1 aDe Beer, M uhttp://www.iacat.org/content/utility-learning-potential-computerised-adaptive-test-lpcat-scores-predicting-academic01149nas a2200205 4500008004100000245008200041210006900123260005600192520043100248653002100679653003000700653001600730653001600746653001800762100001500780700001700795700001700812700001400829856010000843 2002 eng d00aThe work ahead: A psychometric infrastructure for computerized adaptive tests0 awork ahead A psychometric infrastructure for computerized adapti aMahwah, N.J. USAbLawrence Erlbaum Associates, Inc.3 a(From the chapter) Considers the past and future of computerized adaptive tests and computer-based tests and looks at issues and challenges confronting a testing program as it implements and operates a computer-based test. Recommendations for testing programs from The National Council of Measurement in Education Ad Hoc Committee on Computerized Adaptive Test Disclosure are appended. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aEducational10aMeasurement10aPsychometrics1 aDrasgow, F1 aPotenza, M P1 aFreemer, J J1 aWard, W C uhttp://www.iacat.org/content/work-ahead-psychometric-infrastructure-computerized-adaptive-tests00492nas a2200121 4500008004100000245008700041210006900128260001500197100001400212700001900226700001700245856010800262 2001 eng d00aAdaptation of a-stratified method in variable length computerized adaptive testing0 aAdaptation of astratified method in variable length computerized aSeattle WA1 aWen, J -B1 aChang, Hua-Hua1 aHau, K -T   uhttp://www.iacat.org/content/adaptation-stratified-method-variable-length-computerized-adaptive-testing00508nas a2200097 4500008004100000245008000041210006900121260010600190100001600296856009800312 2001 eng d00aApplication of data mining to response data in a computerized adaptive test0 aApplication of data mining to response data in a computerized ad aPaper presented at the Annual Meeting of the National Council on Measurement in Education, Seattle WA1 aMendez, F A uhttp://www.iacat.org/content/application-data-mining-response-data-computerized-adaptive-test00472nas a2200097 4500008004100000245011500041210006900156260001500225100001500240856011900255 2001 eng d00aApplication of score information for CAT pool development and its connection with "likelihood test information0 aApplication of score information for CAT pool development and it aSeattle WA1 aKrass, I A uhttp://www.iacat.org/content/application-score-information-cat-pool-development-and-its-connection-likelihood-test02224nas a2200145 4500008004100000245011600041210006900157300001100226490000600237520165200243653003401895100001301929700001601942856012001958 2001 eng d00aAssessment in the twenty-first century: A role of computerised adaptive testing in national curriculum subjects0 aAssessment in the twentyfirst century A role of computerised ada a241-570 v53 aWith the investment of large sums of money in new technologies forschools and education authorities and the subsequent training of teachers to integrate Information and Communications Technology (ICT) into their teaching strategies, it is remarkable that the old outdated models of assessment still remain. This article highlights the current problems associated with pen-and paper-testing and offers suggestions for an innovative and new approach to assessment for the twenty-first century. Based on the principle of the 'wise examiner' a computerised adaptive testing system which measures pupils' ability against the levels of the United Kingdom National Curriculum has been developed for use in mathematics. Using constructed response items, pupils are administered a test tailored to their ability with a reliability index of 0.99. Since the software administers maximally informative questions matched to each pupil's current ability estimate, no two pupils will receive the same set of items in the same order therefore removing opportunities for plagarism and teaching to the test. All marking is automated and a journal recording the outcome of the test and highlighting the areas of difficulty for each pupil is available for printing by the teacher. The current prototype of the system can be used on a school's network however the authors envisage a day when Examination Boards or the Qualifications and Assessment Authority (QCA) will administer Government tests from a central server to all United Kingdom schools or testing centres. Results will be issued at the time of testing and opportunities for resits will become more widespr10acomputerized adaptive testing1 aCowan, P1 aMorrison, H uhttp://www.iacat.org/content/assessment-twenty-first-century-role-computerised-adaptive-testing-national-curriculum00374nas a2200109 4500008004100000245005000041210004800091260002400139100001000163700001900173856007200192 2001 eng d00aa-stratified CAT design with content-blocking0 aastratified CAT design with contentblocking aKing of Prussia, PA1 aYi, Q1 aChang, Hua-Hua uhttp://www.iacat.org/content/stratified-cat-design-content-blocking00464nas a2200109 4500008004100000245008800041210006900129260001500198100001200213700001900225856011000244 2001 eng d00aa-stratified computerized adaptive testing with unequal item exposure across strata0 aastratified computerized adaptive testing with unequal item expo aSeattle WA1 aDeng, H1 aChang, Hua-Hua uhttp://www.iacat.org/content/stratified-computerized-adaptive-testing-unequal-item-exposure-across-strata00842nas a2200157 4500008004100000245007400041210006900115300001100184490000700195520030900202653003400511100001900545700001200564700001200576856009600588 2001 eng d00aa-stratified multistage computerized adaptive testing with b blocking0 aastratified multistage computerized adaptive testing with b bloc a333-410 v253 aProposed a refinement, based on the stratification of items developed by D. Weiss (1973), of the computerized adaptive testing item selection procedure of H. Chang and Z. Ying (1999). Simulation studies using an item bank from the Graduate Record Examination show the benefits of the new procedure. (SLD)10acomputerized adaptive testing1 aChang, Hua-Hua1 aQian, J1 aYang, Z uhttp://www.iacat.org/content/stratified-multistage-computerized-adaptive-testing-b-blocking01098nas a2200157 4500008004100000020001400041245007400055210006900129300001200198490000700210520058200217100001900799700001200818700001200830856009800842 2001 eng d a0146-621600aa-Stratified multistage computerized adaptive testing with b blocking0 aaStratified multistage computerized adaptive testing with b bloc a333-3410 v253 aChang & Ying’s (1999) computerized adaptive testing item-selection procedure stratifies the item bank according to a parameter values and requires b parameter values to be evenly distributed across all strata. Thus, a and b parameter values must be incorporated into how strata are formed. A refinement is proposed, based on Weiss’ (1973) stratification of items according to b values. Simulation studies using a retired item bank of a Graduate Record Examination test indicate that the new approach improved control of item exposure rates and reduced mean squared errors. 1 aChang, Hua-Hua1 aQian, J1 aYing, Z uhttp://www.iacat.org/content/stratified-multistage-computerized-adaptive-testing-b-blocking-000572nas a2200133 4500008004100000245012700041210006900168260001600237100001700253700001600270700001700286700001300303856012200316 2001 eng d00aCan examinees use judgments of item difficulty to improve proficiency estimates on computerized adaptive vocabulary tests?0 aCan examinees use judgments of item difficulty to improve profic a Seattle WA1 aVispoel, W P1 aClough, S J1 aBleiler, A B1 aIhrig, D uhttp://www.iacat.org/content/can-examinees-use-judgments-item-difficulty-improve-proficiency-estimates-computerized-000554nas a2200109 4500008004100000245013000041210006900171260004500240100001800285700001500303856012600318 2001 eng d00aCATSIB: A modified SIBTEST procedure to detect differential item functioning in computerized adaptive tests (Research report)0 aCATSIB A modified SIBTEST procedure to detect differential item  aNewton, PAbLaw School Admission Council1 aNandakumar, R1 aRoussos, L uhttp://www.iacat.org/content/catsib-modified-sibtest-procedure-detect-differential-item-functioning-computerized-adapti-000485nas a2200097 4500008004100000245009100041210006900132260005800201100001800259856011000277 2001 eng d00aCB BULATS: Examining the reliability of a computer based test using test-retest method0 aCB BULATS Examining the reliability of a computer based test usi aCambridge ESOL Research Notes, Issue 5, July 2001, pp1 aGeranpayeh, A uhttp://www.iacat.org/content/cb-bulats-examining-reliability-computer-based-test-using-test-retest-method01945nas a2200169 4500008004100000245011100041210007100152300001200223490000700235520133200242100001301574700001601587700001201603700001001615700001601625856013401641 2001 eng d00aA comparative study of on line pretest item—Calibration/scaling methods in computerized adaptive testing0 acomparative study of on line pretest item—Calibrationscaling met a191-2120 v383 aThe purpose of this study was to compare and evaluate five on-line pretest item-calibration/scaling methods in computerized adaptive testing (CAT): marginal maximum likelihood estimate with one EM cycle (OEM), marginal maximum likelihood estimate with multiple EM cycles (MEM), Stocking's Method A, Stocking's Method B, and BILOG/Prior. The five methods were evaluated in terms ofitem-parameter recovery, using three different sample sizes (300, 1000 and 3000). The MEM method appeared to be the best choice among these, because it produced the smallest parameter-estimation errors for all sample size conditions. MEM and OEM are mathematically similar, although the OEM method produced larger errors. MEM also was preferable to OEM, unless the amount of timeinvolved in iterative computation is a concern. Stocking's Method B also worked very well, but it required anchor items that either would increase test lengths or require larger sample sizes depending on test administration design. Until more appropriate ways of handling sparse data are devised, the BILOG/Prior method may not be a reasonable choice for small sample sizes. Stocking's Method A hadthe largest weighted total error, as well as a theoretical weakness (i.e., treating estimated ability as true ability); thus, there appeared to be little reason to use it1 aBan, J C1 aHanson, B A1 aWang, T1 aYi, Q1 aHarris, D J uhttp://www.iacat.org/content/comparative-study-line-pretest-item%E2%80%94calibrationscaling-methods-computerized-adaptive-testing00492nas a2200133 4500008004100000245007900041210006900120260001500189100001000204700001400214700001600228700001600244856009800260 2001 eng d00aComparison of the SPRT and CMT procedures in computerized adaptive testing0 aComparison of the SPRT and CMT procedures in computerized adapti aSeattle WA1 aYi, Q1 aHanson, B1 aWidiatmo, H1 aHarris, D J uhttp://www.iacat.org/content/comparison-sprt-and-cmt-procedures-computerized-adaptive-testing01205nas a2200121 4500008004100000245007000041210006900111300001200180490000700192520076700199100002300966856009400989 2001 eng d00aComputerized adaptive testing with equated number-correct scoring0 aComputerized adaptive testing with equated numbercorrect scoring a343-3550 v253 aA constrained computerized adaptive testing (CAT) algorithm is presented that can be used to equate CAT number-correct (NC) scores to a reference test. As a result, the CAT NC scores also are equated across administrations. The constraints are derived from van der Linden & Luecht’s (1998) set of conditions on item response functions that guarantees identical observed NC score distributions on two test forms. An item bank from the Law School Admission Test was used to compare the results of the algorithm with those for equipercentile observed-score equating, as well as the prediction of NC scores on a reference test using its test response function. The effects of the constraints on the statistical properties of the θ estimator in CAT were examined. 1 avan der Linden, WJ uhttp://www.iacat.org/content/computerized-adaptive-testing-equated-number-correct-scoring01699nas a2200229 4500008004100000245007800041210006900119300001200188490000700200520094500207653002501152653005101177653003001228653001801258653001101276653002701287653001101314100001701325700001101342700001801353856009801371 2001 eng d00aComputerized adaptive testing with the generalized graded unfolding model0 aComputerized adaptive testing with the generalized graded unfold a177-1960 v253 aExamined the use of the generalized graded unfolding model (GGUM) in computerized adaptive testing. The objective was to minimize the number of items required to produce equiprecise estimates of person locations. Simulations based on real data about college student attitudes toward abortion and on data generated to fit the GGUM were used. It was found that as few as 7 or 8 items were needed to produce accurate and precise person estimates using an expected a posteriori procedure. The number items in the item bank (20, 40, or 60 items) and their distribution on the continuum (uniform locations or item clusters in moderately extreme locations) had only small effects on the accuracy and precision of the estimates. These results suggest that adaptive testing with the GGUM is a good method for achieving estimates with an approximately uniform level of precision using a small number of items. (PsycINFO Database Record (c) 2005 APA )10aAttitude Measurement10aCollege Students computerized adaptive testing10aComputer Assisted Testing10aItem Response10aModels10aStatistical Estimation10aTheory1 aRoberts, J S1 aLin, Y1 aLaughlin, J E uhttp://www.iacat.org/content/computerized-adaptive-testing-generalized-graded-unfolding-model00496nas a2200097 4500008004100000245012000041210006900161490002600230100002000256856012200276 2001 eng d00aComputerized-adaptive versus paper-and-pencil testing environments: An experimental analysis of examinee experience0 aComputerizedadaptive versus paperandpencil testing environments 0 vDoctoral dissertation1 aBringsjord, E L uhttp://www.iacat.org/content/computerized-adaptive-versus-paper-and-pencil-testing-environments-experimental-analysis01039nas a2200145 4500008004100000245021400041210006900255300001100324490000600335520038100341100001600722700001600738700001700754856012200771 2001 eng d00aConcerns with computerized adaptive oral proficiency assessment. A commentary on "Comparing examinee attitudes Toward computer-assisted and other oral proficient assessments": Response to the Norris Commentary0 aConcerns with computerized adaptive oral proficiency assessment  a95-1080 v53 aResponds to an article on computerized adaptive second language (L2) testing, expressing concerns about the appropriateness of such tests for informing language educators about the language skills of L2 learners and users and fulfilling the intended purposes and achieving the desired consequences of language test use.The authors of the original article respond. (Author/VWL)1 aNorris, J M1 aKenyon, D M1 aMalabonga, V uhttp://www.iacat.org/content/concerns-computerized-adaptive-oral-proficiency-assessment-commentary-comparing-examinee00425nas a2200121 4500008004100000245005900041210005700100300001200157490000700169100002700176700001600203856008400219 2001 eng d00aCUSUM-based person-fit statistics for adaptive testing0 aCUSUMbased personfit statistics for adaptive testing a199-2180 v261 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/cusum-based-person-fit-statistics-adaptive-testing00480nas a2200133 4500008004100000245007400041210006900115260001200184100001100196700001600207700001000223700001400233856009900247 2001 eng d00aData sparseness and online pretest calibration/scaling methods in CAT0 aData sparseness and online pretest calibrationscaling methods in aSeattle1 aBan, J1 aHanson, B A1 aYi, Q1 aHarris, D uhttp://www.iacat.org/content/data-sparseness-and-online-pretest-calibrationscaling-methods-cat00426nas a2200121 4500008004100000245005900041210005900100260001500159100001700174700001900191700001200210856008200222 2001 eng d00aDeriving a stopping rule for sequential adaptive tests0 aDeriving a stopping rule for sequential adaptive tests aSeattle WA1 aGrabovsky, I1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/deriving-stopping-rule-sequential-adaptive-tests00454nas a2200097 4500008004100000245008100041210006900122260004200191100001900233856010400252 2001 eng d00aDetection of misfitting item-score patterns in computerized adaptive testing0 aDetection of misfitting itemscore patterns in computerized adapt aEnschede, The Netherlands: Febodruk B1 aStoop, E M L A uhttp://www.iacat.org/content/detection-misfitting-item-score-patterns-computerized-adaptive-testing00505nam a2200097 4500008004100000245009300041210006900134260007600203100001300279856011500292 2001 eng d00aDevelopment and evaluation of test assembly procedures for computerized adaptive testing0 aDevelopment and evaluation of test assembly procedures for compu aUnpublished doctoral dissertation, University of Massachusetts, Amherst1 aRobin, F uhttp://www.iacat.org/content/development-and-evaluation-test-assembly-procedures-computerized-adaptive-testing00552nas a2200157 4500008004100000245008100041210006900122300001200191490000700203100002000210700001600230700001600246700001700262700001400279856010100293 2001 eng d00aDevelopment of an adaptive multimedia program to collect patient health data0 aDevelopment of an adaptive multimedia program to collect patient a320-3240 v211 aSutherland, L A1 aCampbell, M1 aOrnstein, K1 aWildemuth, B1 aLobach, D uhttp://www.iacat.org/content/development-adaptive-multimedia-program-collect-patient-health-data00457nas a2200097 4500008004100000245009000041210006900131260002500200100003300225856010100258 2001 eng d00aThe Development of STAR Early Literacy: A report of the School Renaissance Institute.0 aDevelopment of STAR Early Literacy A report of the School Renais aMadison, WI: Author.1 aSchool-Renaissance-Institute uhttp://www.iacat.org/content/development-star-early-literacy-report-school-renaissance-institute01969nas a2200193 4500008004100000245008600041210006900127300001000196490000700206520131400213653001401527653003001541653002501571653001101596653003601607653001401643100001501657856010301672 2001 eng d00aDevelopments in measurement of persons and items by means of item response models0 aDevelopments in measurement of persons and items by means of ite a65-940 v283 aThis paper starts with a general introduction into measurement of hypothetical constructs typical of the social and behavioral sciences. After the stages ranging from theory through operationalization and item domain to preliminary test or questionnaire have been treated, the general assumptions of item response theory are discussed. The family of parametric item response models for dichotomous items is introduced and it is explained how parameters for respondents and items are estimated from the scores collected from a sample of respondents who took the test or questionnaire. Next, the family of nonparametric item response models is explained, followed by the 3 classes of item response models for polytomous item scores (e.g., rating scale scores). Then, to what degree the mean item score and the unweighted sum of item scores for persons are useful for measuring items and persons in the context of item response theory is discussed. Methods for fitting parametric and nonparametric models to data are briefly discussed. Finally, the main applications of item response models are discussed, which include equating and item banking, computerized and adaptive testing, research into differential item functioning, person fit research, and cognitive modeling. (PsycINFO Database Record (c) 2005 APA )10aCognitive10aComputer Assisted Testing10aItem Response Theory10aModels10aNonparametric Statistical Tests10aProcesses1 aSijtsma, K uhttp://www.iacat.org/content/developments-measurement-persons-and-items-means-item-response-models01617nas a2200193 4500008004100000245008600041210006900127300001200196490000700208520094500215653002101160653003001181653004101211653000901252653001701261100001601278700001701294856011201311 2001 eng d00aDifferences between self-adapted and computerized adaptive tests: A meta-analysis0 aDifferences between selfadapted and computerized adaptive tests  a235-2470 v383 aSelf-adapted testing has been described as a variation of computerized adaptive testing that reduces test anxiety and thereby enhances test performance. The purpose of this study was to gain a better understanding of these proposed effects of self-adapted tests (SATs); meta-analysis procedures were used to estimate differences between SATs and computerized adaptive tests (CATs) in proficiency estimates and post-test anxiety levels across studies in which these two types of tests have been compared. After controlling for measurement error the results showed that SATs yielded proficiency estimates that were 0.12 standard deviation units higher and post-test anxiety levels that were 0.19 standard deviation units lower than those yielded by CATs. The authors speculate about possible reasons for these differences and discuss advantages and disadvantages of using SATs in operational settings. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aScores computerized adaptive testing10aTest10aTest Anxiety1 aPitkin, A K1 aVispoel, W P uhttp://www.iacat.org/content/differences-between-self-adapted-and-computerized-adaptive-tests-meta-analysis00525nas a2200109 4500008004100000245013200041210006900173260001500242100001400257700001900271856012500290 2001 eng d00aThe effect of test and examinee characteristics on the occurrence of aberrant response patterns in a computerized adaptive test0 aeffect of test and examinee characteristics on the occurrence of aSeattle WA1 aRizavi, S1 aSwaminathan, H uhttp://www.iacat.org/content/effect-test-and-examinee-characteristics-occurrence-aberrant-response-patterns-computerized00481nas a2200097 4500008004100000245012400041210006900165260001500234100001600249856011800265 2001 eng d00aEffective use of simulated data in an on-line item calibration in practical situations of computerized adaptive testing0 aEffective use of simulated data in an online item calibration in aSeattle WA1 aSamejima, F uhttp://www.iacat.org/content/effective-use-simulated-data-line-item-calibration-practical-situations-computerized00482nas a2200109 4500008003900000245010300039210006900142260001500211100001500226700001300241856011800254 2001 d00aEffects of changes in the examinees’ ability distribution on the exposure control methods in CAT0 aEffects of changes in the examinees ability distribution on the  aSeattle WA1 aChang, S-W1 aTwu, B-Y uhttp://www.iacat.org/content/effects-changes-examinees%E2%80%99-ability-distribution-exposure-control-methods-cat00472nas a2200097 4500008004100000245011000041210006900151260001500220100001600235856012300251 2001 eng d00aEfficient on-line item calibration using a nonparametric method adjusted to computerized adaptive testing0 aEfficient online item calibration using a nonparametric method a aSeattle WA1 aSamejima, F uhttp://www.iacat.org/content/efficient-line-item-calibration-using-nonparametric-method-adjusted-computerized-adaptive01840nas a2200229 4500008004100000245007400041210006900115300001000184490000700194520110700201653002101308653000901329653004801338653001801386653002801404653002401432653001501456100001601471700001701487700001601504856009001520 2001 eng d00aEvaluation of an MMPI-A short form: Implications for adaptive testing0 aEvaluation of an MMPIA short form Implications for adaptive test a76-890 v763 aReports some psychometric properties of an MMPI-Adolescent version (MMPI-A; J. N. Butcher et al, 1992) short form based on administration of the 1st 150 items of this test instrument. The authors report results for both the MMPI-A normative sample of 1,620 adolescents (aged 14-18 yrs) and a clinical sample of 565 adolescents (mean age 15.2 yrs) in a variety of treatment settings. The authors summarize results for the MMPI-A basic scales in terms of Pearson product-moment correlations generated between full administration and short-form administration formats and mean T score elevations for the basic scales generated by each approach. In this investigation, the authors also examine single-scale and 2-point congruences found for the MMPI-A basic clinical scales as derived from standard and short-form administrations. The authors present the relative strengths and weaknesses of the MMPI-A short form and discuss the findings in terms of implications for attempts to shorten the item pool through the use of computerized adaptive assessment approaches. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aMean10aMinnesota Multiphasic Personality Inventory10aPsychometrics10aStatistical Correlation10aStatistical Samples10aTest Forms1 aArcher, R P1 aTirrell, C A1 aElkins, D E uhttp://www.iacat.org/content/evaluation-mmpi-short-form-implications-adaptive-testing00518nas a2200133 4500008003900000245009600039210006900135300000900204490000700213100001600220700001800236700001800254856011200272 2001 d00aAn examination of conditioning variables used in computer adaptive testing for DIF analyses0 aexamination of conditioning variables used in computer adaptive  a3-160 v141 aWalker, C M1 aBeretvas, S N1 aAckerman, T A uhttp://www.iacat.org/content/examination-conditioning-variables-used-computer-adaptive-testing-dif-analyses00478nas a2200109 4500008004100000245009900041210006900140260001500209100001400224700001700238856011300255 2001 eng d00aAn examination of item review on a CAT using the specific information item selection algorithm0 aexamination of item review on a CAT using the specific informati aSeattle WA1 aBowles, R1 aPommerich, M uhttp://www.iacat.org/content/examination-item-review-cat-using-specific-information-item-selection-algorithm00480nas a2200109 4500008004100000245009900041210006900140260001500209100001400224700001700238856011500255 2001 eng d00aAn examination of item review on a CAT using the specific information item selection algorithm0 aexamination of item review on a CAT using the specific informati aSeattle WA1 aBowles, R1 aPommerich, M uhttp://www.iacat.org/content/examination-item-review-cat-using-specific-information-item-selection-algorithm-000407nas a2200097 4500008004100000245006100041210005800102260005400160100001400214856008100228 2001 eng d00aAn examination of item review on computer adaptive tests0 aexamination of item review on computer adaptive tests aManuscript in preparation, University of Virginia1 aBowles, R uhttp://www.iacat.org/content/examination-item-review-computer-adaptive-tests00531nas a2200121 4500008004100000245011100041210006900152260001500221100001500236700001900251700001300270856012600283 2001 eng d00aAn examination of item selection rules by stratified CAT designs integrated with content balancing methods0 aexamination of item selection rules by stratified CAT designs in aSeattle WA1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/examination-item-selection-rules-stratified-cat-designs-integrated-content-balancing-methods00551nas a2200109 4500008004100000245011200041210006900153260006800222100001400290700001400304856012300318 2001 eng d00aAn examination of testlet scoring and item exposure constraints in the verbal reasoning section of the MCAT0 aexamination of testlet scoring and item exposure constraints in  aMCAT Monograph Series: Association of American Medical Colleges1 aDavis, LL1 aDodd, B G uhttp://www.iacat.org/content/examination-testlet-scoring-and-item-exposure-constraints-verbal-reasoning-section-mcat-000469nas a2200097 4500008004100000245011200041210006900153100001400222700001400236856012100250 2001 eng d00aAn examination of testlet scoring and item exposure constraints in the Verbal Reasoning section of the MCAT0 aexamination of testlet scoring and item exposure constraints in 1 aDavis, LL1 aDodd, B G uhttp://www.iacat.org/content/examination-testlet-scoring-and-item-exposure-constraints-verbal-reasoning-section-mcat02101nas a2200337 4500008004100000245014400041210006900185300001200254490000700266520096600273653002501239653003601264653002501300653001001325653003001335653001101365653001001376653000901386653003101395653003201426653003601458653003401494653002001528100001601548700001401564700001601578700001901594700001301613700001501626856012201641 2001 eng d00aAn examination of the comparative reliability, validity, and accuracy of performance ratings made using computerized adaptive rating scales0 aexamination of the comparative reliability validity and accuracy a965-9730 v863 aThis laboratory research compared the reliability, validity, and accuracy of a computerized adaptive rating scale (CARS) format and 2 relatively common and representative rating formats. The CARS is a paired-comparison rating task that uses adaptive testing principles to present pairs of scaled behavioral statements to the rater to iteratively estimate a ratee's effectiveness on 3 dimensions of contextual performance. Videotaped vignettes of 6 office workers were prepared, depicting prescripted levels of contextual performance, and 112 subjects rated these vignettes using the CARS format and one or the other competing format. Results showed 23%-37% lower standard errors of measurement for the CARS format. In addition, validity was significantly higher for the CARS format (d = .18), and Cronbach's accuracy coefficients showed significantly higher accuracy, with a median effect size of .08. The discussion focuses on possible reasons for the results.10a*Computer Simulation10a*Employee Performance Appraisal10a*Personnel Selection10aAdult10aAutomatic Data Processing10aFemale10aHuman10aMale10aReproducibility of Results10aSensitivity and Specificity10aSupport, U.S. Gov't, Non-P.H.S.10aTask Performance and Analysis10aVideo Recording1 aBorman, W C1 aBuck, D E1 aHanson, M A1 aMotowidlo, S J1 aStark, S1 aDrasgow, F uhttp://www.iacat.org/content/examination-comparative-reliability-validity-and-accuracy-performance-ratings-made-using00444nam a2200097 4500008004100000245007800041210006900119260002400188100003500212856009900247 2001 eng d00aThe FastTEST Professional Testing System, Version 1.6 [Computer software]0 aFastTEST Professional Testing System Version 16 Computer softwar aSt. Paul MN: Author1 aAssessment-Systems-Corporation uhttp://www.iacat.org/content/fasttest-professional-testing-system-version-16-computer-software00682nas a2200133 4500008004100000245001800041210001700059300001000076490000800086520036100094653003400455100001300489856004600502 2001 eng d00aFinal answer?0 aFinal answer a24-260 v1883 aThe Northwest Evaluation Association helped an Indiana school district develop a computerized adaptive testing system that was aligned with its curriculum and geared toward measuring individual student growth. Now the district can obtain such information from semester to semester and year to year, get immediate results, and test students on demand. (MLH)10acomputerized adaptive testing1 aCoyle, J uhttp://www.iacat.org/content/final-answer00426nas a2200121 4500008004100000245006500041210006500106260001500171100001100186700001100197700001100208856008500219 2001 eng d00aImpact of item location effects on ability estimation in CAT0 aImpact of item location effects on ability estimation in CAT aSeattle WA1 aLiu, M1 aZhu, R1 aGuo, F uhttp://www.iacat.org/content/impact-item-location-effects-ability-estimation-cat00441nas a2200133 4500008004100000245005900041210005900100260001500159100001000174700001600184700001300200700001600213856007800229 2001 eng d00aImpact of scoring options for not reached items in CAT0 aImpact of scoring options for not reached items in CAT aSeattle WA1 aYi, Q1 aWidiatmo, H1 aBan, J-C1 aHarris, D J uhttp://www.iacat.org/content/impact-scoring-options-not-reached-items-cat00500nas a2200109 4500008004100000245011600041210006900157260001500226100001200241700001800253856011900271 2001 eng d00aImpact of several computer-based testing variables on the psychometric properties of credentialing examinations0 aImpact of several computerbased testing variables on the psychom aSeattle WA1 aXing, D1 aHambleton, RK uhttp://www.iacat.org/content/impact-several-computer-based-testing-variables-psychometric-properties-credentialing00621nas a2200109 4500008004100000245018300041210006900224260006700293100001200360700001800372856012100390 2001 eng d00aImpact of several computer-based testing variables on the psychometric properties of credentialing examinations (Laboratory of Psychometric and Evaluative Research Report No 393)0 aImpact of several computerbased testing variables on the psychom aAmherst, MA: University of Massachusetts, School of Education.1 aXing, D1 aHambleton, RK uhttp://www.iacat.org/content/impact-several-computer-based-testing-variables-psychometric-properties-credentialing-000420nas a2200097 4500008004100000245007200041210006900113260003000182100001800212856009200230 2001 eng d00aImplementing constrained CAT with shadow tests for large item pools0 aImplementing constrained CAT with shadow tests for large item po aSubmitted for publication1 aVeldkamp, B P uhttp://www.iacat.org/content/implementing-constrained-cat-shadow-tests-large-item-pools00589nas a2200109 4500008004100000245012400041210006900165260008200234100001900316700002300335856012100358 2001 eng d00aImplementing content constraints in a-stratified adaptive testing using a shadow test approach (Research Report 01-001)0 aImplementing content constraints in astratified adaptive testing aUniversity of Twente, Department of Educational Measurement and Data Analysis1 aChang, Hua-Hua1 avan der Linden, WJ uhttp://www.iacat.org/content/implementing-content-constraints-stratified-adaptive-testing-using-shadow-test-approach00474nas a2200109 4500008004100000245008400041210006900125260004000194100001200234700001500246856010300261 2001 eng d00aThe influence of item characteristics and administration position on CAT Scores0 ainfluence of item characteristics and administration position on aHudson Valley, NY, October 26, 20011 aWang, L1 aGawlick, L uhttp://www.iacat.org/content/influence-item-characteristics-and-administration-position-cat-scores00494nas a2200121 4500008004100000245008700041210006900128260001500197100001600212700001900228700001300247856011200260 2001 eng d00aIntegrating stratification and information approaches for multiple constrained CAT0 aIntegrating stratification and information approaches for multip aSeattle WA1 aLeung, C -I1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/integrating-stratification-and-information-approaches-multiple-constrained-cat00574nas a2200133 4500008004100000245014400041210006900185260001500254100001500269700001100284700001300295700000900308856012300317 2001 eng d00aAn investigation of procedures for estimating error indexes in proficiency estimation in a realistic second-order equitable CAT environment0 ainvestigation of procedures for estimating error indexes in prof aSeattle WA1 aShyu, C -Y1 aFan, M1 aThompson1 aHsu. uhttp://www.iacat.org/content/investigation-procedures-estimating-error-indexes-proficiency-estimation-realistic-second00493nas a2200121 4500008004100000245009500041210006900136260001500205100001800220700001400238700001900252856010000271 2001 eng d00aAn investigation of the impact of items that exhibit mild DIF on ability estimation in CAT0 ainvestigation of the impact of items that exhibit mild DIF on ab aSeattle WA1 aJennings, J A1 aDodd, B G1 aFitzpatrick, S uhttp://www.iacat.org/content/investigation-impact-items-exhibit-mild-dif-ability-estimation-cat00583nas a2200121 4500008004100000245015600041210006900197260002600266100001500292700001500307700002000322856011900342 2001 eng d00aItem and passage selection algorithm simulations for a computerized adaptive version of the verbal section of the Medical College Admission Test (MCAT)0 aItem and passage selection algorithm simulations for a computeri aMCAT Monograph Series1 aSmith, R W1 aPlake, B S1 ade Ayala, R. J. uhttp://www.iacat.org/content/item-and-passage-selection-algorithm-simulations-computerized-adaptive-version-verbal00362nas a2200097 4500008004100000245005300041210005300094260002000147100001700167856008000184 2001 eng d00aItem pool design for computerized adaptive tests0 aItem pool design for computerized adaptive tests aAachen, Germany1 aReckase, M D uhttp://www.iacat.org/content/item-pool-design-computerized-adaptive-tests-001465nas a2200253 4500008004100000245013900041210006900180260005000249300001200299520053700311653002100848653002500869653001200894653002900906653002200935653002700957653002600984653001501010653001601025100001501041700001601056700001701072856012201089 2001 eng d00aItem response theory applied to combinations of multiple-choice and constructed-response items--approximation methods for scale scores0 aItem response theory applied to combinations of multiplechoice a aMahwah, N.J. USAbLawrence Erlbaum Associates a289-3153 a(From the chapter) The authors develop approximate methods that replace the scoring tables with weighted linear combinations of the component scores. Topics discussed include: a linear approximation for the extension to combinations of scores; the generalization of two or more scores; potential applications of linear approximations to item response theory in computerized adaptive tests; and evaluation of the pattern-of-summed-scores, and Gaussian approximation, estimates of proficiency. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aItem Response Theory10aMethod)10aMultiple Choice (Testing10aScoring (Testing)10aStatistical Estimation10aStatistical Weighting10aTest Items10aTest Scores1 aThissen, D1 aNelson, L A1 aSwygert, K A uhttp://www.iacat.org/content/item-response-theory-applied-combinations-multiple-choice-and-constructed-response-items01985nas a2200205 4500008004100000245010100041210006900142300001200211490000700223520124900230653001201479653002101491653003001512653001501542653001601557653004501573100001701618700001901635856012501654 2001 eng d00aItem selection in computerized adaptive testing: Should more discriminating items be used first?0 aItem selection in computerized adaptive testing Should more disc a249-2660 v383 aDuring computerized adaptive testing (CAT), items are selected continuously according to the test-taker's estimated ability. Test security has become a problem because high-discrimination items are more likely to be selected and become overexposed. So, there seems to be a tradeoff between high efficiency in ability estimations and balanced usage of items. This series of four studies addressed the dilemma by focusing on the notion of whether more or less discriminating items should be used first in CAT. The first study demonstrated that the common maximum information method with J. B. Sympson and R. D. Hetter (1985) control resulted in the use of more discriminating items first. The remaining studies showed that using items in the reverse order, as described in H. Chang and Z. Yings (1999) stratified method had potential advantages: (a) a more balanced item usage and (b) a relatively stable resultant item pool structure with easy and inexpensive management. This stratified method may have ability-estimation efficiency better than or close to that of other methods. It is argued that the judicious selection of items, as in the stratified method, is a more active control of item exposure. (PsycINFO Database Record (c) 2005 APA )10aability10aAdaptive Testing10aComputer Assisted Testing10aEstimation10aStatistical10aTest Items computerized adaptive testing1 aHau, Kit-Tai1 aChang, Hua-Hua uhttp://www.iacat.org/content/item-selection-computerized-adaptive-testing-should-more-discriminating-items-be-used-first00497nas a2200145 4500008004100000245007200041210006900113300001000182490000700192100001400199700001400213700001900227700001200246856009300258 2001 eng d00aOn maximizing item information and matching difficulty with ability0 amaximizing item information and matching difficulty with ability a69-770 v661 aBickel, P1 aBuyske, S1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/maximizing-item-information-and-matching-difficulty-ability00450nas a2200109 4500008004100000245007700041210006900118260002100187100001400208700001500222856010300237 2001 eng d00aMeasurement efficiency of multidimensional computerized adaptive testing0 aMeasurement efficiency of multidimensional computerized adaptive aSan Francisco CA1 aWang, W-C1 aChen, B -H uhttp://www.iacat.org/content/measurement-efficiency-multidimensional-computerized-adaptive-testing00489nas a2200097 4500008004100000245013100041210006900172260001500241100001600256856011900272 2001 eng d00aMeasuring test compromise in high-stakes computerized adaptive testing: A Bayesian Strategy for surrogate test-taker detection0 aMeasuring test compromise in highstakes computerized adaptive te aSeattle WA1 aSegall, D O uhttp://www.iacat.org/content/measuring-test-compromise-high-stakes-computerized-adaptive-testing-bayesian-strategy00576nas a2200121 4500008004100000245012500041210006900166260004600235100001800281700001500299700001600314856012400330 2001 eng d00aA method for building a realistic model of test taker behavior for computerized adaptive testing (Research Report 01-22)0 amethod for building a realistic model of test taker behavior for aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aSteffen, M1 aEignor, D R uhttp://www.iacat.org/content/method-building-realistic-model-test-taker-behavior-computerized-adaptive-testing-research00401nas a2200097 4500008004100000245007100041210006900112260001500181100001600196856009100212 2001 eng d00aMethods to test invariant ability across subgroups of items in CAT0 aMethods to test invariant ability across subgroups of items in C aSeattle WA1 aMeijer, R R uhttp://www.iacat.org/content/methods-test-invariant-ability-across-subgroups-items-cat00448nas a2200109 4500008004100000245009100041210006900132300001200201490000700213100001300220856010500233 2001 eng d00aA minimax procedure in the context of sequential testing problems in psychodiagnostics0 aminimax procedure in the context of sequential testing problems  a139-1590 v541 aVos, H J uhttp://www.iacat.org/content/minimax-procedure-context-sequential-testing-problems-psychodiagnostics00381nas a2200109 4500008004100000245005100041210005100092260001500143100001600158700002300174856007400197 2001 eng d00aModeling variability in item parameters in CAT0 aModeling variability in item parameters in CAT aSeattle WA1 aGlas, C A W1 avan der Linden, WJ uhttp://www.iacat.org/content/modeling-variability-item-parameters-cat00503nas a2200133 4500008004100000245007900041210006900120260002400189100001500213700001400228700001700242700001200259856009800271 2001 eng d00aMonitoring items for changes in performance in computerized adaptive tests0 aMonitoring items for changes in performance in computerized adap aSeattle, Washington1 aSmith, R L1 aWang, M M1 aWingersky, M1 aZhao, C uhttp://www.iacat.org/content/monitoring-items-changes-performance-computerized-adaptive-tests00435nas a2200121 4500008004100000245006800041210006400109260001500173100001600188700001500204700001600219856007800235 2001 eng d00aA monte carlo study of the feasibility of on-the-fly assessment0 amonte carlo study of the feasibility of onthefly assessment aSeattle WA1 aRevuelta, J1 aBejar, I I1 aStocking, M uhttp://www.iacat.org/content/monte-carlo-study-feasibility-fly-assessment03152nas a2200133 4500008004100000245007900041210006900120300000900189490000700198520266000205653003402865100001502899856010402914 2001 eng d00aMultidimensional adaptive testing using the weighted likelihood estimation0 aMultidimensional adaptive testing using the weighted likelihood  a47460 v613 aThis study extended Warm's (1989) weighted likelihood estimation (WLE) to a multidimensional computerized adaptive test (MCAT) setting. WLE was compared with the maximum likelihood estimation (MLE), expected a posteriori (EAP), and maximum a posteriori (MAP) using a three-dimensional 3PL IRT model under a variety of computerized adaptive testing conditions. The dependent variables included bias, standard error of ability estimates (SE), square root of mean square error (RMSE), and test information. The independent variables were ability estimation methods, intercorrelation levels between dimensions, multidimensional structures, and ability combinations. Simulation results were presented in terms of descriptive statistics, such as figures and tables. In addition, inferential procedures were used to analyze bias by conceptualizing this Monte Carlo study as a statistical sampling experiment. The results of this study indicate that WLE and the other three estimation methods yield significantly more accurate ability estimates under an approximate simple test structure with one dominant dimension and several secondary dimensions. All four estimation methods, especially WLE, yield very large SEs when a three equally dominant multidimensional structure was employed. Consistent with previous findings based on unidimensional IRT model, MLE and WLE are less biased in the extreme of the ability scale; MLE and WLE yield larger SEs than the Bayesian methods; test information-based SEs underestimate actual SEs for both MLE and WLE in MCAT situations, especially at shorter test lengths; WLE reduced the bias of MLE under the approximate simple structure; test information-based SEs underestimates the actual SEs of MLE and WLE estimators in the MCAT conditions, similar to the findings of Warm (1989) in the unidimensional case. The results from the MCAT simulations did show some advantages of WLE in reducing the bias of MLE under the approximate simple structure with a fixed test length of 50 items, which was consistent with the previous research findings based on different unidimensional models. It is clear from the current results that all four methods perform very poorly when the multidimensional structures with multiple dominant factors were employed. More research efforts are urged to investigate systematically how different multidimensional structures affect the accuracy and reliability of ability estimation. Based on the simulated results in this study, there is no significant effect found on the ability estimation from the intercorrelation between dimensions. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aTseng, F-L uhttp://www.iacat.org/content/multidimensional-adaptive-testing-using-weighted-likelihood-estimation00502nas a2200109 4500008004100000245011100041210006900152260001500221100001600236700001400252856012600266 2001 eng d00aMultidimensional adaptive testing using weighted likelihood estimation: A comparison of estimation methods0 aMultidimensional adaptive testing using weighted likelihood esti aSeattle WA1 aTseng, F -E1 aHsu, T -C uhttp://www.iacat.org/content/multidimensional-adaptive-testing-using-weighted-likelihood-estimation-comparison-estimation00424nas a2200109 4500008004100000245006700041210006600108260001500174100001300189700001600202856009600218 2001 eng d00aMultidimensional IRT-based adaptive sequential mastery testing0 aMultidimensional IRTbased adaptive sequential mastery testing aSeattle WA1 aVos, H J1 aGlas, C E W uhttp://www.iacat.org/content/multidimensional-irt-based-adaptive-sequential-mastery-testing02031nas a2200253 4500008004100000245007700041210006900118260001200187300001200199490000700211520125800218653003901476653002901515653001501544653001001559653001101569653001101580653000901591653003001600653001301630100001601643700002001659856009801679 2001 eng d00aNCLEX-RN performance: predicting success on the computerized examination0 aNCLEXRN performance predicting success on the computerized exami cJul-Aug a158-1650 v173 aSince the adoption of the Computerized Adaptive Testing (CAT) format of the National Certification Licensure Examination for Registered Nurses (NCLEX-RN), no studies have been reported in the literature on predictors of successful performance by baccalaureate nursing graduates on the licensure examination. In this study, a discriminant analysis was used to identify which of 21 variables can be significant predictors of success on the CAT NCLEX-RN. The convenience sample consisted of 289 individuals who graduated from a baccalaureate nursing program between 1995 and 1998. Seven significant predictor variables were identified. The total number of C+ or lower grades earned in nursing theory courses was the best predictor, followed by grades in several individual nursing courses. More than 93 per cent of graduates were correctly classified. Ninety-four per cent of NCLEX "passes" were correctly classified, as were 92 per cent of NCLEX failures. This degree of accuracy in classifying CAT NCLEX-RN failures represents a marked improvement over results reported in previous studies of licensure examinations, and suggests the discriminant function will be helpful in identifying future students in danger of failure. J Prof Nurs 17:158-165, 2001.10a*Education, Nursing, Baccalaureate10a*Educational Measurement10a*Licensure10aAdult10aFemale10aHumans10aMale10aPredictive Value of Tests10aSoftware1 aBeeman, P B1 aWaterhouse, J K uhttp://www.iacat.org/content/nclex-rn-performance-predicting-success-computerized-examination00587nas a2200133 4500008004100000245013700041210006900178260001500247100001800262700001700280700001600297700001700313856012300330 2001 eng d00aNearest neighbors, simple strata, and probabilistic parameters: An empirical comparison of methods for item exposure control in CATs0 aNearest neighbors simple strata and probabilistic parameters An  aSeattle WA1 aParshall, C G1 aKromrey, J D1 aHarmes, J C1 aSentovich, C uhttp://www.iacat.org/content/nearest-neighbors-simple-strata-and-probabilistic-parameters-empirical-comparison-methods00406nas a2200097 4500008004100000245007400041210006900115260001500184100001400199856009500213 2001 eng d00aA new approach to simulation studies in computerized adaptive testing0 anew approach to simulation studies in computerized adaptive test aSeattle WA1 aChen, S-Y uhttp://www.iacat.org/content/new-approach-simulation-studies-computerized-adaptive-testing00471nas a2200109 4500008004100000245010000041210006900141300001200210490000700222100001200229856012000241 2001 eng d00aA new computer algorithm for simultaneous test construction of two-stage and multistage testing0 anew computer algorithm for simultaneous test construction of two a180-1980 v261 aWu, I L uhttp://www.iacat.org/content/new-computer-algorithm-simultaneous-test-construction-two-stage-and-multistage-testing01859nas a2200193 4500008004100000245012400041210007100165300001200236490000700248520110700255653002101362653002601383653002201409653001401431653005901445100001601504700001701520856012801537 2001 eng d00aNouveaux développements dans le domaine du testing informatisé [New developments in the area of computerized testing]0 aNouveaux développements dans le domaine du testing informatisé N a221-2300 v463 aL'usage de l'évaluation assistée par ordinateur s'est fortement développé depuis la première formulation de ses principes de base dans les années soixante et soixante-dix. Cet article offre une introduction aux derniers développements dans le domaine de l'évaluation assistée par ordinateur, en particulier celui du testing adaptative informatisée (TAI). L'estimation de l'aptitude, la sélection des items et le développement d'une base d'items dans le cas du TAI sont discutés. De plus, des exemples d'utilisations innovantes de l'ordinateur dans des systèmes intégrés de testing et de testing via Internet sont présentés. L'article se termine par quelques illustrations de nouvelles applications du testing informatisé et des suggestions pour des recherches futures.Discusses the latest developments in computerized psychological assessment, with emphasis on computerized adaptive testing (CAT). Ability estimation, item selection, and item pool development in CAT are described. Examples of some innovative approaches to CAT are presented. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Applications10aComputer Assisted10aDiagnosis10aPsychological Assessment computerized adaptive testing1 aMeijer, R R1 aGrégoire, J uhttp://www.iacat.org/content/nouveaux-d%C3%A9veloppements-dans-le-domaine-du-testing-informatis%C3%A9-new-developments-area00521nas a2200121 4500008004100000245010800041210006900149260002400218100001100242700001300253700001200266856012100278 2001 eng d00aOn-line Calibration Using PARSCALE Item Specific Prior Method: Changing Test Population and Sample Size0 aOnline Calibration Using PARSCALE Item Specific Prior Method Cha aSeattle, Washington1 aGuo, F1 aStone, E1 aCruz, D uhttp://www.iacat.org/content/line-calibration-using-parscale-item-specific-prior-method-changing-test-population-and00609nas a2200121 4500008004100000245017700041210006900218260002700287100001600314700001700330700001800347856012200365 2001 eng d00aOnline item parameter recalibration: Application of missing data treatments to overcome the effects of sparse data conditions in a computerized adaptive version of the MCAT0 aOnline item parameter recalibration Application of missing data  aUnpublished manuscript1 aHarmes, J C1 aKromrey, J D1 aParshall, C G uhttp://www.iacat.org/content/online-item-parameter-recalibration-application-missing-data-treatments-overcome-effects01705nas a2200181 4500008004100000245007300041210006900114300001100183490000700194520110100201653002101302653003001323653002501353653001501378100001701393700001501410856009801425 2001 eng d00aOutlier measures and norming methods for computerized adaptive tests0 aOutlier measures and norming methods for computerized adaptive t a85-1040 v263 aNotes that the problem of identifying outliers has 2 important aspects: the choice of outlier measures and the method to assess the degree of outlyingness (norming) of those measures. Several classes of measures for identifying outliers in Computerized Adaptive Tests (CATs) are introduced. Some of these measures are constructed to take advantage of CATs' sequential choice of items; other measures are taken directly from paper and pencil (P&P) tests and are used for baseline comparisons. Assessing the degree of outlyingness of CAT responses, however, can not be applied directly from P&P tests because stopping rules associated with CATs yield examinee responses of varying lengths. Standard outlier measures are highly correlated with the varying lengths which makes comparison across examinees impossible. Therefore, 4 methods are presented and compared which map outlier statistics to a familiar probability scale (a p value). The methods are explored in the context of CAT data from a 1995 Nationally Administered Computerized Examination (NACE). (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aStatistical Analysis10aTest Norms1 aBradlow, E T1 aWeiss, R E uhttp://www.iacat.org/content/outlier-measures-and-norming-methods-computerized-adaptive-tests00519nas a2200097 4500008004100000245013000041210006900171260004000240100001600280856012500296 2001 eng d00aOverexposure and underexposure of items in computerized adaptive testing (Measurement and Research Department Reports 2001-1)0 aOverexposure and underexposure of items in computerized adaptive aArnhem, The Netherlands: CITO Groep1 aEggen, Theo uhttp://www.iacat.org/content/overexposure-and-underexposure-items-computerized-adaptive-testing-measurement-and-research02337nas a2200157 4500008004100000020001400041245019300055210006900248300001200317490000700329520164900336653003401985100001402019700001502033856013102048 2001 eng d a0214-991500aPasado, presente y futuro de los test adaptativos informatizados: Entrevista con Isaac I. Béjar [Past, present and future of computerized adaptive testing: Interview with Isaac I. Béjar]0 aPasado presente y futuro de los test adaptativos informatizados  a685-6900 v133 aEn este artículo se presenta el resultado de una entrevista con Isaac I. Bejar. El Dr. Bejar es actualmente Investigador Científico Principal y Director del Centro para el Diseño de Evaluación y Sistemas de Puntuación perteneciente a la División de Investigación del Servicio de Medición Educativa (Educa - tional Testing Service, Princeton, NJ, EE.UU.). El objetivo de esta entrevista fue conversar sobre el pasado, presente y futuro de los Tests Adaptativos Informatizados. En la entrevista se recogen los inicios de los Tests Adaptativos y de los Tests Adaptativos Informatizados y últimos avances que se desarrollan en el Educational Testing Service sobre este tipo de tests (modelos generativos, isomorfos, puntuación automática de ítems de ensayo…). Se finaliza con la visión de futuro de los Tests Adaptativos Informatizados y su utilización en España.Past, present and future of Computerized Adaptive Testing: Interview with Isaac I. Bejar. In this paper the results of an interview with Isaac I. Bejar are presented. Dr. Bejar is currently Principal Research Scientist and Director of Center for Assessment Design and Scoring, in Research Division at Educational Testing Service (Princeton, NJ, U.S.A.). The aim of this interview was to review the past, present and future of the Computerized Adaptive Tests. The beginnings of the Adaptive Tests and Computerized Adaptive Tests, and the latest advances developed at the Educational Testing Service (generative response models, isomorphs, automated scoring…) are reviewed. The future of Computerized Adaptive Tests is analyzed, and its utilization in Spain commented.10acomputerized adaptive testing1 aTejada, R1 aAntonio, J uhttp://www.iacat.org/content/pasado-presente-y-futuro-de-los-test-adaptativos-informatizados-entrevista-con-isaac-i-b%C3%A9jar00898nas a2200121 4500008004100000245007300041210006900114490001100183520045200194100001500646700001900661856009600680 2001 eng d00aPolytomous modeling of cognitive errors in computer adaptive testing0 aPolytomous modeling of cognitive errors in computer adaptive tes0 v2 (4).3 aUsed Monte Carlo simulation to compare the relative measurement efficiency of polytomous modeling and dichotomous modeling under different scoring schemes and termination criteria. Results suggest that polytomous computerized adaptive testing (CAT) yields marginal gains over dichotomous CAT when termination criteria are more stringent. Discusses conditions under which polytomous CAT cannot prevent the nonuniform gain in test information. (SLD)1 aWang, L -S1 aLi., Chun-Shan uhttp://www.iacat.org/content/polytomous-modeling-cognitive-errors-computer-adaptive-testing00459nas a2200097 4500008004100000245009100041210007200132260001200204100001500216856013000231 2001 eng d00aPour une évaluation sur mesure des étudiants : défis et enjeux du testing adaptatif0 aPour une évaluation sur mesure des étudiants défis et enjeux du  aADMÉÉ1 aRaîche, G uhttp://www.iacat.org/content/pour-une-%C3%A9valuation-sur-mesure-des-%C3%A9tudiants-d%C3%A9fis-et-enjeux-du-testing-adaptatif00625nas a2200097 4500008004100000245023400041210007200275100002400347700001500371856014100386 2001 eng d00aPour une évaluation sur mesure pour chaque étudiant : défis et enjeux du testing adaptatif par ordinateur en éducation [Tailored testing for each student : Principles and stakes of computerized adaptive testing in education]0 aPour une évaluation sur mesure pour chaque étudiant défis et enj1 aRaîche, Blais, J G1 aBoiteau, N uhttp://www.iacat.org/content/pour-une-%C3%A9valuation-sur-mesure-pour-chaque-%C3%A9tudiant-d%C3%A9fis-et-enjeux-du-testing-adaptatif-par01348nas a2200181 4500008004100000245007300041210006900114260005600183300001200239520069300251653002100944653003000965653002200995653002001017100001601037700001701053856009601070 2001 eng d00aPractical issues in setting standards on computerized adaptive tests0 aPractical issues in setting standards on computerized adaptive t aMahwah, N.J. USAbLawrence Erlbaum Associates, Inc. a355-3693 a(From the chapter) Examples of setting standards on computerized adaptive tests (CATs) are hard to find. Some examples of CATs involving performance standards include the registered nurse exam and the Novell systems engineer exam. Although CATs do not require separate standard setting-methods, there are special issues to be addressed by test specialist who set performance standards on CATs. Setting standards on a CAT will typical require modifications on the procedures used with more traditional, fixed-form, paper-and -pencil examinations. The purpose of this chapter is to illustrate why CATs pose special challenges to the standard setter. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aPerformance Tests10aTesting Methods1 aSireci, S G1 aClauser, B E uhttp://www.iacat.org/content/practical-issues-setting-standards-computerized-adaptive-tests00488nas a2200121 4500008004100000245009800041210006900139300001200208490000700220100000900227700001200236856011800248 2001 eng d00aPrecision of Warm’s weighted likelihood estimation of ability for a polytomous model in CAT0 aPrecision of Warm s weighted likelihood estimation of ability fo a317-3310 v251 aWang1 aWang, T uhttp://www.iacat.org/content/precision-warm%E2%80%99s-weighted-likelihood-estimation-ability-polytomous-model-cat00466nas a2200097 4500008004100000245010500041210006900146260001000215100001500225856012800240 2001 eng d00aPrincipes et enjeux du testing adaptatif : de la loi des petits nombres à la loi des grands nombres0 aPrincipes et enjeux du testing adaptatif de la loi des petits no aAcfas1 aRaîche, G uhttp://www.iacat.org/content/principes-et-enjeux-du-testing-adaptatif-de-la-loi-des-petits-nombres-%C3%A0-la-loi-des-grands00513nam a2200097 4500008004100000245009700041210006900138260006500207100002300272856012000295 2001 eng d00aA rearrangement procedure for administering adaptive tests when review options are permitted0 arearrangement procedure for administering adaptive tests when re aUnpublished doctoral dissertation, Michigan State University1 aPapanastasiou, E C uhttp://www.iacat.org/content/rearrangement-procedure-administering-adaptive-tests-when-review-options-are-permitted00560nas a2200133 4500008004100000245009400041210006900135260004600204100001300250700001500263700001500278700001800293856011500311 2001 eng d00aRefining a system for computerized adaptive testing pool creation (Research Report 01-18)0 aRefining a system for computerized adaptive testing pool creatio aPrinceton NJ: Educational Testing Service1 aWay, W D1 aSwanson, L1 aSteffen, M1 aStocking, M L uhttp://www.iacat.org/content/refining-system-computerized-adaptive-testing-pool-creation-research-report-01-1800451nas a2200121 4500008004100000245007000041210006900111260001500180100001300195700001200208700001600220856009300236 2001 eng d00aRefining a system for computerized adaptive testing pool creation0 aRefining a system for computerized adaptive testing pool creatio aSeattle WA1 aWay, W D1 aSwanson1 aStocking, M uhttp://www.iacat.org/content/refining-system-computerized-adaptive-testing-pool-creation01360nas a2200205 4500008004100000245016700041210007000208300001000278490000700288520051600295653003000811653003100841653004800872100001800920700001900938700002600957700002600983700001401009856013101023 2001 eng d00aRequerimientos, aplicaciones e investigación en tests adaptativos informatizados [Requirements, applications, and investigation in computerized adaptive testing]0 aRequerimientos aplicaciones e investigación en tests adaptativos a11-280 v193 aSummarizes the main requirements and applications of computerized adaptive testing (CAT) with emphasis on the differences between CAT and conventional computerized tests. Psychometric properties of estimations based on CAT, item selection strategies, and implementation software are described. Results of CAT studies in Spanish-speaking samples are described. Implications for developing a CAT measuring the English vocabulary of Spanish-speaking students are discussed. (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aEnglish as Second Language10aPsychometrics computerized adaptive testing1 aOlea Díaz, J1 aPonsoda Gil, V1 aRevuelta Menéndez, J1 aHontangas Beltrán, P1 aAbad, F J uhttp://www.iacat.org/content/requerimientos-aplicaciones-e-investigaci%C3%B3n-en-tests-adaptativos-informatizados-requirements00531nas a2200121 4500008004100000245009200041210006900133260004600202100001300248700001700261700001600278856011500294 2001 eng d00aScoring alternatives for incomplete computerized adaptive tests (Research Report 01-20)0 aScoring alternatives for incomplete computerized adaptive tests  aPrinceton NJ: Educational Testing Service1 aWay, W D1 aGawlick, L A1 aEignor, D R uhttp://www.iacat.org/content/scoring-alternatives-incomplete-computerized-adaptive-tests-research-report-01-2000463nas a2200097 4500008004100000245008200041210006900123260003300192100003000225856011000255 2001 eng d00aSTAR Early Literacy Computer-Adaptive Diagnostic Assessment: Technical Manual0 aSTAR Early Literacy ComputerAdaptive Diagnostic Assessment Techn aWisconsin Rapids, WI: Author1 aRenaissance-Learning-Inc. uhttp://www.iacat.org/content/star-early-literacy-computer-adaptive-diagnostic-assessment-technical-manual00317nas a2200097 4500008004100000245004500041210004100086260001500127100001600142856006100158 2001 eng d00aA system for on-the-fly adaptive testing0 asystem for onthefly adaptive testing aSeattle WA1 aWagner, M E uhttp://www.iacat.org/content/system-fly-adaptive-testing00525nas a2200109 4500008004100000245014700041210006900188300001300257490000900270100001600279856012000295 2001 eng d00aTest anxiety and test performance: Comparing paper-based and computer-adaptive versions of the Graduate Record Examinations (GRE) General test0 aTest anxiety and test performance Comparing paperbased and compu a249-273.0 v24 1 aPowers, D E uhttp://www.iacat.org/content/test-anxiety-and-test-performance-comparing-paper-based-and-computer-adaptive-versions00445nas a2200097 4500008004100000245008800041210006900129260002100198100001300219856011500232 2001 eng d00aTesting a computerized adaptive personality inventory using simulated response data0 aTesting a computerized adaptive personality inventory using simu aSan Francisco CA1 aSimms, L uhttp://www.iacat.org/content/testing-computerized-adaptive-personality-inventory-using-simulated-response-data00722nas a2200145 4500008004100000245020100041210006900242260005700311100001700368700001700385700001400402700002000416700001600436856012400452 2001 eng d00aTesting via the Internet: A literature review and analysis of issues for Department of Defense Internet testing of the Armed Services Vocational Aptitude Battery (ASVAB) in high schools (FR-01-12)0 aTesting via the Internet A literature review and analysis of iss aAlexandria VA: Human Resources Research Organization1 aMcBride, J R1 aPaddock, A F1 aWise, L L1 aStrickland, W J1 aWaters, B K uhttp://www.iacat.org/content/testing-internet-literature-review-and-analysis-issues-department-defense-internet-testing01591nas a2200205 4500008004100000245016500041210006900206300001200275490000700287520076900294653002101063653002601084653003001110653002501140653005101165100001301216700001701229700002101246856011801267 2001 eng d00aToepassing van een computergestuurde adaptieve testprocedure op persoonlijkheidsdata [Application of a computerised adaptive test procedure on personality data]0 aToepassing van een computergestuurde adaptieve testprocedure op  a119-1330 v563 aStudied the applicability of a computerized adaptive testing procedure to an existing personality questionnaire within the framework of item response theory. The procedure was applied to the scores of 1,143 male and female university students (mean age 21.8 yrs) in the Netherlands on the Neuroticism scale of the Amsterdam Biographical Questionnaire (G. J. Wilde, 1963). The graded response model (F. Samejima, 1969) was used. The quality of the adaptive test scores was measured based on their correlation with test scores for the entire item bank and on their correlation with scores on other scales from the personality test. The results indicate that computerized adaptive testing can be applied to personality scales. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Applications10aComputer Assisted Testing10aPersonality Measures10aTest Reliability computerized adaptive testing1 aHol, A M1 aVorst, H C M1 aMellenbergh, G J uhttp://www.iacat.org/content/toepassing-van-een-computergestuurde-adaptieve-testprocedure-op-persoonlijkheidsdata00567nas a2200121 4500008004100000245012200041210006900163260004700232100001200279700001700291700001100308856012600319 2001 eng d00aUser's guide for SCORIGHT (version 1): A computer program for scoring tests built of testlets (Research Report 01-06)0 aUsers guide for SCORIGHT version 1 A computer program for scorin aPrinceton NJ: Educational Testing Service.1 aWang, X1 aBradlow, E T1 aWainer uhttp://www.iacat.org/content/users-guide-scoright-version-1-computer-program-scoring-tests-built-testlets-research-report00567nas a2200121 4500008004100000245012200041210006900163260004700232100001200279700001700291700001100308856012600319 2001 eng d00aUsers guide for SCORIGHT (version 2) : A computer program for scoring tests built of testlets (Research Report 01-06)0 aUsers guide for SCORIGHT version 2 A computer program for scorin aPrinceton NJ: Educational Testing Service.1 aWang, X1 aBradlow, E T1 aWainer uhttp://www.iacat.org/content/users-guide-scoright-version-2-computer-program-scoring-tests-built-testlets-research-report00480nas a2200109 4500008004100000245008600041210006900127260001500196100002300211700002700234856010900261 2001 eng d00aUsing response times to detect aberrant behavior in computerized adaptive testing0 aUsing response times to detect aberrant behavior in computerized aSeattle WA1 avan der Linden, WJ1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/using-response-times-detect-aberrant-behavior-computerized-adaptive-testing00376nas a2200121 4500008004100000245004600041210004500087300001000132490001000142100001400152700001600166856007200182 2001 eng d00aValidity issues in computer-based testing0 aValidity issues in computerbased testing a16-250 v20(3)1 aHuff, K L1 aSireci, S G uhttp://www.iacat.org/content/validity-issues-computer-based-testing00645nas a2200109 4500008004100000245012800041210006900169260014400238100001600382700001300398856012400411 2000 eng d00aAdaptive mastery testing using a multidimensional IRT model and Bayesian sequential decision theory (Research Report 00-06)0 aAdaptive mastery testing using a multidimensional IRT model and  aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aVos, H J uhttp://www.iacat.org/content/adaptive-mastery-testing-using-multidimensional-irt-model-and-bayesian-sequential-decision02442nas a2200169 4500008004100000245012400041210007300165300001000238490000700248520174900255653003402004100002002038700001802058700002202076700002202098856015202120 2000 eng d00aAlgoritmo mixto mínima entropía-máxima información para la selección de ítems en un test adaptativo informatizado0 aAlgoritmo mixto mínima entropíamáxima información para la selecc a12-140 v123 aEl objetivo del estudio que presentamos es comparar la eficacia como estrat egia de selección de ítems de tres algo ritmos dife rentes: a) basado en máxima info rmación; b) basado en mínima entropía; y c) mixto mínima entropía en los ítems iniciales y máxima info rmación en el resto; bajo la hipótesis de que el algo ritmo mixto, puede dotar al TAI de mayor eficacia. Las simulaciones de procesos TAI se re a l i z a ron sobre un banco de 28 ítems de respuesta graduada calibrado según el modelo de Samejima, tomando como respuesta al TAI la respuesta ori ginal de los sujetos que fueron utilizados para la c a l i b ración. Los resultados iniciales mu e s t ran cómo el cri t e rio mixto es más eficaz que cualquiera de los otros dos tomados indep e n d i e n t e m e n t e. Dicha eficacia se maximiza cuando el algo ritmo de mínima entropía se re s t ri n ge a la selección de los pri m e ros ítems del TAI, ya que con las respuestas a estos pri m e ros ítems la estimación de q comienza a ser re l evante y el algo ritmo de máxima informaciónse optimiza.Item selection algo rithms in computeri zed adap t ive testing. The aim of this paper is to compare the efficacy of three different item selection algo rithms in computeri zed adap t ive testing (CAT). These algorithms are based as follows: the first one is based on Item Info rm ation, the second one on Entropy, and the last algo rithm is a mixture of the two previous ones. The CAT process was simulated using an emotional adjustment item bank. This item bank contains 28 graded items in six categories , calibrated using Samejima (1969) Graded Response Model. The initial results show that the mixed criterium algorithm performs better than the other ones.10acomputerized adaptive testing1 aDorronsoro, J R1 aSanta-Cruz, C1 aRubio Franco, V J1 aAguado García, D uhttp://www.iacat.org/content/algoritmo-mixto-m%C3%ADnima-entrop%C3%ADa-m%C3%A1xima-informaci%C3%B3n-para-la-selecci%C3%B3n-de-%C3%ADtems-en-un-test00448nas a2200109 4500008004100000245007300041210006900114260002700183100001800210700001300228856009700241 2000 eng d00aApplying specific information item selection to a passage-based test0 aApplying specific information item selection to a passagebased t aNew Orleans, LA, April1 aThompson, T D1 aDavey, T uhttp://www.iacat.org/content/applying-specific-information-item-selection-passage-based-test00470nas a2200133 4500008004100000245006900041210006900110260001600179100001200195700001100207700001300218700001100231856009400242 2000 eng d00aAssembling parallel item pools for computerized adaptive testing0 aAssembling parallel item pools for computerized adaptive testing aNew Orleans1 aWang, T1 aFan, Q1 aBan, J C1 aZhu, D uhttp://www.iacat.org/content/assembling-parallel-item-pools-computerized-adaptive-testing01260nas a2200145 4500008004100000245006500041210006500106300001000171490000700181520076500188653003400953100002300987700001601010856008801026 2000 eng d00aCapitalization on item calibration error in adaptive testing0 aCapitalization on item calibration error in adaptive testing a35-530 v133 a(from the journal abstract) In adaptive testing, item selection is sequentially optimized during the test. Because the optimization takes place over a pool of items calibrated with estimation error, capitalization on chance is likely to occur. How serious the consequences of this phenomenon are depends not only on the distribution of the estimation errors in the pool or the conditional ratio of the test length to the pool size given ability, but may also depend on the structure of the item selection criterion used. A simulation study demonstrated a dramatic impact of capitalization on estimation errors on ability estimation. Four different strategies to minimize the likelihood of capitalization on error in computerized adaptive testing are discussed.10acomputerized adaptive testing1 avan der Linden, WJ1 aGlas, C A W uhttp://www.iacat.org/content/capitalization-item-calibration-error-adaptive-testing01587nas a2200241 4500008004100000245005800041210005800099300001200157490000600169520081000175653001400985653001400999653004801013653005701061653001101118653001801129653003101147653003701178100001301215700001701228700001601245856008401261 2000 eng d00aCAT administration of language placement examinations0 aCAT administration of language placement examinations a292-3020 v13 aThis article describes the development of a computerized adaptive test for Cegep de Jonquiere, a community college located in Quebec, Canada. Computerized language proficiency testing allows the simultaneous presentation of sound stimuli as the question is being presented to the test-taker. With a properly calibrated bank of items, the language proficiency test can be offered in an adaptive framework. By adapting the test to the test-taker's level of ability, an assessment can be made with significantly fewer items. We also describe our initial attempt to detect instances in which "cheating low" is occurring. In the "cheating low" situation, test-takers deliberately answer questions incorrectly, questions that they are fully capable of answering correctly had they been taking the test honestly.10a*Language10a*Software10aAptitude Tests/*statistics & numerical data10aEducational Measurement/*statistics & numerical data10aHumans10aPsychometrics10aReproducibility of Results10aResearch Support, Non-U.S. Gov't1 aStahl, J1 aBergstrom, B1 aGershon, RC uhttp://www.iacat.org/content/cat-administration-language-placement-examinations00597nas a2200109 4500008004100000245010000041210006900141260012600210100001100336700001600347856012400363 2000 eng d00aCaveats, pitfalls, and unexpected consequences of implementing large-scale computerized testing0 aCaveats pitfalls and unexpected consequences of implementing lar aWainer, H. (Ed). Computerized adaptive testing: A primer (2nd ed.). pp. 271-299. Mahwah, NJ: Lawrence Erlbaum Associates.1 aWainer1 aEignor, D R uhttp://www.iacat.org/content/caveats-pitfalls-and-unexpected-consequences-implementing-large-scale-computerized-testing00467nas a2200097 4500008004100000245007700041210006900118260006600187100001300253856010300266 2000 eng d00aCBTS: Computer-based testing simulation and analysis [computer software]0 aCBTS Computerbased testing simulation and analysis computer soft aAmherst, MA: University of Massachusetts, School of Education1 aRobin, F uhttp://www.iacat.org/content/cbts-computer-based-testing-simulation-and-analysis-computer-software00405nas a2200097 4500008004100000245008000041210006900121260000700190100001500197856009500212 2000 eng d00aChange in distribution of latent ability with item position in CAT sequence0 aChange in distribution of latent ability with item position in C aLA1 aKrass, I A uhttp://www.iacat.org/content/change-distribution-latent-ability-item-position-cat-sequence00450nas a2200145 4500008004100000245005800041210005400099300000900153490000700162100001700169700001500186700001200201700001400213856007700227 2000 eng d00aThe choice of item difficulty in self adapted testing0 achoice of item difficulty in self adapted testing a3-120 v161 aHontangas, P1 aPonsoda, V1 aOlea, J1 aWise, S L uhttp://www.iacat.org/content/choice-item-difficulty-self-adapted-testing00562nas a2200133 4500008004100000245012400041210006900165260001900234100001300253700001200266700001400278700001500292856012100307 2000 eng d00aClassification accuracy and test security for a computerized adaptive mastery test calibrated with different IRT models0 aClassification accuracy and test security for a computerized ada aNew Orleans LA1 aRobin, F1 aXing, D1 aScrams, D1 aPotenza, M uhttp://www.iacat.org/content/classification-accuracy-and-test-security-computerized-adaptive-mastery-test-calibrated02654nas a2200133 4500008004100000245007300041210006900114300000900183490000700192520217300199653003402372100001702406856009702423 2000 eng d00aA comparison of computerized adaptive testing and multistage testing0 acomparison of computerized adaptive testing and multistage testi a58290 v603 aThere is considerable evidence to show that computerized-adaptive testing (CAT) and multi-stage testing (MST) are viable frameworks for testing. With many testing organizations looking to move towards CAT or MST, it is important to know what framework is superior in different situations and at what cost in terms of measurement. What was needed is a comparison of the different testing procedures under various realistic testing conditions. This dissertation addressed the important problem of the increase or decrease in accuracy of ability estimation in using MST rather than CAT. The purpose of this study was to compare the accuracy of ability estimates produced by MST and CAT while keeping some variables fixed and varying others. A simulation study was conducted to investigate the effects of several factors on the accuracy of ability estimation using different CAT and MST designs. The factors that were manipulated are the number of stages, the number of subtests per stage, and the number of items per subtest. Kept constant were test length, distribution of subtest information, method of determining cut-points on subtests, amount of overlap between subtests, and method of scoring total test. The primary question of interest was, given a fixed test length, how many stages and many subtests per stage should there be to maximize measurement precision? Furthermore, how many items should there be in each subtest? Should there be more in the routing test or should there be more in the higher stage tests? Results showed that, in general, increasing the number of stages from two to three decreased the amount of errors in ability estimation. Increasing the number of subtests from three to five increased the accuracy of ability estimates as well as the efficiency of the MST designs relative to the P&P and CAT designs at most ability levels (-.75 to 2.25). Finally, at most ability levels (-.75 to 2.25), varying the number of items per stage had little effect on either the resulting accuracy of ability estimates or the relative efficiency of the MST designs to the P&P and CAT designs. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aPatsula, L N uhttp://www.iacat.org/content/comparison-computerized-adaptive-testing-and-multistage-testing00519nas a2200133 4500008004100000245009400041210006900135300001200204490000700216100001400223700001900237700001900256856011000275 2000 eng d00aA comparison of item selection rules at the early stages of computerized adaptive testing0 acomparison of item selection rules at the early stages of comput a241-2550 v241 aChen, S Y1 aAnkenmann, R D1 aChang, Hua-Hua uhttp://www.iacat.org/content/comparison-item-selection-rules-early-stages-computerized-adaptive-testing-001389nas a2200193 4500008004100000245009400041210006900135300001200204490000700216520067900223653002100902653003000923653002500953653005700978100001401035700001901049700001901068856010801087 2000 eng d00aA comparison of item selection rules at the early stages of computerized adaptive testing0 acomparison of item selection rules at the early stages of comput a241-2550 v243 aThe effects of 5 item selection rules--Fisher information (FI), Fisher interval information (FII), Fisher information with a posterior distribution (FIP), Kullback-Leibler information (KL), and Kullback-Leibler information with a posterior distribution (KLP)--were compared with respect to the efficiency and precision of trait (θ) estimation at the early stages of computerized adaptive testing (CAT). FII, FIP, KL, and KLP performed marginally better than FI at the early stages of CAT for θ=-3 and -2. For tests longer than 10 items, there appeared to be no precision advantage for any of the selection rules. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aItem Analysis (Test)10aStatistical Estimation computerized adaptive testing1 aChen, S-Y1 aAnkenmann, R D1 aChang, Hua-Hua uhttp://www.iacat.org/content/comparison-item-selection-rules-early-stages-computerized-adaptive-testing00470nas a2200109 4500008004100000245004100041210004000082260013400122100001500256700001900271856007000290 2000 eng d00aComputer-adaptive sequential testing0 aComputeradaptive sequential testing aW. J. van der Linden (Ed.), Computerized Adaptive Testing: Theory and Practice (pp. 289-209). Dordrecht, The Netherlands: Kluwer.1 aLuecht, RM1 aNungester, R J uhttp://www.iacat.org/content/computer-adaptive-sequential-testing00544nas a2200157 4500008004100000245006500041210006300106260002700169490000700196653003400203100001700237700001200254700001200266700001700278856009100295 2000 eng d00aComputer-adaptive testing: A methodology whose time has come0 aComputeradaptive testing A methodology whose time has come aChicago, IL. USAbMESA0 v6910acomputerized adaptive testing1 aLinacre, J M1 aKang, U1 aJean, E1 aLinacre, J M uhttp://www.iacat.org/content/computer-adaptive-testing-methodology-whose-time-has-come00490nas a2200097 4500008004100000245008700041210006900128260006600197100001700263856011200280 2000 eng d00aComputer-adaptive testing: A methodology whose time has come. MESA Memorandum No 90 aComputeradaptive testing A methodology whose time has come MESA  aChicago : MESA psychometric laboratory, Unversity of Chicago.1 aLinacre, J M uhttp://www.iacat.org/content/computer-adaptive-testing-methodology-whose-time-has-come-mesa-memorandum-no-901563nas a2200229 4500008004100000245006400041210006300105300001100168490000600179520083800185653002701023653001501050653001501065653004201080653001101122653002601133653002601159653003101185100001501216700001601231856008601247 2000 eng d00aComputerization and adaptive administration of the NEO PI-R0 aComputerization and adaptive administration of the NEO PIR a347-640 v73 aThis study asks, how well does an item response theory (IRT) based computerized adaptive NEO PI-R work? To explore this question, real-data simulations (N = 1,059) were used to evaluate a maximum information item selection computerized adaptive test (CAT) algorithm. Findings indicated satisfactory recovery of full-scale facet scores with the administration of around four items per facet scale. Thus, the NEO PI-R could be reduced in half with little loss in precision by CAT administration. However, results also indicated that the CAT algorithm was not necessary. We found that for many scales, administering the "best" four items per facet scale would have produced similar results. In the conclusion, we discuss the future of computerized personality assessment and describe the role IRT methods might play in such assessments.10a*Personality Inventory10aAlgorithms10aCalifornia10aDiagnosis, Computer-Assisted/*methods10aHumans10aModels, Psychological10aPsychometrics/methods10aReproducibility of Results1 aReise, S P1 aHenson, J M uhttp://www.iacat.org/content/computerization-and-adaptive-administration-neo-pi-r00484nas a2200133 4500008004100000245007600041210006900117300001100186490000700197100001500204700001600219700001700235856009800252 2000 eng d00aComputerized adaptive administration of the self-evaluation examination0 aComputerized adaptive administration of the selfevaluation exami a226-310 v681 aLaVelle, T1 aZaglaniczny1 aSpitzer, L E uhttp://www.iacat.org/content/computerized-adaptive-administration-self-evaluation-examination00586nas a2200133 4500008004100000245009000041210006900131260007900200100001600279700001600295700001800311700001400329856010900343 2000 eng d00aComputerized adaptive rating scales (CARS): Development and evaluation of the concept0 aComputerized adaptive rating scales CARS Development and evaluat a(Institute Rep No. 350). Tampa FL: Personnel Decisions Research Institute.1 aBorman, W C1 aHanson, M A1 aKubisiak, U C1 aBuck, D E uhttp://www.iacat.org/content/computerized-adaptive-rating-scales-cars-development-and-evaluation-concept00587nam a2200181 4500008004100000245005800041210005500099260005100154100001100205700001400216700001600230700001600246700001400262700001500276700001700291700001500308856008200323 2000 eng d00aComputerized adaptive testing: A primer (2nd edition)0 aComputerized adaptive testing A primer 2nd edition aHillsdale, N. J. : Lawrence Erlbaum Associates1 aWainer1 aDorans, N1 aEignor, D R1 aFlaugher, R1 aGreen, BF1 aMislevy, R1 aSteinberg, L1 aThissen, D uhttp://www.iacat.org/content/computerized-adaptive-testing-primer-2nd-edition01598nas a2200157 4500008004100000245008200041210006900123300001100192490000700203520101400210653003401224653004001258100001601298700002401314856010201338 2000 eng d00aComputerized adaptive testing for classifying examinees into three categories0 aComputerized adaptive testing for classifying examinees into thr a713-340 v603 aThe objective of this study was to explore the possibilities for using computerized adaptive testing in situations in which examinees are to be classified into one of three categories.Testing algorithms with two different statistical computation procedures are described and evaluated. The first computation procedure is based on statistical testing and the other on statistical estimation. Item selection methods based on maximum information (MI) considering content and exposure control are considered. The measurement quality of the proposed testing algorithms is reported. The results of the study are that a reduction of at least 22% in the mean number of items can be expected in a computerized adaptive test (CAT) compared to an existing paper-and-pencil placement test. Furthermore, statistical testing is a promising alternative to statistical estimation. Finally, it is concluded that imposing constraints on the MI selection strategy does not negatively affect the quality of the testing algorithms10acomputerized adaptive testing10aComputerized classification testing1 aEggen, Theo1 aStraetmans, G J J M uhttp://www.iacat.org/content/computerized-adaptive-testing-classifying-examinees-three-categories00441nam a2200109 4500008004100000245005500041210005400096260005900150100002300209700001600232856008300248 2000 eng d00aComputerized adaptive testing: Theory and practice0 aComputerized adaptive testing Theory and practice aDordrecht, The NetherlandsbKluwer Academic Publishers1 avan der Linden, WJ1 aGlas, C A W uhttp://www.iacat.org/content/computerized-adaptive-testing-theory-and-practice00462nas a2200097 4500008004100000245009400041210006900135260001900204100001700223856012400240 2000 eng d00aComputerized testing – the adolescent years: Juvenile delinquent or positive role model0 aComputerized testing the adolescent years Juvenile delinquent or aNew Orleans LA1 aReckase, M D uhttp://www.iacat.org/content/computerized-testing-%E2%80%93-adolescent-years-juvenile-delinquent-or-positive-role-model00473nas a2200097 4500008004100000245005100041210005100092260013400143100002300277856007500300 2000 eng d00aConstrained adaptive testing with shadow tests0 aConstrained adaptive testing with shadow tests aW. J. van der Linden and C. A. W. Glas (eds.), Computerized adaptive testing: Theory and practice (pp.27-52). Norwell MA: Kluwer.1 avan der Linden, WJ uhttp://www.iacat.org/content/constrained-adaptive-testing-shadow-tests00542nam a2200097 4500008004100000245011800041210006900159260008400228100001500312856011700327 2000 eng d00aThe construction and evaluation of a dynamic computerised adaptive test for the measurement of learning potential0 aconstruction and evaluation of a dynamic computerised adaptive t aUnpublished D. Litt et Phil dissertation. University of South Africa, Pretoria.1 aDe Beer, M uhttp://www.iacat.org/content/construction-and-evaluation-dynamic-computerised-adaptive-test-measurement-learning00473nas a2200121 4500008004100000245007400041210006900115260002000184100001500204700001900219700001300238856010000251 2000 eng d00aContent balancing in stratified computerized adaptive testing designs0 aContent balancing in stratified computerized adaptive testing de aNew Orleans, LA1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/content-balancing-stratified-computerized-adaptive-testing-designs00548nas a2200109 4500008004100000245006700041210006600108260013200174100002300306700001600329856009300345 2000 eng d00aCross-validating item parameter estimation in adaptive testing0 aCrossvalidating item parameter estimation in adaptive testing aA. Boorsma, M. A. J. van Duijn, and T. A. B. Snijders (Eds.) (pp. 205-219), Essays on item response theory. New York: Springer.1 avan der Linden, WJ1 aGlas, C A W uhttp://www.iacat.org/content/cross-validating-item-parameter-estimation-adaptive-testing00479nas a2200121 4500008004100000245005900041210005900100260005900159300001400218100001800232700002300250856008400273 2000 eng d00aDesigning item pools for computerized adaptive testing0 aDesigning item pools for computerized adaptive testing aDendrecht, The NetherlandsbKluwer Academic Publishers a149–1621 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/designing-item-pools-computerized-adaptive-testing00604nas a2200109 4500008004100000245009300041210006900134260012700203100002700330700001600357856012100373 2000 eng d00aDetecting person misfit in adaptive testing using statistical process control techniques0 aDetecting person misfit in adaptive testing using statistical pr aW. J. van der Linden, and C. A. W. Glas (Editors). Computerized Adaptive Testing: Theory and Practice. Norwell MA: Kluwer.1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/detecting-person-misfit-adaptive-testing-using-statistical-process-control-techniques-000575nas a2200133 4500008004100000245009300041210006900134260004900203300001200252653001500264100002700279700001600306856011900322 2000 eng d00aDetecting person misfit in adaptive testing using statistical process control techniques0 aDetecting person misfit in adaptive testing using statistical pr aDordrecht, The NetherlandsbKluwer Academic. a201-21910aperson Fit1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/detecting-person-misfit-adaptive-testing-using-statistical-process-control-techniques00518nas a2200109 4500008004100000245012100041210006900162260001900231100001700250700001600267856012500283 2000 eng d00aDetecting test-takers who have memorized items in computerized-adaptive testing and muti-stage testing: A comparison0 aDetecting testtakers who have memorized items in computerizedada aNew Orleans LA1 aPatsula, L N1 aMcLeod, L D uhttp://www.iacat.org/content/detecting-test-takers-who-have-memorized-items-computerized-adaptive-testing-and-muti-stage00485nas a2200121 4500008004100000245009100041210006900132300001200201490000700213100002000220700001600240856010700256 2000 eng d00aDetection of known items in adaptive testing with a statistical quality control method0 aDetection of known items in adaptive testing with a statistical  a373-3890 v251 aVeerkamp, W J J1 aGlas, C E W uhttp://www.iacat.org/content/detection-known-items-adaptive-testing-statistical-quality-control-method00643nas a2200109 4500008004100000245011000041210006900151260014400220100002700364700001600391856012600407 2000 eng d00aDetection of person misfit in computerized adaptive testing with polytomous items (Research Report 00-01)0 aDetection of person misfit in computerized adaptive testing with aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/detection-person-misfit-computerized-adaptive-testing-polytomous-items-research-report-00-0100581nas a2200097 4500008004100000245016800041210006900209260006600278100001300344856012600357 2000 eng d00aDevelopment and evaluation of test assembly procedures for computerized adaptive testing (Laboratory of Psychometric and Evaluative Methods Research Report No 391)0 aDevelopment and evaluation of test assembly procedures for compu aAmherst MA: University of Massachusetts, School of Education.1 aRobin, F uhttp://www.iacat.org/content/development-and-evaluation-test-assembly-procedures-computerized-adaptive-testing-laboratory02844nas a2200193 4500008004100000245013800041210006900179300000900248490000700257520208000264653003002344653002002374653005202394653002202446653001802468653002402486100001602510856012402526 2000 eng d00aThe development of a computerized version of Vandenberg's mental rotation test and the effect of visuo-spatial working memory loading0 adevelopment of a computerized version of Vandenbergs mental rota a39380 v603 aThis dissertation focused on the generation and evaluation of web-based versions of Vandenberg's Mental Rotation Test. Memory and spatial visualization theory were explored in relation to the addition of a visuo-spatial working memory component. Analysis of the data determined that there was a significant difference between scores on the MRT Computer and MRT Memory test. The addition of a visuo-spatial working memory component did significantly affect results at the .05 alpha level. Reliability and discrimination estimates were higher on the MRT Memory version. The computerization of the paper and pencil version on the MRT did not significantly effect scores but did effect the time required to complete the test. The population utilized in the quasi-experiment consisted of 107 university students from eight institutions in engineering graphics related courses. The subjects completed two researcher developed, Web-based versions of Vandenberg's Mental Rotation Test and the original paper and pencil version of the Mental Rotation Test. One version of the test included a visuo-spatial working memory loading. Significant contributions of this study included developing and evaluating computerized versions of Vandenberg's Mental Rotation Test. Previous versions of Vandenberg's Mental Rotation Test did not take advantage of the ability of the computer to incorporate an interaction factor, such as a visuo-spatial working memory loading, into the test. The addition of an interaction factor results in a more discriminate test which will lend itself well to computerized adaptive testing practices. Educators in engineering graphics related disciplines should strongly consider the use of spatial visualization tests to aid in establishing the effects of modern computer systems on fundamental design/drafting skills. Regular testing of spatial visualization skills will result assist in the creation of a more relevant curriculum. Computerized tests which are valid and reliable will assist in making this task feasible. (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aMental Rotation10aShort Term Memory computerized adaptive testing10aTest Construction10aTest Validity10aVisuospatial Memory1 aStrong, S D uhttp://www.iacat.org/content/development-computerized-version-vandenbergs-mental-rotation-test-and-effect-visuo-spatial03274nas a2200217 4500008004100000245020800041210007000249300001000319490000700329520241300336653002102749653002402770653003202794653001302826100001902839700001802858700001702876700001802893700001702911856012802928 2000 eng d00aDiagnostische programme in der Demenzfrüherkennung: Der Adaptive Figurenfolgen-Lerntest (ADAFI) [Diagnostic programs in the early detection of dementia: The Adaptive Figure Series Learning Test (ADAFI)]0 aDiagnostische programme in der Demenzfrüherkennung Der Adaptive  a16-290 v133 aZusammenfassung: Untersucht wurde die Eignung des computergestützten Adaptiven Figurenfolgen-Lerntests (ADAFI), zwischen gesunden älteren Menschen und älteren Menschen mit erhöhtem Demenzrisiko zu differenzieren. Der im ADAFI vorgelegte Aufgabentyp der fluiden Intelligenzdimension (logisches Auffüllen von Figurenfolgen) hat sich in mehreren Studien zur Erfassung des intellektuellen Leistungspotentials (kognitive Plastizität) älterer Menschen als günstig für die genannte Differenzierung erwiesen. Aufgrund seiner Konzeption als Diagnostisches Programm fängt der ADAFI allerdings einige Kritikpunkte an Vorgehensweisen in diesen bisherigen Arbeiten auf. Es konnte gezeigt werden, a) daß mit dem ADAFI deutliche Lokationsunterschiede zwischen den beiden Gruppen darstellbar sind, b) daß mit diesem Verfahren eine gute Vorhersage des mentalen Gesundheitsstatus der Probanden auf Einzelfallebene gelingt (Sensitivität: 80 %, Spezifität: 90 %), und c) daß die Vorhersageleistung statusdiagnostischer Tests zur Informationsverarbeitungsgeschwindigkeit und zum Arbeitsgedächtnis geringer ist. Die Ergebnisse weisen darauf hin, daß die plastizitätsorientierte Leistungserfassung mit dem ADAFI vielversprechend für die Frühdiagnostik dementieller Prozesse sein könnte.The aim of this study was to examine the ability of the computerized Adaptive Figure Series Learning Test (ADAFI) to differentiate among old subjects at risk for dementia and old healthy controls. Several studies on the subject of measuring the intellectual potential (cognitive plasticity) of old subjects have shown the usefulness of the fluid intelligence type of task used in the ADAFI (completion of figure series) for this differentiation. Because the ADAFI has been developed as a Diagnostic Program it is able to counter some critical issues in those studies. It was shown a) that distinct differences between both groups are revealed by the ADAFI, b) that the prediction of the cognitive health status of individual subjects is quite good (sensitivity: 80 %, specifity: 90 %), and c) that the prediction of the cognitive health status with tests of processing speed and working memory is worse than with the ADAFI. The results indicate that the ADAFI might be a promising plasticity-oriented tool for the measurement of cognitive decline in the elderly, and thus might be useful for the early detection of dementia.10aAdaptive Testing10aAt Risk Populations10aComputer Assisted Diagnosis10aDementia1 aSchreiber, M D1 aSchneider, RJ1 aSchweizer, A1 aBeckmann, J F1 aBaltissen, R uhttp://www.iacat.org/content/diagnostische-programme-der-demenzfr%C3%BCherkennung-der-adaptive-figurenfolgen-lerntest-adafi00407nas a2200121 4500008004100000245005400041210005300095300001200148490000700160100001700167700001900184856008200203 2000 eng d00aDoes adaptive testing violate local independence?0 aDoes adaptive testing violate local independence a149-1560 v651 aMislevy, R J1 aChang, Hua-Hua uhttp://www.iacat.org/content/does-adaptive-testing-violate-local-independence00548nas a2200109 4500008004100000245013300041210006900174260004400243100001400287700001500301856012200316 2000 eng d00aEffects of item-selection criteria on classification testing with the sequential probability ratio test (Research Report 2000-8)0 aEffects of itemselection criteria on classification testing with aIowa City, IA: American College Testing1 aLin, C -J1 aSpray, J A uhttp://www.iacat.org/content/effects-item-selection-criteria-classification-testing-sequential-probability-ratio-test00475nas a2200133 4500008004100000245007200041210006900113260001900182100001300201700001200214700001000226700001600236856008900252 2000 eng d00aEffects of nonequivalence of item pools on ability estimates in CAT0 aEffects of nonequivalence of item pools on ability estimates in  aNew Orleans LA1 aBan, J C1 aWang, T1 aYi, Q1 aHarris, D J uhttp://www.iacat.org/content/effects-nonequivalence-item-pools-ability-estimates-cat00716nas a2200193 4500008004100000245008400041210006900125300001400194490000700208653003000215653001100245653002500256653001600281653005500297653002200352653002300374100001800397856010700415 2000 eng d00aEmergence of item response modeling in instrument development and data analysis0 aEmergence of item response modeling in instrument development an aII60-II650 v3810aComputer Assisted Testing10aHealth10aItem Response Theory10aMeasurement10aStatistical Validity computerized adaptive testing10aTest Construction10aTreatment Outcomes1 aHambleton, RK uhttp://www.iacat.org/content/emergence-item-response-modeling-instrument-development-and-data-analysis00587nas a2200133 4500008004100000245014200041210006900183260002700252100001600279700001600295700001400311700001300325856011500338 2000 eng d00aEstimating item parameters from classical indices for item pool development with a computerized classification test (ACT Research 2000-4)0 aEstimating item parameters from classical indices for item pool  aIowa City IA, ACT, Inc1 aChang, C -Y1 aKalohn, J C1 aLin, C -J1 aSpray, J uhttp://www.iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized-000571nas a2200133 4500008004100000245012200041210006900163260003100232100001600263700001600279700001400295700001500309856011300324 2000 eng d00aEstimating Item Parameters from Classical Indices for Item Pool Development with a Computerized Classification Test. 0 aEstimating Item Parameters from Classical Indices for Item Pool  aIowa City, IowabACT, Inc.1 aHuang, C -Y1 aKalohn, J C1 aLin, C -J1 aSpray, J A uhttp://www.iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized00589nas a2200133 4500008004100000245014500041210006900186260002600255100001600281700001600297700001400313700001300327856011500340 2000 eng d00aEstimating item parameters from classical indices for item pool development with a computerized classification test (Research Report 2000-4)0 aEstimating item parameters from classical indices for item pool  aIowa City IA: ACT Inc1 aHuang, C -Y1 aKalohn, J C1 aLin, C -J1 aSpray, J uhttp://www.iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized-101432nas a2200193 4500008004100000245006300041210006300104300001200167490000700179520079500186653001800981653002100999653003001020653001801050653005701068100001501125700001201140856008601152 2000 eng d00aEstimation of trait level in computerized adaptive testing0 aEstimation of trait level in computerized adaptive testing a257-2650 v243 aNotes that in computerized adaptive testing (CAT), a examinee's trait level (θ) must be estimated with reasonable accuracy based on a small number of item responses. A successful implementation of CAT depends on (1) the accuracy of statistical methods used for estimating θ and (2) the efficiency of the item-selection criterion. Methods of estimating θ suitable for CAT are reviewed, and the differences between Fisher and Kullback-Leibler information criteria for selecting items are discussed. The accuracy of different CAT algorithms was examined in an empirical study. The results show that correcting θ estimates for bias was necessary at earlier stages of CAT, but most CAT algorithms performed equally well for tests of 10 or more items. (PsycINFO Database Record (c) 2005 APA )10a(Statistical)10aAdaptive Testing10aComputer Assisted Testing10aItem Analysis10aStatistical Estimation computerized adaptive testing1 aCheng, P E1 aLiou, M uhttp://www.iacat.org/content/estimation-trait-level-computerized-adaptive-testing00389nas a2200109 4500008004100000245006200041210006200103300000800165490000700173100001500180856008400195 2000 eng d00aETS finds flaws in the way online GRE rates some students0 aETS finds flaws in the way online GRE rates some students aa470 v471 aCarlson, S uhttp://www.iacat.org/content/ets-finds-flaws-way-online-gre-rates-some-students00609nas a2200145 4500008004100000245013100041210006900172260002000241100001400261700001600275700001400291700001400305700001900319856012500338 2000 eng d00aAn examination of exposure control and content balancing restrictions on item selection in CATs using the partial credit model0 aexamination of exposure control and content balancing restrictio aNew Orleans, LA1 aDavis, LL1 aPastor, D A1 aDodd, B G1 aChiang, C1 aFitzpatrick, S uhttp://www.iacat.org/content/examination-exposure-control-and-content-balancing-restrictions-item-selection-cats-using-002315nas a2200205 4500008004100000245012100041210006900162300000800231490000700239520159200246653002101838653003001859653002201889653001801911653001601929653000901945653001801954100001401972856012301986 2000 eng d00aAn examination of the reliability and validity of performance ratings made using computerized adaptive rating scales0 aexamination of the reliability and validity of performance ratin a5700 v613 aThis study compared the psychometric properties of performance ratings made using recently-developed computerized adaptive rating scales (CARS) to the psyc hometric properties of ratings made using more traditional paper-and-pencil rati ng formats, i.e., behaviorally-anchored and graphic rating scales. Specifically, the reliability, validity and accuracy of the performance ratings from each for mat were examined. One hundred twelve participants viewed six 5-minute videotape s of office situations and rated the performance of a target person in each vide otape on three contextual performance dimensions-Personal Support, Organizationa l Support, and Conscientious Initiative-using CARS and either behaviorally-ancho red or graphic rating scales. Performance rating properties were measured using Shrout and Fleiss's intraclass correlation (2, 1), Borman's differential accurac y measure, and Cronbach's accuracy components as indexes of rating reliability, validity, and accuracy, respectively. Results found that performance ratings mad e using the CARS were significantly more reliable and valid than performance rat ings made using either of the other formats. Additionally, CARS yielded more acc urate performance ratings than the paper-and-pencil formats. The nature of the C ARS system (i.e., its adaptive nature and scaling methodology) and its paired co mparison judgment task are offered as possible reasons for the differences found in the psychometric properties of the performance ratings made using the variou s rating formats. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aPerformance Tests10aRating Scales10aReliability10aTest10aTest Validity1 aBuck, D E uhttp://www.iacat.org/content/examination-reliability-and-validity-performance-ratings-made-using-computerized-adaptive02407nas a2200193 4500008004100000245010700041210006900148300000900217490000700226520169400233653003201927653002501959653002001984653001802004653002602022653001402048100002602062856012502088 2000 eng d00aAn exploratory analysis of item parameters and characteristics that influence item level response time0 aexploratory analysis of item parameters and characteristics that a18120 v613 aThis research examines the relationship between item level response time and (1) item discrimination, (2) item difficulty, (3) word count, (4) item type, and (5) whether a figure is included in an item. Data are from the Graduate Management Admission Test, which is currently offered only as a computerized adaptive test. Analyses revealed significant differences in response time between the five item types: problem solving, data sufficiency, sentence correction, critical reasoning, and reading comprehension. For this reason, the planned pairwise and complex analyses were run within each item type. Pairwise curvilinear regression analyses explored the relationship between response time and item discrimination, item difficulty, and word count. Item difficulty significantly contributed to the prediction of response time for each item type; two of the relationships were significantly quadratic. Item discrimination significantly contributed to the prediction of response time for only two of the item types; one revealed a quadratic relationship and the other a cubic relationship. Word count had significant linear relationship with response time for all the item types except reading comprehension, for which there was no significant relationship. Multiple regression analyses using word count, item difficulty, and item discrimination predicted between 35.4% and 71.4% of the variability in item response time across item types. The results suggest that response time research should consider the type of item that is being administered and continue to explore curvilinear relationships between response time and its predictor variables. (PsycINFO Database Record (c) 2005 APA )10aItem Analysis (Statistical)10aItem Response Theory10aProblem Solving10aReaction Time10aReading Comprehension10aReasoning1 aSmith, Russell Winsor uhttp://www.iacat.org/content/exploratory-analysis-item-parameters-and-characteristics-influence-item-level-response-time00363nas a2200097 4500008004100000245005200041210005000093260002700143100001800170856007700188 2000 eng d00aA framework for comparing adaptive test designs0 aframework for comparing adaptive test designs aUnpublished manuscript1 aStocking, M L uhttp://www.iacat.org/content/framework-comparing-adaptive-test-designs-000448nas a2200109 4500008004100000245007600041210006900117260002800186100001700214700001400231856009300245 2000 eng d00aFrom simulation to application: Examinees react to computerized testing0 aFrom simulation to application Examinees react to computerized t aNew Orleans, April 20001 aPommerich, M1 aBurden, T uhttp://www.iacat.org/content/simulation-application-examinees-react-computerized-testing00512nas a2200109 4500008004100000245005500041210005000096260014700146100001500293700001500308856007900323 2000 eng d00aThe GRE computer adaptive test: Operational issues0 aGRE computer adaptive test Operational issues aW. J. van der Linden and C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice (pp. 75-99). Dordrecht, Netherlands: Kluwer.1 aMills, C N1 aSteffen, M uhttp://www.iacat.org/content/gre-computer-adaptive-test-operational-issues01222nas a2200145 4500008004100000245009700041210006900138300001200207490000600219520069600225100001500921700001400936700001400950856011200964 2000 eng d00aThe impact of receiving the same items on consecutive computer adaptive test administrations0 aimpact of receiving the same items on consecutive computer adapt a131-1510 v13 aAddresses item exposure in a Computerized Adaptive Test (CAT) when the item selection algorithm is permitted to present examinees with questions that they have already been asked in a previous test administration. The data were from a national certification exam in medical technology. The responses of 178 repeat examinees were compared. The results indicate that the combined use of an adaptive algorithm to select items and latent trait theory to estimate person ability provides substantial protection from score contamination. The implications for constraints that prohibit examinees from seeing an item twice are discussed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aO'Neill, T1 aLunz, M E1 aThiede, K uhttp://www.iacat.org/content/impact-receiving-same-items-consecutive-computer-adaptive-test-administrations00507nas a2200097 4500008004100000245014000041210006900181260002000250100001500270856012400285 2000 eng d00aImplementing the computer-adaptive sequential testing (CAST) framework to mass produce high quality computer-adaptive and mastery tests0 aImplementing the computeradaptive sequential testing CAST framew aNew Orleans, LA1 aLuecht, RM uhttp://www.iacat.org/content/implementing-computer-adaptive-sequential-testing-cast-framework-mass-produce-high-quality01172nas a2200205 4500008004100000245005600041210005300097300001200150490000700162520055300169653002200722653002500744653002500769653002200794653001500816100002300831700001800854700001500872856007900887 2000 eng d00aAn integer programming approach to item bank design0 ainteger programming approach to item bank design a139-1500 v243 aAn integer programming approach to item bank design is presented that can be used to calculate an optimal blueprint for an item bank, in order to support an existing testing program. The results are optimal in that they minimize the effort involved in producing the items as revealed by current item writing patterns. Also presented is an adaptation of the models, which can be used as a set of monitoring tools in item bank management. The approach is demonstrated empirically for an item bank that was designed for the Law School Admission Test. 10aAptitude Measures10aItem Analysis (Test)10aItem Response Theory10aTest Construction10aTest Items1 avan der Linden, WJ1 aVeldkamp, B P1 aReese, L M uhttp://www.iacat.org/content/integer-programming-approach-item-bank-design00617nas a2200121 4500008004100000245016600041210006900207260004700276100001800323700001300341700001500354856012600369 2000 eng d00aAn investigation of approaches to computerizing the GRE subject tests (GRE Board Professional Report No 93-08P; Educational Testing Service Research Report 00-4)0 ainvestigation of approaches to computerizing the GRE subject tes aPrinceton NJ: Educational Testing Service.1 aStocking, M L1 aSmith, R1 aSwanson, L uhttp://www.iacat.org/content/investigation-approaches-computerizing-gre-subject-tests-gre-board-professional-report-no-9300452nas a2200097 4500008004100000245004100041210004100082260014500123100001600268856007000284 2000 eng d00aItem calibration and parameter drift0 aItem calibration and parameter drift aW. J. van der linden and C. A. W. Glas (Eds.). Computerized adaptive testing: Theory and practice (pp.183-199). Norwell MA: Kluwer Academic.1 aGlas, C A W uhttp://www.iacat.org/content/item-calibration-and-parameter-drift00529nas a2200133 4500008004100000245010200041210006900143300001000212490000700222100001600229700001600245700001700261856011700278 2000 eng d00aItem exposure control in computer-adaptive testing: The use of freezing to augment stratification0 aItem exposure control in computeradaptive testing The use of fre a28-520 v401 aParshall, C1 aHarmes, J C1 aKromrey, J D uhttp://www.iacat.org/content/item-exposure-control-computer-adaptive-testing-use-freezing-augment-stratification00314nas a2200097 4500008004100000245001500041210001500056260008500071100001600156856004400172 2000 eng d00aItem pools0 aItem pools aWainer, H. (2000). Computerized adaptive testing: a primer. Mahwah, NJ: Erlbaum.1 aFlaugher, R uhttp://www.iacat.org/content/item-pools01774nas a2200289 4500008004100000245007700041210006900118300001400187490000700201520080000208653002501008653003101033653003701064653003801101653001901139653001001158653002701168653004601195653002001241653002801261653003201289653001801321100001401339700001701353700001501370856009901385 2000 eng d00aItem response theory and health outcomes measurement in the 21st century0 aItem response theory and health outcomes measurement in the 21st aII28-II420 v383 aItem response theory (IRT) has a number of potential advantages over classical test theory in assessing self-reported health outcomes. IRT models yield invariant item and latent trait estimates (within a linear transformation), standard errors conditional on trait level, and trait estimates anchored to item content. IRT also facilitates evaluation of differential item functioning, inclusion of items with different response formats in the same scale, and assessment of person fit and is ideally suited for implementing computer adaptive testing. Finally, IRT methods can be helpful in developing better health outcome measures and in assessing change over time. These issues are reviewed, along with a discussion of some of the methodological and practical challenges in applying IRT methods.10a*Models, Statistical10aActivities of Daily Living10aData Interpretation, Statistical10aHealth Services Research/*methods10aHealth Surveys10aHuman10aMathematical Computing10aOutcome Assessment (Health Care)/*methods10aResearch Design10aSupport, Non-U.S. Gov't10aSupport, U.S. Gov't, P.H.S.10aUnited States1 aHays, R D1 aMorales, L S1 aReise, S P uhttp://www.iacat.org/content/item-response-theory-and-health-outcomes-measurement-21st-century01343nas a2200157 4500008004100000245006300041210006300104300001000167490000700177520083100184100002101015700001801036700002001054700002201074856008901096 2000 eng d00aItem selection algorithms in computerized adaptive testing0 aItem selection algorithms in computerized adaptive testing a12-140 v123 aStudied the efficacy of 3 different item selection algorithms in computerized adaptive testing. Ss were 395 university students (aged 20-25 yrs) in Spain. Ss were asked to submit answers via computer to 28 items of a personality questionnaire using item selection algorithms based on maximum item information, entropy, or mixed item-entropy algorithms. The results were evaluated according to ability of Ss to use item selection algorithms and number of questions. Initial results indicate that mixed criteria algorithms were more efficient than information or entropy algorithms for up to 15 questionnaire items, but that differences in efficiency decreased with increasing item number. Implications for developing computer adaptive testing methods are discussed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aGarcia, David, A1 aSanta Cruz, C1 aDorronsoro, J R1 aRubio Franco, V J uhttp://www.iacat.org/content/item-selection-algorithms-computerized-adaptive-testing00485nas a2200121 4500008004100000245006200041210006200103260005900165300001100224100002300235700001700258856008800275 2000 eng d00aItem selection and ability estimation in adaptive testing0 aItem selection and ability estimation in adaptive testing aDordrecht, The NetherlandsbKluwer Academic Publishers a1–251 avan der Linden, WJ1 aPashley, P J uhttp://www.iacat.org/content/item-selection-and-ability-estimation-adaptive-testing00659nam a2200097 4500008004100000245026000041210006900301260005400370100001300424856012400437 2000 eng d00aLa distribution dchantillonnage en testing adaptatif en fonction de deux rgles darrt : selon lerreur type et selon le nombre ditems administrs [Sampling distribution of the proficiency estimate in computerized adaptive testing according to two stopping...0 aLa distribution dchantillonnage en testing adaptatif en fonction aDoctoral thesis, Montreal: University of Montreal1 aRache, G uhttp://www.iacat.org/content/la-distribution-dchantillonnage-en-testing-adaptatif-en-fonction-de-deux-rgles-darrt-selon02718nas a2200169 4500008004100000245011500041210006900156300000900225490000700234520208500241653001302326653002802339653002602367653001602393100001602409856012302425 2000 eng d00aLagrangian relaxation for constrained curve-fitting with binary variables: Applications in educational testing0 aLagrangian relaxation for constrained curvefitting with binary v a10630 v613 aThis dissertation offers a mathematical programming approach to curve fitting with binary variables. Various Lagrangian Relaxation (LR) techniques are applied to constrained curve fitting. Applications in educational testing with respect to test assembly are utilized. In particular, techniques are applied to both static exams (i.e. conventional paper-and-pencil (P&P)) and adaptive exams (i.e. a hybrid computerized adaptive test (CAT) called a multiple-forms structure (MFS)). This dissertation focuses on the development of mathematical models to represent these test assembly problems as constrained curve-fitting problems with binary variables and solution techniques for the test development. Mathematical programming techniques are used to generate parallel test forms with item characteristics based on item response theory. A binary variable is used to represent whether or not an item is present on a form. The problem of creating a test form is modeled as a network flow problem with additional constraints. In order to meet the target information and the test characteristic curves, a Lagrangian relaxation heuristic is applied to the problem. The Lagrangian approach works by multiplying the constraint by a "Lagrange multiplier" and adding it to the objective. By systematically varying the multiplier, the test form curves approach the targets. This dissertation explores modifications to Lagrangian Relaxation as it is applied to the classical paper-and-pencil exams. For the P&P exams, LR techniques are also utilized to include additional practical constraints to the network problem, which limit the item selection. An MFS is a type of a computerized adaptive test. It is a hybrid of a standard CAT and a P&P exam. The concept of an MFS will be introduced in this dissertation, as well as, the application of LR as it is applied to constructing parallel MFSs. The approach is applied to the Law School Admission Test for the assembly of the conventional P&P test as well as an experimental computerized test using MFSs. (PsycINFO Database Record (c) 2005 APA )10aAnalysis10aEducational Measurement10aMathematical Modeling10aStatistical1 aKoppel, N B uhttp://www.iacat.org/content/lagrangian-relaxation-constrained-curve-fitting-binary-variables-applications-educational00421nam a2200097 4500008004100000245007600041210006900117260002000186100001500206856010200221 2000 eng d00aLearning Potential Computerised Adaptive Test (LPCAT): Technical Manual0 aLearning Potential Computerised Adaptive Test LPCAT Technical Ma aPretoria: UNISA1 aDe Beer, M uhttp://www.iacat.org/content/learning-potential-computerised-adaptive-test-lpcat-technical-manual00414nam a2200097 4500008004100000245007300041210006900114260002000183100001500203856009800218 2000 eng d00aLearning Potential Computerised Adaptive Test (LPCAT): User's Manual0 aLearning Potential Computerised Adaptive Test LPCAT Users Manual aPretoria: UNISA1 aDe Beer, M uhttp://www.iacat.org/content/learning-potential-computerised-adaptive-test-lpcat-users-manual00555nas a2200133 4500008004100000245011800041210006900159300001000228490000700238100001700245700002100262700001500283856012300298 2000 eng d00aLimiting answer review and change on computerized adaptive vocabulary tests: Psychometric and attitudinal results0 aLimiting answer review and change on computerized adaptive vocab a21-380 v371 aVispoel, W P1 aHendrickson, A B1 aBleiler, T uhttp://www.iacat.org/content/limiting-answer-review-and-change-computerized-adaptive-vocabulary-tests-psychometric-and00692nas a2200169 4500008004100000020001400041245015800055210006900213300001200282490000600294653003400300100001700334700001500351700001200366700001400378856013000392 2000 eng d a1575-910500aLos tests adaptativos informatizados en la frontera del siglo XXI: Una revisión [Computerized adaptive tests at the turn of the 21st century: A review]0 aLos tests adaptativos informatizados en la frontera del siglo XX a183-2160 v210acomputerized adaptive testing1 aHontangas, P1 aPonsoda, V1 aOlea, J1 aAbad, F J uhttp://www.iacat.org/content/los-tests-adaptativos-informatizados-en-la-frontera-del-siglo-xxi-una-revisi%C3%B3n-computerized00503nas a2200109 4500008004100000245005600041210005600097260013700153100001800290700001300308856007200321 2000 eng d00aMethods of controlling the exposure of items in CAT0 aMethods of controlling the exposure of items in CAT aW. J. van der Linden and C. A. W. Glas (eds.), Computerized adaptive testing: Theory and practice (pp. 163-182). Norwell MA: Kluwer.1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/methods-controlling-exposure-items-cat00518nas a2200097 4500008004100000245006200041210006000103260015900163100001300322856008500335 2000 eng d00aA minimax solution for sequential classification problems0 aminimax solution for sequential classification problems aH. A. L. Kiers, J.-P.Rasson, P. J. F. Groenen, and M. Schader (Eds.), Data analysis, classification, and related methods (pp. 121-126). Berlin: Springer. 1 aVos, H J uhttp://www.iacat.org/content/minimax-solution-sequential-classification-problems00498nas a2200133 4500008004100000245006100041210006000102260005900162300001200221100001600233700001100249700001700260856008700277 2000 eng d00aMML and EAP estimation in testlet-based adaptive testing0 aMML and EAP estimation in testletbased adaptive testing aDordrecht, The NetherlandsbKluwer Academic Publishers a271-2871 aGlas, C A W1 aWainer1 aBradlow, E T uhttp://www.iacat.org/content/mml-and-eap-estimation-testlet-based-adaptive-testing00618nas a2200097 4500008004100000245012400041210006900165260014400234100001800378856012400396 2000 eng d00aModifications of the branch-and-bound algorithm for application in constrained adaptive testing (Research Report 00-05)0 aModifications of the branchandbound algorithm for application in aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aVeldkamp, B P uhttp://www.iacat.org/content/modifications-branch-and-bound-algorithm-application-constrained-adaptive-testing-research00614nas a2200109 4500008004100000245009500041210006900136260014400205100001800349700002300367856011400390 2000 eng d00aMultidimensional adaptive testing with constraints on test content (Research Report 00-11)0 aMultidimensional adaptive testing with constraints on test conte aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-constraints-test-content-research-report-00-1100414nas a2200109 4500008004100000245006100041210006100102260002700163100001000190700001900200856008500219 2000 eng d00aMultiple stratification CAT designs with content control0 aMultiple stratification CAT designs with content control aUnpublished manuscript1 aYi, Q1 aChang, Hua-Hua uhttp://www.iacat.org/content/multiple-stratification-cat-designs-content-control00467nas a2200109 4500008004100000245009400041210006900135260001600204100001100220700001200231856011400243 2000 eng d00aA new item selection procedure for mixed item type in computerized classification testing0 anew item selection procedure for mixed item type in computerized aNew Orleans1 aLau, C1 aWang, T uhttp://www.iacat.org/content/new-item-selection-procedure-mixed-item-type-computerized-classification-testing00486nas a2200121 4500008004100000245008700041210006900128300001200197490000700209100002700216700001600243856010500259 2000 eng d00aThe null distribution of person-fit statistics for conventional and adaptive tests0 anull distribution of personfit statistics for conventional and a a327-3450 v231 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/null-distribution-person-fit-statistics-conventional-and-adaptive-tests00610nas a2200097 4500008004100000245011100041210006900152260014400221100002300365856012400388 2000 eng d00aOptimal stratification of item pools in a-stratified computerized adaptive testing (Research Report 00-07)0 aOptimal stratification of item pools in astratified computerized aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ uhttp://www.iacat.org/content/optimal-stratification-item-pools-stratified-computerized-adaptive-testing-research-report00867nas a2200145 4500008004100000245006600041210006600107300001200173490000700185520036100192653002100553653004400574100001500618856008800633 2000 eng d00aOverview of the computerized adaptive testing special section0 aOverview of the computerized adaptive testing special section a115-1200 v213 aThis paper provides an overview of the five papers included in the Psicologica special section on computerized adaptive testing. A short introduction to this topic is presented as well. The main results, the links between the five papers and the general research topic to which they are more related are also shown. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputers computerized adaptive testing1 aPonsoda, V uhttp://www.iacat.org/content/overview-computerized-adaptive-testing-special-section00526nas a2200121 4500008004100000245010400041210006900145260002100214100001900235700001300254700001100267856012600278 2000 eng d00aPerformance of item exposure control methods in computerized adaptive testing: Further explorations0 aPerformance of item exposure control methods in computerized ada aNew Orleans , LA1 aChang, Hua-Hua1 aChang, S1 aAnsley uhttp://www.iacat.org/content/performance-item-exposure-control-methods-computerized-adaptive-testing-further-explorations00488nas a2200121 4500008003900000245009100039210006900130300001200199490000700211100001400218700001900232856011500251 2000 d00aPractical issues in developing and maintaining a computerized adaptive testing program0 aPractical issues in developing and maintaining a computerized ad a135-1550 v211 aWise, S L1 aKingsbury, G G uhttp://www.iacat.org/content/practical-issues-developing-and-maintaining-computerized-adaptive-testing-program00472nas a2200097 4500008004100000245005200041210005200093260013500145100001600280856007800296 2000 eng d00aPrinciples of multidimensional adaptive testing0 aPrinciples of multidimensional adaptive testing aW. J. van der Linden and C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice (pp. 53-73). Norwell MA: Kluwer.1 aSegall, D O uhttp://www.iacat.org/content/principles-multidimensional-adaptive-testing00380nas a2200121 4500008003900000245004800039210004800087300000900135490000600144100001500150700001900165856007400184 2000 d00aPsychological reactions to adaptive testing0 aPsychological reactions to adaptive testing a7-150 v81 aTonidandel1 aQuiñones, M A uhttp://www.iacat.org/content/psychological-reactions-adaptive-testing00549nas a2200145 4500008004500000245009400045210006900139300001200208490000700220100001200227700001600239700001700255700001400272856011700286 2000 Spandsh 00aPsychometric and psychological effects of review on computerized fixed and adaptive tests0 aPsychometric and psychological effects of review on computerized a157-1730 v211 aOlea, J1 aRevuelta, J1 aXimenez, M C1 aAbad, F J uhttp://www.iacat.org/content/psychometric-and-psychological-effects-review-computerized-fixed-and-adaptive-tests02579nas a2200145 4500008004100000245008100041210006900122300001000191490000700201520207600208100001502284700001602299700002002315856009802335 2000 eng d00aA real data simulation of computerized adaptive administration of the MMPI-A0 areal data simulation of computerized adaptive administration of  a83-960 v163 aA real data simulation of computerized adaptive administration of the Minnesota Multiphasic Inventory-Adolescent (MMPI-A) was conducted using item responses from three groups of participants. The first group included 196 adolescents (age range 14-18) tested at a midwestern residential treatment facility for adolescents. The second group was the normative sample used in the standardization of the MMPI-A (Butcher, Williams, Graham, Archer, Tellegen, Ben-Porath, & Kaemmer, 1992. Minnesota Multiphasic Inventory-Adolescent (MMPI-A): manual for administration, scoring, and interpretation. Minneapolis: University of Minnesota Press.). The third group was the clinical sample: used in the validation of the MMPI-A (Williams & Butcher, 1989. An MMPI study of adolescents: I. Empirical validation of the study's scales. Personality assessment, 1, 251-259.). The MMPI-A data for each group of participants were run through a modified version of the MMPI-2 adaptive testing computer program (Roper, Ben-Porath & Butcher, 1995. Comparability and validity of computerized adaptive testing with the MMPI-2. Journal of Personality Assessment, 65, 358-371.). To determine the optimal amount of item savings, each group's MMPI-A item responses were used to simulate three different orderings of the items: (1) from least to most frequently endorsed in the keyed direction; (2) from least to most frequently endorsed in the keyed direction with the first 120 items rearranged into their booklet order; and (3) all items in booklet order. The mean number of items administered for each group was computed for both classification and full- scale elevations for T-score cut-off values of 60 and 65. Substantial item administration savings were achieved for all three groups, and the mean number of items saved ranged from 50 items (10.7% of the administered items) to 123 items (26.4% of the administered items), depending upon the T-score cut-off, classification method (i.e. classification only or full-scale elevation), and group. (C) 2000 Elsevier Science Ltd. All rights reserved.1 aFobey, J D1 aHandel, R W1 aBen-Porath, Y S uhttp://www.iacat.org/content/real-data-simulation-computerized-adaptive-administration-mmpi-000492nas a2200133 4500008004100000245008100041210006900122300001000191490000700201100001600208700001600224700002000240856009800260 2000 eng d00aA real data simulation of computerized adaptive administration of the MMPI-A0 areal data simulation of computerized adaptive administration of  a83-960 v161 aForbey, J D1 aHandel, R W1 aBen-Porath, Y S uhttp://www.iacat.org/content/real-data-simulation-computerized-adaptive-administration-mmpi-100388nas a2200109 4500008004100000245005900041210005700100300001200157490000700169100001100176856009100187 2000 eng d00aRescuing computerized testing by breaking Zipf’s law0 aRescuing computerized testing by breaking Zipf s law a203-2240 v251 aWainer uhttp://www.iacat.org/content/rescuing-computerized-testing-breaking-zipf%E2%80%99s-law00638nas a2200133 4500008004100000245020600041210006900247300001000316490000700326100001400333700001700347700001600364856012400380 2000 eng d00aResponse to Hays et al and McHorney and Cohen: Practical implications of item response theory and computerized adaptive testing: A brief summary of ongoing studies of widely used headache impact scales0 aResponse to Hays et al and McHorney and Cohen Practical implicat a73-820 v381 aWare, Jr.1 aBjorner, J B1 aKosinski, M uhttp://www.iacat.org/content/response-hays-et-al-and-mchorney-and-cohen-practical-implications-item-response-theory-and00598nas a2200121 4500008004100000245002700041210002500068300001000093490000600103520029500109100002100404856005100425 2000 eng d00aA review of CAT review0 areview of CAT review a47-490 v33 aStudied the effects of answer review on results of a computerized adaptive test, the laboratory professional examination of the American Society of Clinical Pathologists. Results from 29,293 candidates show that candidates who changed answers were more likely to improve their scores. (SLD)1 aSekula-Wacura, R uhttp://www.iacat.org/content/review-cat-review00594nas a2200133 4500008004100000245013300041210006900174260003400243100000900277700001600286700001600302700001700318856012500335 2000 eng d00aA selection procedure for polytomous items in computerized adaptive testing (Measurement and Research Department Reports 2000-5)0 aselection procedure for polytomous items in computerized adaptiv aArnhem, The Netherlands: Cito1 aRijn1 aEggen, Theo1 aHemker, B T1 aSanders, P F uhttp://www.iacat.org/content/selection-procedure-polytomous-items-computerized-adaptive-testing-measurement-and-research00496nas a2200121 4500008004100000245008600041210006900127260002100196100001500217700001900232700001300251856011000264 2000 eng d00aSolving complex constraints in a-stratified computerized adaptive testing designs0 aSolving complex constraints in astratified computerized adaptive aNew Orleans, USA1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/solving-complex-constraints-stratified-computerized-adaptive-testing-designs00506nas a2200097 4500008004100000245014600041210006900187260001900256100001600275856011700291 2000 eng d00aSome considerations for improving accuracy of estimation of item characteristic curves in online calibration of computerized adaptive testing0 aSome considerations for improving accuracy of estimation of item aNew Orleans LA1 aSamejima, F uhttp://www.iacat.org/content/some-considerations-improving-accuracy-estimation-item-characteristic-curves-online00399nas a2200109 4500008004100000245006100041210006100102260001600163100001300179700001100192856008600203 2000 eng d00aSpecific information item selection for adaptive testing0 aSpecific information item selection for adaptive testing aNew Orleans1 aDavey, T1 aFan, M uhttp://www.iacat.org/content/specific-information-item-selection-adaptive-testing00461nas a2200097 4500008004100000245008100041210006900122260003300191100003000224856010900254 2000 eng d00aSTAR Reading 2 Computer-Adaptive Reading Test and Database: Technical Manual0 aSTAR Reading 2 ComputerAdaptive Reading Test and Database Techni aWisconsin Rapids, WI: Author1 aRenaissance-Learning-Inc. uhttp://www.iacat.org/content/star-reading-2-computer-adaptive-reading-test-and-database-technical-manual00560nas a2200121 4500008004100000245013100041210006900172260001900241100001800260700001700278700001700295856012600312 2000 eng d00aSufficient simplicity or comprehensive complexity? A comparison of probabilitic and stratification methods of exposure control0 aSufficient simplicity or comprehensive complexity A comparison o aNew Orleans LA1 aParshall, C G1 aKromrey, J D1 aHogarty, K Y uhttp://www.iacat.org/content/sufficient-simplicity-or-comprehensive-complexity-comparison-probabilitic-and-stratification01199nas a2200133 4500008004100000245008300041210006900124300001200193490000700205520069300212653003400905100002000939856010600959 2000 eng d00aTaylor approximations to logistic IRT models and their use in adaptive testing0 aTaylor approximations to logistic IRT models and their use in ad a307-3430 v253 aTaylor approximation can be used to generate a linear approximation to a logistic ICC and a linear ability estimator. For a specific situation it will be shown to result in a special case of a Robbins-Monro item selection procedure for adaptive testing. The linear estimator can be used for the situation of zero and perfect scores when maximum likelihood estimation fails to come up with a finite estimate. It is also possible to use this estimator to generate starting values for maximum likelihood and weighted likelihood estimation. Approximations to the expectation and variance of the linear estimator for a sequence of Robbins-Monro item selections can be determined analytically. 10acomputerized adaptive testing1 aVeerkamp, W J J uhttp://www.iacat.org/content/taylor-approximations-logistic-irt-models-and-their-use-adaptive-testing00379nas a2200097 4500008004100000245006400041210006200105260001200167100001400179856008800193 2000 eng d00aTest security and item exposure control for computer-based 0 aTest security and item exposure control for computerbased aChicago1 aKalohn, J uhttp://www.iacat.org/content/test-security-and-item-exposure-control-computer-based00421nas a2200121 4500008004100000245006000041210006000101260001600161100001100177700001300188700001600201856008200217 2000 eng d00aTest security and the development of computerized tests0 aTest security and the development of computerized tests aNew Orleans1 aGuo, F1 aWay, W D1 aReshetar, R uhttp://www.iacat.org/content/test-security-and-development-computerized-tests00617nas a2200121 4500008004100000245009800041210006900139260013700208100001100345700001700356700001000373856011200383 2000 eng d00aTestlet response theory: An analog for the 3PL model useful in testlet-based adaptive testing0 aTestlet response theory An analog for the 3PL model useful in te aW. J. van der Linden and C. A. W. Glas (Eds.), Computerized Adaptive Testing: Theory and Practice (pp. 245-270). Norwell MA: Kluwer.1 aWainer1 aBradlow, E T1 aDu, Z uhttp://www.iacat.org/content/testlet-response-theory-analog-3pl-model-useful-testlet-based-adaptive-testing00459nas a2200109 4500008004100000245004600041210004400087260011500131100001300246700001600259856007400275 2000 eng d00aTestlet-based adaptive mastery testing, W0 aTestletbased adaptive mastery testing W aJ. van der Linden (Ed.), Computerized adaptive testing: Theory and practice (pp. 289-309). Norwell MA: Kluwer.1 aVos, H J1 aGlas, C A W uhttp://www.iacat.org/content/testlet-based-adaptive-mastery-testing-w00478nas a2200097 4500008004100000245009400041210006900135260004400204100001800248856011400266 2000 eng d00aTestlet-based Designs for Computer-Based Testing in a Certification and Licensure Setting0 aTestletbased Designs for ComputerBased Testing in a Certificatio aJersey City, NJ: AICPA Technical Report1 aPitoniak, M J uhttp://www.iacat.org/content/testlet-based-designs-computer-based-testing-certification-and-licensure-setting00546nas a2200133 4500008004100000245005900041210005900100260009900159100001400258700001400272700002700286700001400313856008500327 2000 eng d00aUsing Bayesian Networks in Computerized Adaptive Tests0 aUsing Bayesian Networks in Computerized Adaptive Tests aM. Ortega and J. Bravo (Eds.),Computers and Education in the 21st Century. Kluwer, pp. 217228.1 aMillan, E1 aTrella, M1 aPerez-de-la-Cruz, J -L1 aConejo, R uhttp://www.iacat.org/content/using-bayesian-networks-computerized-adaptive-tests00379nas a2200097 4500008004100000245006000041210006000101100001800161700001600179856008600195 2000 eng d00aUsing constraints to develop and deliver adaptive tests0 aUsing constraints to develop and deliver adaptive tests1 aAbdullah, S C1 aCooley, R E uhttp://www.iacat.org/content/using-constraints-develop-and-deliver-adaptive-tests00649nas a2200109 4500008004100000245011000041210006900151260014400220100002300364700002700387856012500414 2000 eng d00aUsing response times to detect aberrant behavior in computerized adaptive testing (Research Report 00-09)0 aUsing response times to detect aberrant behavior in computerized aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/using-response-times-detect-aberrant-behavior-computerized-adaptive-testing-research-report00596nas a2200109 4500008004100000245016200041210006900203260006200272100001700334700001300351856012200364 2000 eng d00aVariations in mean response times for questions on the computer-adaptive GRE general test: Implications for fair assessment (GRE Board Professional Report No0 aVariations in mean response times for questions on the computera a96-20P: Educational Testing Service Research Report 00-7)1 aBridgeman, B1 aCline, F uhttp://www.iacat.org/content/variations-mean-response-times-questions-computer-adaptive-gre-general-test-implications00559nas a2200097 4500008004100000245008100041210006900122260014400191100002300335856010300358 1999 eng d00aAdaptive testing with equated number-correct scoring (Research Report 99-02)0 aAdaptive testing with equated numbercorrect scoring Research Rep aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ uhttp://www.iacat.org/content/adaptive-testing-equated-number-correct-scoring-research-report-99-0200441nas a2200109 4500008004100000245007500041210006900116260002100185100001100206700001300217856010100230 1999 eng d00aAdjusting computer adaptive test starting points to conserve item pool0 aAdjusting computer adaptive test starting points to conserve ite aMontreal, Canada1 aZhu, D1 aM., Fan. uhttp://www.iacat.org/content/adjusting-computer-adaptive-test-starting-points-conserve-item-pool00506nas a2200145 4500008004100000245007100041210006900112260002100181100001200202700001000214700001300224700001600237700001600253856009100269 1999 eng d00aAdjusting "scores" from a CAT following successful item challenges0 aAdjusting scores from a CAT following successful item challenges aMontreal, Canada1 aWang, T1 aYi, Q1 aBan, J C1 aHarris, D J1 aHanson, B A uhttp://www.iacat.org/content/adjusting-scores-cat-following-successful-item-challenges00473nas a2200097 4500008004100000245011800041210006900159260001100228100001300239856012300252 1999 eng d00aAlternative item selection strategies for improving test security and pool usage in computerized adaptive testing0 aAlternative item selection strategies for improving test securit aCanada1 aRobin, F uhttp://www.iacat.org/content/alternative-item-selection-strategies-improving-test-security-and-pool-usage-computerized00512nas a2200121 4500008004100000245009600041210006900137300000900206490000700215653003400222100002300256856011100279 1999 eng d00aAlternative methods for the detection of item preknowledge in computerized adaptive testing0 aAlternative methods for the detection of item preknowledge in co a37650 v5910acomputerized adaptive testing1 aMcLeod, Lori Davis uhttp://www.iacat.org/content/alternative-methods-detection-item-preknowledge-computerized-adaptive-testing00417nas a2200121 4500008004100000245005800041210005700099300001400156490000700170100001900177700001200196856008700208 1999 eng d00aa-stratified multistage computerized adaptive testing0 aastratified multistage computerized adaptive testing a211–2220 v231 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/stratified-multistage-computerized-adaptive-testing-001734nas a2200145 4500008004100000245005800041210005700099300001200156490000700168520126300175653003401438100001901472700001201491856008501503 1999 eng d00aa-stratified multistage computerized adaptive testing0 aastratified multistage computerized adaptive testing a211-2220 v233 aFor computerized adaptive tests (CAT) based on the three-parameter logistic mode it was found that administering items with low discrimination parameter (a) values early in the test and administering those with high a values later was advantageous; the skewness of item exposure distributions was reduced while efficiency was maintain in trait level estimation. Thus, a new multistage adaptive testing approach is proposed that factors a into the item selection process. In this approach, the items in the item bank are stratified into a number of levels based on their a values. The early stages of a test use items with lower as and later stages use items with higher as. At each stage, items are selected according to an optimization criterion from the corresponding level. Simulation studies were performed to compare a-stratified CATs with CATs based on the Sympson-Hetter method for controlling item exposure. Results indicated that this new strategy led to tests that were well-balanced, with respect to item exposure, and efficient. The a-stratified CATs achieved a lower average exposure rate than CATs based on Bayesian or information-based item selection and the Sympson-Hetter method. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/stratified-multistage-computerized-adaptive-testing00415nas a2200121 4500008004100000245005800041210005700099300001200156490000700168100001900175700001200194856008700206 1999 eng d00aa-stratified multistage computerized adaptive testing0 aastratified multistage computerized adaptive testing a211-2220 v231 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/stratified-multistage-computerized-adaptive-testing-100489nas a2200109 4500008004100000245009800041210006900139260002100208100001500229700001900244856011600263 1999 eng d00aAutomated flawed item detection and graphical item used in on-line calibration of CAT-ASVAB. 0 aAutomated flawed item detection and graphical item used in onlin aMontreal, Canada1 aKrass, I A1 aThomasson, G L uhttp://www.iacat.org/content/automated-flawed-item-detection-and-graphical-item-used-line-calibration-cat-asvab00404nas a2200133 4500008004100000245005000041210004700091300001200138490000800150100001700158700001100175700001200186856007200198 1999 eng d00aA Bayesian random effects model for testlets 0 aBayesian random effects model for testlets a153-1680 v 641 aBradlow, E T1 aWainer1 aWang, X uhttp://www.iacat.org/content/bayesian-random-effects-model-testlets00427nas a2200109 4500008004100000245007800041210006900119300001000188490000700198100001600205856009600221 1999 eng d00aBenefits from computerized adaptive testing as seen in simulation studies0 aBenefits from computerized adaptive testing as seen in simulatio a91-980 v151 aHornke, L F uhttp://www.iacat.org/content/benefits-computerized-adaptive-testing-seen-simulation-studies00575nas a2200145 4500008004100000245011800041210006900159300001200228490000700240100001700247700001700264700001200281700001500293856012100308 1999 eng d00aCan examinees use a review option to obtain positively biased ability estimates on a computerized adaptive test? 0 aCan examinees use a review option to obtain positively biased ab a141-1570 v361 aVispoel, W P1 aRocklin, T R1 aWang, T1 aBleiler, T uhttp://www.iacat.org/content/can-examinees-use-review-option-obtain-positively-biased-ability-estimates-computerized00409nas a2200121 4500008004100000245005100041210005100092260002100143100001300164700001600177700001700193856007700210 1999 eng d00aCAT administration of language placement exams0 aCAT administration of language placement exams aMontreal, Canada1 aStahl, J1 aGershon, RC1 aBergstrom, B uhttp://www.iacat.org/content/cat-administration-language-placement-exams01276nas a2200145 4500008004100000245004000041210004000081260004600121300001000167520081600177653003400993100002401027700001401051856006501065 1999 eng d00aCAT for certification and licensure0 aCAT for certification and licensure aMahwah, N.J.bLawrence Erlbaum Associates a67-913 a(from the chapter) This chapter discusses implementing computerized adaptive testing (CAT) for high-stakes examinations that determine whether or not a particular candidate will be certified or licensed. The experience of several boards who have chosen to administer their licensure or certification examinations using the principles of CAT illustrates the process of moving into this mode of administration. Examples of the variety of options that can be utilized within a CAT administration are presented, the decisions that boards must make to implement CAT are discussed, and a timetable for completing the tasks that need to be accomplished is provided. In addition to the theoretical aspects of CAT, practical issues and problems are reviewed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).10acomputerized adaptive testing1 aBergstrom, Betty, A1 aLunz, M E uhttp://www.iacat.org/content/cat-certification-and-licensure00494nas a2200109 4500008004100000245010000041210006900141260002000210100001700230700001800247856011900265 1999 eng d00aA comparative study of ability estimates from computer-adaptive testing and multi-stage testing0 acomparative study of ability estimates from computeradaptive tes aMontreal Canada1 aPatsula, L N1 aHambleton, RK uhttp://www.iacat.org/content/comparative-study-ability-estimates-computer-adaptive-testing-and-multi-stage-testing00475nam a2200097 4500008004100000245007400041210006900115260007800184100001700262856009800279 1999 eng d00aA comparison of computerized-adaptive testing and multi-stage testing0 acomparison of computerizedadaptive testing and multistage testin aUnpublished doctoral dissertation, University of Massachusetts at Amherst1 aPatsula, L N uhttp://www.iacat.org/content/comparison-computerized-adaptive-testing-and-multi-stage-testing00490nas a2200109 4500008004100000245009900041210006900140260002100209100001900230700001200249856011900261 1999 eng d00aA comparison of conventional and adaptive testing procedures for making single-point decisions0 acomparison of conventional and adaptive testing procedures for m aMontreal, Canada1 aKingsbury, G G1 aZara, A uhttp://www.iacat.org/content/comparison-conventional-and-adaptive-testing-procedures-making-single-point-decisions00392nas a2200097 4500008004100000245006400041210006400105260002100169100001400190856009000204 1999 eng d00aComparison of stratum scored and maximum likelihood scoring0 aComparison of stratum scored and maximum likelihood scoring aMontreal, Canada1 aWise, S L uhttp://www.iacat.org/content/comparison-stratum-scored-and-maximum-likelihood-scoring00517nas a2200109 4500008004100000245012200041210006900163260002300232100001800255700001500273856011900288 1999 eng d00aA comparison of testlet-based test designs for computerized adaptive testing (LSAC Computerized Testing Report 97-01)0 acomparison of testletbased test designs for computerized adaptiv aNewtown, PA: LSAC.1 aSchnipke, D L1 aReese, L M uhttp://www.iacat.org/content/comparison-testlet-based-test-designs-computerized-adaptive-testing-lsac-computerized00525nas a2200121 4500008004100000245012600041210006900167260001600236100001100252700001200263700001000275856011800285 1999 eng d00aComparison of the a-stratified method, the Sympson-Hetter method, and the matched difficulty method in CAT administration0 aComparison of the astratified method the SympsonHetter method an aLawrence KS1 aBan, J1 aWang, T1 aYi, Q uhttp://www.iacat.org/content/comparison-stratified-method-sympson-hetter-method-and-matched-difficulty-method-cat01772nas a2200265 4500008004100000245004900041210004800090300001000138490000600148520092600154653002501080653005701105653001501162653001201177653001001189653002101199653006401220653001101284653002201295653001101317653000901328653007801337100001701415856007401432 1999 eng d00aCompetency gradient for child-parent centers0 aCompetency gradient for childparent centers a35-520 v33 aThis report describes an implementation of the Rasch model during the longitudinal evaluation of a federally-funded early childhood preschool intervention program. An item bank is described for operationally defining a psychosocial construct called community life-skills competency, an expected teenage outcome of the preschool intervention. This analysis examined the position of teenage students on this scale structure, and investigated a pattern of cognitive operations necessary for students to pass community life-skills test items. Then this scale structure was correlated with nationally standardized reading and math achievement scores, teacher ratings, and school records to assess its validity as a measure of the community-related outcome goal for this intervention. The results show a functional relationship between years of early intervention and magnitude of effect on the life-skills competency variable.10a*Models, Statistical10aActivities of Daily Living/classification/psychology10aAdolescent10aChicago10aChild10aChild, Preschool10aEarly Intervention (Education)/*statistics & numerical data10aFemale10aFollow-Up Studies10aHumans10aMale10aOutcome and Process Assessment (Health Care)/*statistics & numerical data1 aBezruczko, N uhttp://www.iacat.org/content/competency-gradient-child-parent-centers00478nas a2200133 4500008004100000245007500041210006900116300001200185490000700197100001600204700002000220700001400240856009000254 1999 eng d00aComputerized adaptive assessment with the MMPI-2 in a clinical setting0 aComputerized adaptive assessment with the MMPI2 in a clinical se a369-3800 v111 aHandel, R W1 aBen-Porath, Y S1 aWatt, M E uhttp://www.iacat.org/content/computerized-adaptive-assessment-mmpi-2-clinical-setting00359nas a2200097 4500008004100000245005200041210005200093260002700145100001500172856007400187 1999 eng d00aComputerized adaptive testing in the Bundeswehr0 aComputerized adaptive testing in the Bundeswehr aUnpublished manuscript1 aStorm, E G uhttp://www.iacat.org/content/computerized-adaptive-testing-bundeswehr00915nas a2200145 4500008004100000245006100041210006000102300001100162490000700173520043400180653003400614100001600648700001600664856008900680 1999 eng d00aComputerized Adaptive Testing: Overview and Introduction0 aComputerized Adaptive Testing Overview and Introduction a187-940 v233 aUse of computerized adaptive testing (CAT) has increased substantially since it was first formulated in the 1970s. This paper provides an overview of CAT and introduces the contributions to this Special Issue. The elements of CAT discussed here include item selection procedures, estimation of the latent trait, item exposure, measurement precision, and item bank development. Some topics for future research are also presented. 10acomputerized adaptive testing1 aMeijer, R R1 aNering, M L uhttp://www.iacat.org/content/computerized-adaptive-testing-overview-and-introduction00426nas a2200121 4500008004100000245006100041210006000102300001200162490000700174100001600181700001600197856009100213 1999 eng d00aComputerized adaptive testing: Overview and introduction0 aComputerized adaptive testing Overview and introduction a187-1940 v231 aMeijer, R R1 aNering, M L uhttp://www.iacat.org/content/computerized-adaptive-testing-overview-and-introduction-000461nas a2200109 4500008004100000245009200041210006900133260001300202100000800215700001200223856011600235 1999 eng d00aComputerized classification testing under practical constraints with a polytomous model0 aComputerized classification testing under practical constraints  aMontreal1 aLau1 aWang, T uhttp://www.iacat.org/content/computerized-classification-testing-under-practical-constraints-polytomous-model-000488nas a2200109 4500008004100000245009200041210006900133260003800202100001200240700001200252856011400264 1999 eng d00aComputerized classification testing under practical constraints with a polytomous model0 aComputerized classification testing under practical constraints  aMontreal, Quebec, Canadac04/19991 aLau, CA1 aWang, T uhttp://www.iacat.org/content/computerized-classification-testing-under-practical-constraints-polytomous-model00492nas a2200133 4500008004100000245007400041210006700115260001300182100001600195700001300211700001300224700001400237856010700251 1999 eng d00aComputerized testing – Issues and applications (Mini-course manual)0 aComputerized testing Issues and applications Minicourse manual aMontreal1 aParshall, C1 aDavey, T1 aSpray, J1 aKalohn, J uhttp://www.iacat.org/content/computerized-testing-%E2%80%93-issues-and-applications-mini-course-manual00442nas a2200121 4500008004100000245006600041210006600107260001300173100001100186700001600197700001300213856009400226 1999 eng d00aConstructing adaptive tests to parallel conventional programs0 aConstructing adaptive tests to parallel conventional programs aMontreal1 aFan, M1 aThompson, T1 aDavey, T uhttp://www.iacat.org/content/constructing-adaptive-tests-parallel-conventional-programs-000576nas a2200097 4500008004100000245010300041210006900144260012200213100001700335856012600352 1999 eng d00aCreating computerized adaptive tests of music aptitude: Problems, solutions, and future directions0 aCreating computerized adaptive tests of music aptitude Problems  aF. Drasgow and J. B. Olson-Buchanan (Eds.), Innovations in computerized assessment (pp. 151-176). Mahwah NJ: Erlbaum.1 aVispoel, W P uhttp://www.iacat.org/content/creating-computerized-adaptive-tests-music-aptitude-problems-solutions-and-future-directions00505nas a2200097 4500008004100000245008000041210006900121260009600190100001700286856010400303 1999 eng d00aCurrent and future research in multi-stage testing (Research Report No 370)0 aCurrent and future research in multistage testing Research Repor aAmherst MA: University of Massachusetts, Laboratory of Pychometric and Evaluative Research.1 aZenisky, A L uhttp://www.iacat.org/content/current-and-future-research-multi-stage-testing-research-report-no-37000427nas a2200121 4500008004100000245005900041210005700100300001200157490000700169100002700176700001600203856008600219 1999 eng d00aCUSUM-based person-fit statistics for adaptive testing0 aCUSUMbased personfit statistics for adaptive testing a199-2180 v261 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/cusum-based-person-fit-statistics-adaptive-testing-000596nas a2200109 4500008004100000245008300041210006900124260014400193100002700337700001600364856010600380 1999 eng d00aCUSUM-based person-fit statistics for adaptive testing (Research Report 99-05)0 aCUSUMbased personfit statistics for adaptive testing Research Re aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/cusum-based-person-fit-statistics-adaptive-testing-research-report-99-0500595nas a2200109 4500008004100000245008400041210006900125260014400194100001800338700002300356856010600379 1999 eng d00aDesigning item pools for computerized adaptive testing (Research Report 99-03 )0 aDesigning item pools for computerized adaptive testing Research  aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aVeldkamp, B P1 avan der Linden, WJ uhttp://www.iacat.org/content/designing-item-pools-computerized-adaptive-testing-research-report-99-0300399nas a2200121 4500008004100000245005500041210005500096300001200151490000700163100001700170700001300187856007700200 1999 eng d00aDetecting item memorization in the CAT environment0 aDetecting item memorization in the CAT environment a147-1600 v231 aMcLeod L. D.1 aLewis, C uhttp://www.iacat.org/content/detecting-item-memorization-cat-environment00427nas a2200109 4500008004100000245006800041210006800109260002100177100001600198700001800214856008500232 1999 eng d00aDetecting items that have been memorized in the CAT environment0 aDetecting items that have been memorized in the CAT environment aMontreal, Canada1 aMcLeod, L D1 aSchinpke, D L uhttp://www.iacat.org/content/detecting-items-have-been-memorized-cat-environment00521nas a2200109 4500008004100000245006300041210006300104260012100167100001900288700001600307856008800323 1999 eng d00aDeveloping computerized adaptive tests for school children0 aDeveloping computerized adaptive tests for school children aF. Drasgow and J. B. Olson-Buchanan (Eds.), Innovations in computerized assessment (pp. 93-115). Mahwah NJ: Erlbaum.1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/developing-computerized-adaptive-tests-school-children00486nas a2200097 4500008004100000245011700041210006900158260002100227100002000248856012000268 1999 eng d00aThe development and cognitive evaluation of an audio-assisted computer-adaptive test for eight-grade mathematics0 adevelopment and cognitive evaluation of an audioassisted compute aMontreal, Canada1 aWilliams, V S L uhttp://www.iacat.org/content/development-and-cognitive-evaluation-audio-assisted-computer-adaptive-test-eight-grade00563nas a2200097 4500008004100000245009700041210006900138260012200207100001500329856012100344 1999 eng d00aDevelopment and introduction of a computer adaptive Graduate Record Examination General Test0 aDevelopment and introduction of a computer adaptive Graduate Rec aF. Drasgow and J .B. Olson-Buchanan (Eds.). Innovations in computerized assessment (pp. 117-135). Mahwah NJ: Erlbaum.1 aMills, C N uhttp://www.iacat.org/content/development-and-introduction-computer-adaptive-graduate-record-examination-general-test00661nas a2200133 4500008004100000245012100041210006900162260010800231100001600339700001700355700001600372700001500388856012400403 1999 eng d00aThe development of a computerized adaptive selection system for computer programmers in a financial services company0 adevelopment of a computerized adaptive selection system for comp aF. Drasgow and J. B. Olsen (Eds.), Innvoations in computerized assessment (p. 7-33). Mahwah NJ Erlbaum.1 aZickar, M J1 aOverton, R C1 aTaylor, L R1 aHarms, H J uhttp://www.iacat.org/content/development-computerized-adaptive-selection-system-computer-programmers-financial-services00385nas a2200109 4500008004100000245006400041210006000105300001200165490000700177100001500184856007600199 1999 eng d00aThe development of an adaptive test for placement in french0 adevelopment of an adaptive test for placement in french a122-1350 v101 aLaurier, M uhttp://www.iacat.org/content/development-adaptive-test-placement-french00594nas a2200109 4500008004100000245011100041210006900152260010500221100001600326700001600342856012600358 1999 eng d00aDevelopment of the computerized adaptive testing version of the Armed Services Vocational Aptitude Battery0 aDevelopment of the computerized adaptive testing version of the  aF. Drasgow and J. Olson-Buchanan (Eds.). Innovations in computerized assessment. Mahwah NJ: Erlbaum.1 aSegall, D O1 aMoreno, K E uhttp://www.iacat.org/content/development-computerized-adaptive-testing-version-armed-services-vocational-aptitude-battery00503nas a2200121 4500008004100000245009700041210006900138300001000207100001400217700001700231700001600248856011700264 1999 eng d00aDynamic health assessments: The search for more practical and more precise outcomes measures0 aDynamic health assessments The search for more practical and mor a11-131 aWare, Jr.1 aBjorner, J B1 aKosinski, M uhttp://www.iacat.org/content/dynamic-health-assessments-search-more-practical-and-more-precise-outcomes-measures01684nas a2200145 4500008004100000245010000041210006900141300001000210490000700220520112900227653003401356100001601390700001501406856011701421 1999 eng d00aThe effect of model misspecification on classification decisions made using a computerized test0 aeffect of model misspecification on classification decisions mad a47-590 v363 aMany computerized testing algorithms require the fitting of some item response theory (IRT) model to examinees' responses to facilitate item selection, the determination of test stopping rules, and classification decisions. Some IRT models are thought to be particularly useful for small volume certification programs that wish to make the transition to computerized adaptive testing (CAT). The 1-parameter logistic model (1-PLM) is usually assumed to require a smaller sample size than the 3-parameter logistic model (3-PLM) for item parameter calibrations. This study examined the effects of model misspecification on the precision of the decisions made using the sequential probability ratio test. For this comparison, the 1-PLM was used to estimate item parameters, even though the items' characteristics were represented by a 3-PLM. Results demonstrate that the 1-PLM produced considerably more decision errors under simulation conditions similar to a real testing environment, compared to the true model and to a fixed-form standard reference set of items. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aKalohn, J C1 aSpray, J A uhttp://www.iacat.org/content/effect-model-misspecification-classification-decisions-made-using-computerized-test00569nas a2200145 4500008004100000245010600041210006900147300001200216490000700228100001500235700001200250700001900262700001600281856012600297 1999 eng d00aThe effects of test difficulty manipulation in computerized adaptive testing and self-adapted testing0 aeffects of test difficulty manipulation in computerized adaptive a167-1840 v121 aPonsoda, V1 aOlea, J1 aRodriguez, M S1 aRevuelta, J uhttp://www.iacat.org/content/effects-test-difficulty-manipulation-computerized-adaptive-testing-and-self-adapted-testin-200423nas a2200109 4500008004100000245007200041210006900113300001000182490000700192100002300199856009100222 1999 eng d00aEmpirical initialization of the trait estimator in adaptive testing0 aEmpirical initialization of the trait estimator in adaptive test a21-290 v231 avan der Linden, WJ uhttp://www.iacat.org/content/empirical-initialization-trait-estimator-adaptive-testing00446nas a2200121 4500008004100000245006400041210006100105260002100166100001500187700001900202700001300221856009000234 1999 eng d00aAn enhanced stratified computerized adaptive testing design0 aenhanced stratified computerized adaptive testing design aMontreal, Canada1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/enhanced-stratified-computerized-adaptive-testing-design02155nas a2200277 4500008004100000020002200041245009600063210006900159250001500228260000800243300001100251490000700262520122800269653001601497653003901513653003701552653001101589653003301600653002501633653002701658653003101685100001701716700001601733700001701749856011101766 1999 eng d a1040-2446 (Print)00aEvaluating the usefulness of computerized adaptive testing for medical in-course assessment0 aEvaluating the usefulness of computerized adaptive testing for m a1999/10/28 cOct a1125-80 v743 aPURPOSE: This study investigated the feasibility of converting an existing computer-administered, in-course internal medicine test to an adaptive format. METHOD: A 200-item internal medicine extended matching test was used for this research. Parameters were estimated with commercially available software with responses from 621 examinees. A specially developed simulation program was used to retrospectively estimate the efficiency of the computer-adaptive exam format. RESULTS: It was found that the average test length could be shortened by almost half with measurement precision approximately equal to that of the full 200-item paper-and-pencil test. However, computer-adaptive testing with this item bank provided little advantage for examinees at the upper end of the ability continuum. An examination of classical item statistics and IRT item statistics suggested that adding more difficult items might extend the advantage to this group of examinees. CONCLUSIONS: Medical item banks presently used for incourse assessment might be advantageously employed in adaptive testing. However, it is important to evaluate the match between the items and the measurement objective of the test before implementing this format.10a*Automation10a*Education, Medical, Undergraduate10aEducational Measurement/*methods10aHumans10aInternal Medicine/*education10aLikelihood Functions10aPsychometrics/*methods10aReproducibility of Results1 aKreiter, C D1 aFerguson, K1 aGruppen, L D uhttp://www.iacat.org/content/evaluating-usefulness-computerized-adaptive-testing-medical-course-assessment00498nas a2200109 4500008004100000245010400041210006900145260002100214100001600235700001800251856011900269 1999 eng d00aAn examination of conditioning variables in DIF analysis in a computer adaptive testing environment0 aexamination of conditioning variables in DIF analysis in a compu aMontreal, Canada1 aWalker, C M1 aAckerman, T A uhttp://www.iacat.org/content/examination-conditioning-variables-dif-analysis-computer-adaptive-testing-environment00603nas a2200157 4500008004100000245011600041210006900157300001200226490000700238100001400245700001100259700001600270700001700286700001900303856012300322 1999 eng d00aExaminee judgments of changes in item difficulty: Implications for item review in computerized adaptive testing0 aExaminee judgments of changes in item difficulty Implications fo a185-1980 v121 aWise, S L1 aFinney1 aEnders, C K1 aFreeman, S A1 aSeverance, D D uhttp://www.iacat.org/content/examinee-judgments-changes-item-difficulty-implications-item-review-computerized-adaptive00621nas a2200121 4500008004100000245011300041210006900154260011200223100001200335700001900347700001500366856011800381 1999 eng d00aExploring the relationship between item exposure rate and test overlap rate in computerized adaptive testing0 aExploring the relationship between item exposure rate and test o aPaper presented at the annual meeting of the National Council on Measurement in Education, Montreal, Canada1 aChen, S1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/exploring-relationship-between-item-exposure-rate-and-test-overlap-rate-computerized00574nas a2200121 4500008004100000245014700041210006900188260002700257100001400284700001900298700001500317856012000332 1999 eng d00aExploring the relationship between item exposure rate and test overlap rate in computerized adaptive testing (ACT Research Report series 99-5)0 aExploring the relationship between item exposure rate and test o aIowa City IA: ACT, Inc1 aChen, S-Y1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/exploring-relationship-between-item-exposure-rate-and-test-overlap-rate-computerized-000378nas a2200121 4500008004100000245003900041210003800080260002100118100002000139700001700159700001500176856006500191 1999 eng d00aFairness in computer-based testing0 aFairness in computerbased testing aMontreal, Canada1 aGallagher, Aand1 aBridgeman, B1 aCalahan, C uhttp://www.iacat.org/content/fairness-computer-based-testing00434nas a2200097 4500008004100000245008600041210006900127100001600196700001500212856010900227 1999 eng d00aFormula score and direct optimization algorithms in CAT ASVAB on-line calibration0 aFormula score and direct optimization algorithms in CAT ASVAB on1 aLevine, M V1 aKrass, I A uhttp://www.iacat.org/content/formula-score-and-direct-optimization-algorithms-cat-asvab-line-calibration00420nas a2200109 4500008004100000245006800041210006700109300001200176490000700188100001900195856009600214 1999 eng d00aGenerating items during testing: Psychometric issues and models0 aGenerating items during testing Psychometric issues and models a407-4330 v641 aEmbretson, S E uhttp://www.iacat.org/content/generating-items-during-testing-psychometric-issues-and-models00754nas a2200145 4500008004100000245005500041210005500096300001100151490000700162520028800169653003400457100001600491700001700507856008400524 1999 eng d00aGraphical models and computerized adaptive testing0 aGraphical models and computerized adaptive testing a223-370 v233 aConsiders computerized adaptive testing from the perspective of graphical modeling (GM). GM provides methods for making inferences about multifaceted skills and knowledge and for extracting data from complex performances. Provides examples from language-proficiency assessment. (SLD)10acomputerized adaptive testing1 aAlmond, R G1 aMislevy, R J uhttp://www.iacat.org/content/graphical-models-and-computerized-adaptive-testing00600nas a2200097 4500008004100000245006700041210006500108260021200173100002300385856009400408 1999 eng d00aHet ontwerpen van adaptieve examens [Designing adaptive tests]0 aHet ontwerpen van adaptieve examens Designing adaptive tests aJ. M Pieters, Tj. Plomp, and L.E. Odenthal (Eds.), Twintig jaar Toegepaste Onderwijskunde: Een kaleidoscopisch overzicht van Twents onderwijskundig onderzoek (pp. 249-267). Enschede: Twente University Press.1 avan der Linden, WJ uhttp://www.iacat.org/content/het-ontwerpen-van-adaptieve-examens-designing-adaptive-tests00386nas a2200109 4500008004100000245005600041210005600097260002100153100001100174700001500185856007600200 1999 eng d00aImpact of flawed items on ability estimation in CAT0 aImpact of flawed items on ability estimation in CAT aMontreal, Canada1 aLiu, M1 aSteffen, M uhttp://www.iacat.org/content/impact-flawed-items-ability-estimation-cat00534nas a2200109 4500008004100000245013000041210006900171260002100240100002000261700001900281856012400300 1999 eng d00aImplications from information functions and standard errors for determining preferred normed scales for CAT and P and P ASVAB0 aImplications from information functions and standard errors for  aMontreal, Canada1 aNicewander, W A1 aThomasson, G L uhttp://www.iacat.org/content/implications-information-functions-and-standard-errors-determining-preferred-normed-scales01885nas a2200145 4500008004100000020001100041245008200052210006900134260005300203520133100256100001501587700001801602700001601620856010301636 1999 eng d aSeries00aIncorporating content constraints into a multi-stage adaptive testlet design.0 aIncorporating content constraints into a multistage adaptive tes aPrinceton, NJ. USAbLaw School Admission Council3 aMost large-scale testing programs facing computerized adaptive testing (CAT) must face the challenge of maintaining extensive content requirements, but content constraints in computerized adaptive testing (CAT) can compromise the precision and efficiency that could be achieved by a pure maximum information adaptive testing algorithm. This simulation study first evaluated whether realistic content constraints could be met by carefully assembling testlets and appropriately selecting testlets for each test taker that, when combined, would meet the content requirements of the test and would be adapted to the test takers ability level. The second focus of the study was to compare the precision of the content-balanced testlet design with that achieved by the current paper-and-pencil version of the test through data simulation. The results reveal that constraints to control for item exposure, testlet overlap, and efficient pool utilization need to be incorporated into the testlet assembly algorithm. More refinement of the statistical constraints for testlet assembly is also necessary. However, even for this preliminary attempt at assembling content-balanced testlets, the two-stage computerized test simulated with these testlets performed quite well. (Contains 5 figures, 5 tables, and 12 references.) (Author/SLD)1 aReese, L M1 aSchnipke, D L1 aLuebke, S W uhttp://www.iacat.org/content/incorporating-content-constraints-multi-stage-adaptive-testlet-design02471nam a2200133 4500008004100000245004300041210004300084260005200127520201600179653003402195100001502229700002402244856006902268 1999 eng d00aInnovations in computerized assessment0 aInnovations in computerized assessment aMahwah, N.J.bLawrence Erlbaum Associates, Inc.3 aChapters in this book present the challenges and dilemmas faced by researchers as they created new computerized assessments, focusing on issues addressed in developing, scoring, and administering the assessments. Chapters are: (1) "Beyond Bells and Whistles; An Introduction to Computerized Assessment" (Julie B. Olson-Buchanan and Fritz Drasgow); (2) "The Development of a Computerized Selection System for Computer Programmers in a Financial Services Company" (Michael J. Zickar, Randall C. Overton, L. Rogers Taylor, and Harvey J. Harms); (3) "Development of the Computerized Adaptive Testing Version of the Armed Services Vocational Aptitude Battery" (Daniel O. Segall and Kathleen E. Moreno); (4) "CAT for Certification and Licensure" (Betty A. Bergstrom and Mary E. Lunz); (5) "Developing Computerized Adaptive Tests for School Children" (G. Gage Kingsbury and Ronald L. Houser); (6) "Development and Introduction of a Computer Adaptive Graduate Record Examinations General Test" (Craig N. Mills); (7) "Computer Assessment Using Visual Stimuli: A Test of Dermatological Skin Disorders" (Terry A. Ackerman, John Evans, Kwang-Seon Park, Claudia Tamassia, and Ronna Turner); (8) "Creating Computerized Adaptive Tests of Music Aptitude: Problems, Solutions, and Future Directions" (Walter P. Vispoel); (9) "Development of an Interactive Video Assessment: Trials and Tribulations" (Fritz Drasgow, Julie B. Olson-Buchanan, and Philip J. Moberg); (10) "Computerized Assessment of Skill for a Highly Technical Job" (Mary Ann Hanson, Walter C. Borman, Henry J. Mogilka, Carol Manning, and Jerry W. Hedge); (11) "Easing the Implementation of Behavioral Testing through Computerization" (Wayne A. Burroughs, Janet Murray, S. Scott Wesley, Debra R. Medina, Stacy L. Penn, Steven R. Gordon, and Michael Catello); and (12) "Blood, Sweat, and Tears: Some Final Comments on Computerized Assessment." (Fritz Drasgow and Julie B. Olson-Buchanan). Each chapter contains references. (Contains 17 tables and 21 figures.) (SLD)10acomputerized adaptive testing1 aDrasgow, F1 aOlson-Buchanan, J B uhttp://www.iacat.org/content/innovations-computerized-assessment00460nas a2200109 4500008004100000245004100041210004100082260011900123100001600242700002000258856007200278 1999 eng d00aItem calibration and parameter drift0 aItem calibration and parameter drift aW. J. van der Linden and C. A. W. Glas (Eds.), Computer adaptive testing: Theory and practice. Norwell MA: Kluwer.1 aGlas, C A W1 aVeerkamp, W J J uhttp://www.iacat.org/content/item-calibration-and-parameter-drift-000485nas a2200121 4500008004100000245008600041210006900127260001600196100001600212700001500228700001500243856010500258 1999 eng d00aItem exposure in adaptive tests: An empirical investigation of control strategies0 aItem exposure in adaptive tests An empirical investigation of co aLawrence KS1 aParshall, C1 aHogarty, K1 aKromrey, J uhttp://www.iacat.org/content/item-exposure-adaptive-tests-empirical-investigation-control-strategies00473nas a2200097 4500008004100000245008900041210006900130260004700199100001900246856011000265 1999 eng d00aItem nonresponse: Occurrence, causes and imputation of missing answers to test items0 aItem nonresponse Occurrence causes and imputation of missing ans a(M and T Series No 32). Leiden: DSWO Press1 aHuisman, J M E uhttp://www.iacat.org/content/item-nonresponse-occurrence-causes-and-imputation-missing-answers-test-items00436nas a2200109 4500008004100000245008200041210006900123300001200192490000700204100001600211856009900227 1999 eng d00aItem selection in adaptive testing with the sequential probability ratio test0 aItem selection in adaptive testing with the sequential probabili a249-2610 v231 aEggen, Theo uhttp://www.iacat.org/content/item-selection-adaptive-testing-sequential-probability-ratio-test00540nas a2200121 4500008004100000245012100041210006900162260001700231100001500248700001900263700001300282856012300295 1999 eng d00aItem selection in computerized adaptive testing: improving the a-stratified design with the Sympson-Hetter algorithm0 aItem selection in computerized adaptive testing improving the as aMontreal, CA1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://www.iacat.org/content/item-selection-computerized-adaptive-testing-improving-stratified-design-sympson-hetter-100627nas a2200157 4500008004100000245011800041210006900159260002100228100001700249700001900266700001500285700001600300700001500316700001300331856012500344 1999 eng d00aLimiting answer review and change on computerized adaptive vocabulary tests: Psychometric and attitudinal results0 aLimiting answer review and change on computerized adaptive vocab aMontreal, Canada1 aVispoel, W P1 aHendrickson, A1 aBleiler, T1 aWidiatmo, H1 aShrairi, S1 aIhrig, D uhttp://www.iacat.org/content/limiting-answer-review-and-change-computerized-adaptive-vocabulary-tests-psychometric-and-000373nas a2200097 4500008004100000245006100041210006100102260002100163100001100184856008000195 1999 eng d00aManaging CAT item development in the face of uncertainty0 aManaging CAT item development in the face of uncertainty aMontreal, Canada1 aGuo, F uhttp://www.iacat.org/content/managing-cat-item-development-face-uncertainty00566nas a2200097 4500008004100000245009300041210006900134260014400203100001300347856010800360 1999 eng d00aA minimax procedure in the context of sequential mastery testing (Research Report 99-04)0 aminimax procedure in the context of sequential mastery testing R aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aVos, H J uhttp://www.iacat.org/content/minimax-procedure-context-sequential-mastery-testing-research-report-99-0400351nas a2200109 4500008004100000245004300041210004300084260002100127100001300148700001100161856006900172 1999 eng d00aMore efficient use of item inventories0 aMore efficient use of item inventories aMontreal, Canada1 aSmith, R1 aZhu, R uhttp://www.iacat.org/content/more-efficient-use-item-inventories01090nas a2200133 4500008004100000245007800041210006900119300001200188490000700200520059200207653003400799100002300833856010000856 1999 eng d00aMultidimensional adaptive testing with a minimum error-variance criterion0 aMultidimensional adaptive testing with a minimum errorvariance c a398-4120 v243 aAdaptive testing under a multidimensional logistic response model is addressed. An algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. In addition, it is shown how the algorithm can be modified if the interest is in a test with a "simple ability structure". The statistical properties of the adaptive ML estimator are demonstrated for a two-dimensional item pool with several linear combinations of the abilities. 10acomputerized adaptive testing1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-minimum-error-variance-criterion00488nas a2200121 4500008004100000245008700041210006900128300001200197490000700209100002700216700001600243856010700259 1999 eng d00aThe null distribution of person-fit statistics for conventional and adaptive tests0 anull distribution of personfit statistics for conventional and a a327-3450 v231 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/null-distribution-person-fit-statistics-conventional-and-adaptive-tests-000446nas a2200097 4500008004100000245009500041210006900136260002100205100001500226856010700241 1999 eng d00aOn-the-fly adaptive tests: An application of generative modeling to quantitative reasoning0 aOnthefly adaptive tests An application of generative modeling to aMontreal, Canada1 aBejar, I I uhttp://www.iacat.org/content/fly-adaptive-tests-application-generative-modeling-quantitative-reasoning02646nas a2200133 4500008004100000245007300041210006900114300000900183490000700192520216800199653003402367100001602401856009502417 1999 eng d00aOptimal design for item calibration in computerized adaptive testing0 aOptimal design for item calibration in computerized adaptive tes a42200 v593 aItem Response Theory is the psychometric model used for standardized tests such as the Graduate Record Examination. A test-taker's response to an item is modelled as a binary response with success probability depending on parameters for both the test-taker and the item. Two popular models are the two-parameter logistic (2PL) model and the three-parameter logistic (3PL) model. For the 2PL model, the logit of the probability of a correct response equals ai(theta j-bi), where ai and bi are item parameters, while thetaj is the test-taker's parameter, known as "proficiency." The 3PL model adds a nonzero left asymptote to model random response behavior by low theta test-takers. Assigning scores to students requires accurate estimation of theta s, while accurate estimation of theta s requires accurate estimation of the item parameters. The operational implementation of Item Response Theory, particularly following the advent of computerized adaptive testing, generally involves handling these two estimation problems separately. This dissertation addresses the optimal design for item parameter estimation. Most current designs calibrate items with a sample drawn from the overall test-taking population. For 2PL models a sequential design based on the D-optimality criterion has been proposed, while no 3PL design is in the literature. In this dissertation, we design the calibration with the ultimate use of the items in mind, namely to estimate test-takers' proficiency parameters. For both the 2PL and 3PL models, this criterion leads to a locally L-optimal design criterion, named the Minimal Information Loss criterion. In turn, this criterion and the General Equivalence Theorem give a two point design for the 2PL model and a three point design for the 3PL model. A sequential implementation of this optimal design is presented. For the 2PL model, this design is almost 55% more efficient than the simple random sample approach, and 12% more efficient than the locally D-optimal design. For the 3PL model, the proposed design is 34% more efficient than the simple random sample approach. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aBuyske, S G uhttp://www.iacat.org/content/optimal-design-item-calibration-computerized-adaptive-testing00524nas a2200133 4500008004100000245009300041210006900134260002100203100001600224700001400240700001400254700001400268856010800282 1999 eng d00aPerformance of the Sympson-Hetter exposure control algorithm with a polytomous item bank0 aPerformance of the SympsonHetter exposure control algorithm with aMontreal, Canada1 aPastor, D A1 aChiang, C1 aDodd, B G1 aYockey, R uhttp://www.iacat.org/content/performance-sympson-hetter-exposure-control-algorithm-polytomous-item-bank00535nam a2200097 4500008004100000245012500041210006900166260006400235100001200299856012600311 1999 eng d00aThe precision of ability estimation methods for computerized adaptive testing using the generalized partial credit model0 aprecision of ability estimation methods for computerized adaptiv aUnpublished doctoral dissertation, University of Pittsburgh1 aWang, S uhttp://www.iacat.org/content/precision-ability-estimation-methods-computerized-adaptive-testing-using-generalized-partial00462nas a2200109 4500008004100000245009600041210006900137260001300206100001200219700001200231856010900243 1999 eng d00aPrecision of Warm's weighted likelihood estimation of ability for a polytomous model in CAT0 aPrecision of Warms weighted likelihood estimation of ability for aMontreal1 aWang, S1 aWang, T uhttp://www.iacat.org/content/precision-warms-weighted-likelihood-estimation-ability-polytomous-model-cat00390nas a2200121 4500008004100000245004400041210004400085260002100129100001300150700001700163700001800180856007000198 1999 eng d00aPretesting alongside an operational CAT0 aPretesting alongside an operational CAT aMontreal, Canada1 aDavey, T1 aPommerich, M1 aThompson, D T uhttp://www.iacat.org/content/pretesting-alongside-operational-cat00367nas a2200109 4500008004100000245004800041210004800089260002000137100001400157700001300171856007300184 1999 eng d00aPrinciples for administering adaptive tests0 aPrinciples for administering adaptive tests aMontreal Canada1 aMiller, T1 aDavey, T uhttp://www.iacat.org/content/principles-administering-adaptive-tests00504nas a2200109 4500008004100000245010600041210006900147260002100216100001900237700001200256856012600268 1999 eng d00aA procedure to compare conventional and adaptive testing procedures for making single-point decisions0 aprocedure to compare conventional and adaptive testing procedure aMontreal, Canada1 aKingsbury, G G1 aZara, A uhttp://www.iacat.org/content/procedure-compare-conventional-and-adaptive-testing-procedures-making-single-point-decisions00348nas a2200097 4500008004100000245005200041210004800093260002100141100001400162856007400176 1999 eng d00aThe rationale and principles of stratum scoring0 arationale and principles of stratum scoring aMontreal, Canada1 aWise, S L uhttp://www.iacat.org/content/rationale-and-principles-stratum-scoring00467nas a2200133 4500008004100000245007000041210006900111300001200180490000700192100001200199700001600211700001600227856009000243 1999 eng d00aReducing bias in CAT trait estimation: A comparison of approaches0 aReducing bias in CAT trait estimation A comparison of approaches a263-2780 v231 aWang, T1 aHanson, B H1 aLau, C -M H uhttp://www.iacat.org/content/reducing-bias-cat-trait-estimation-comparison-approaches00481nas a2200109 4500008004100000245009400041210006900135260001700204100001600221700001600237856011800253 1999 eng d00aReducing item exposure without reducing precision (much) in computerized adaptive testing0 aReducing item exposure without reducing precision much in comput aMontreal, CA1 aHolmes, R M1 aSegall, D O uhttp://www.iacat.org/content/reducing-item-exposure-without-reducing-precision-much-computerized-adaptive-testing00610nas a2200097 4500008004100000245012700041210006900168260013500237100001400372856012600386 1999 eng d00aResearch and development of a computer-adaptive test of listening comprehension in the less-commonly taught language Hausa0 aResearch and development of a computeradaptive test of listening aM. Chalhoub-Deville (Ed.). Issues in computer-adaptive testing of reading proficiency. Cambridge, UK : Cambridge University Press.1 aDunkel, P uhttp://www.iacat.org/content/research-and-development-computer-adaptive-test-listening-comprehension-less-commonly-taught00405nas a2200109 4500008004100000245005800041210005700099260002100156100001600177700001800193856008400211 1999 eng d00aResponse time feedback on computer-administered tests0 aResponse time feedback on computeradministered tests aMontreal, Canada1 aScrams, D J1 aSchnipke, D L uhttp://www.iacat.org/content/response-time-feedback-computer-administered-tests00544nam a2200097 4500008004100000245012500041210006900166260007500235100001400310856012200324 1999 eng d00aThe robustness of the unidimensional 3PL IRT model when applied to two-dimensional data in computerized adaptive testing0 arobustness of the unidimensional 3PL IRT model when applied to t aUnpublished Ph.D. dissertation, State University of New York at Albany1 aZhao, J C uhttp://www.iacat.org/content/robustness-unidimensional-3pl-irt-model-when-applied-two-dimensional-data-computerized-000354nas a2200085 4500008004100000245006300041210006300104100001200167856008900179 1999 eng d00aSome relationship among issues in CAT item pool management0 aSome relationship among issues in CAT item pool management1 aWang, T uhttp://www.iacat.org/content/some-relationship-among-issues-cat-item-pool-management01182nas a2200133 4500008004100000245006300041210006300104300001100167490000700178520073600185100002000921700001900941856008800960 1999 eng d00aSome reliability estimates for computerized adaptive tests0 aSome reliability estimates for computerized adaptive tests a239-470 v233 aThree reliability estimates are derived for the Bayes modal estimate (BME) and the maximum likelihood estimate (MLE) of θin computerized adaptive tests (CAT). Each reliability estimate is a function of test information. Two of the estimates are shown to be upper bounds to true reliability. The three reliability estimates and the true reliabilities of both MLE and BME were computed for seven simulated CATs. Results showed that the true reliabilities for MLE and BME were nearly identical in all seven tests. The three reliability estimates never differed from the true reliabilities by more than .02 (.01 in most cases). A simple implementation of one reliability estimate was found to accurately estimate reliability in CATs. 1 aNicewander, W A1 aThomasson, G L uhttp://www.iacat.org/content/some-reliability-estimates-computerized-adaptive-tests00403nas a2200097 4500008004100000245006700041210006700108260002100175100001900196856009000215 1999 eng d00aStandard errors of proficiency estimates in stratum scored CAT0 aStandard errors of proficiency estimates in stratum scored CAT aMontreal, Canada1 aKingsbury, G G uhttp://www.iacat.org/content/standard-errors-proficiency-estimates-stratum-scored-cat00488nas a2200121 4500008004100000245008200041210006900123260002100192100001700213700001900230700001500249856010200264 1999 eng d00aStudy of methods to detect aberrant response patterns in computerized testing0 aStudy of methods to detect aberrant response patterns in compute aMontreal, Canada1 aIwamoto, C K1 aNungester, R J1 aLuecht, RM uhttp://www.iacat.org/content/study-methods-detect-aberrant-response-patterns-computerized-testing00534nas a2200097 4500008004100000245014000041210006900181260004600250100001600296856012400312 1999 eng d00aTest anxiety and test performance: Comparing paper-based and computer-adaptive versions of the GRE General Test (Research Report 99-15)0 aTest anxiety and test performance Comparing paperbased and compu aPrinceton NJ: Educational Testing Service1 aPowers, D E uhttp://www.iacat.org/content/test-anxiety-and-test-performance-comparing-paper-based-and-computer-adaptive-versions-gre00537nas a2200097 4500008004100000245006100041210006100102260016700163100001500330856009400345 1999 eng d00aTesting adaptatif et évaluation des processus cognitifs0 aTesting adaptatif et évaluation des processus cognitifs aC. Depover and B. Noël (Éds) : L’évaluation des compétences et des processus cognitifs - Modèles, pratiques et contextes. Bruxelles : De Boeck Université.1 aLaurier, M uhttp://www.iacat.org/content/testing-adaptatif-et-%C3%A9valuation-des-processus-cognitifs00522nas a2200121 4500008004100000245010600041210006900147260002100216100001200237700001500249700001700264856011900281 1999 eng d00aTests informatizados: Fundamentos y aplicaciones (Computerized testing: Fundamentals and applications0 aTests informatizados Fundamentos y aplicaciones Computerized tes aMadrid: Pirmide.1 aOlea, J1 aPonsoda, V1 aPrieto, Eds. uhttp://www.iacat.org/content/tests-informatizados-fundamentos-y-aplicaciones-computerized-testing-fundamentals-and00284nas a2200097 4500008004100000245002700041210002600068260002100094100001500115856005600130 1999 eng d00aTest-taking strategies0 aTesttaking strategies aMontreal, Canada1 aSteffen, M uhttp://www.iacat.org/content/test-taking-strategies00405nas a2200109 4500008004100000245006000041210005900101260002100160100001500181700001300196856008600209 1999 eng d00aTest-taking strategies in computerized adaptive testing0 aTesttaking strategies in computerized adaptive testing aMontreal, Canada1 aSteffen, M1 aWay, W D uhttp://www.iacat.org/content/test-taking-strategies-computerized-adaptive-testing00489nas a2200109 4500008004100000245011200041210006900153300001000222490000600232100001500238856012600253 1999 eng d00aThreats to score comparability with applications to performance assessments and computerized adaptive tests0 aThreats to score comparability with applications to performance  a73-960 v61 aKolen, M J uhttp://www.iacat.org/content/threats-score-comparability-applications-performance-assessments-and-computerized-adaptive-000896nas a2200121 4500008004100000245011200041210006900153300001000222490000600232520039700238100001500635856012400650 1999 eng d00aThreats to score comparability with applications to performance assessments and computerized adaptive tests0 aThreats to score comparability with applications to performance  a73-960 v63 aDevelops a conceptual framework that addresses score comparability for performance assessments, adaptive tests, paper-and-pencil tests, and alternate item pools for computerized tests. Outlines testing situation aspects that might threaten score comparability and describes procedures for evaluating the degree of score comparability. Suggests ways to minimize threats to comparability. (SLD)1 aKolen, M J uhttp://www.iacat.org/content/threats-score-comparability-applications-performance-assessments-and-computerized-adaptive00408nas a2200097 4500008004100000245007200041210006900113260002100182100001600203856009100219 1999 eng d00aUse of conditional item exposure methodology for an operational CAT0 aUse of conditional item exposure methodology for an operational  aMontreal, Canada1 aAnderson, D uhttp://www.iacat.org/content/use-conditional-item-exposure-methodology-operational-cat00356nas a2200097 4500008004100000245005900041210005200100260002100152100001500173856007000188 1999 eng d00aThe use of linear-on-the-fly testing for TOEFL Reading0 ause of linearonthefly testing for TOEFL Reading aMontreal, Canada1 aCarey, P A uhttp://www.iacat.org/content/use-linear-fly-testing-toefl-reading01910nas a2200229 4500008004100000245008600041210006900127300001000196490000700206520111400213653003201327653003701359653001001396653003401406653003001440653002901470653003201499100001601531700001801547700001301565856010201578 1999 eng d00aThe use of Rasch analysis to produce scale-free measurement of functional ability0 ause of Rasch analysis to produce scalefree measurement of functi a83-900 v533 aInnovative applications of Rasch analysis can lead to solutions for traditional measurement problems and can produce new assessment applications in occupational therapy and health care practice. First, Rasch analysis is a mechanism that translates scores across similar functional ability assessments, thus enabling the comparison of functional ability outcomes measured by different instruments. This will allow for the meaningful tracking of functional ability outcomes across the continuum of care. Second, once the item-difficulty order of an instrument or item bank is established by Rasch analysis, computerized adaptive testing can be used to target items to the patient's ability level, reducing assessment length by as much as one half. More importantly, Rasch analysis can provide the foundation for "equiprecise" measurement or the potential to have precise measurement across all levels of functional ability. The use of Rasch analysis to create scale-free measurement of functional ability demonstrates how this methodlogy can be used in practical applications of clinical and outcome assessment.10a*Activities of Daily Living10aDisabled Persons/*classification10aHuman10aOccupational Therapy/*methods10aPredictive Value of Tests10aQuestionnaires/standards10aSensitivity and Specificity1 aVelozo, C A1 aKielhofner, G1 aLai, J-S uhttp://www.iacat.org/content/use-rasch-analysis-produce-scale-free-measurement-functional-ability00429nas a2200109 4500008004100000245007300041210006900114300001400183490001000197100001300207856009900220 1999 eng d00aUsing Bayesian decision theory to design a computerized mastery test0 aUsing Bayesian decision theory to design a computerized mastery  a271–2920 v24(3)1 aVos, H J uhttp://www.iacat.org/content/using-bayesian-decision-theory-design-computerized-mastery-test-001190nas a2200157 4500008004100000245010900041210006900150300001200219490000700231520058300238653003400821100002300855700001600878700001800894856012000912 1999 eng d00aUsing response-time constraints to control for differential speededness in computerized adaptive testing0 aUsing responsetime constraints to control for differential speed a195-2100 v233 aAn item-selection algorithm is proposed for neutralizing the differential effects of time limits on computerized adaptive test scores. The method is based on a statistical model for distributions of examinees’ response times on items in a bank that is updated each time an item is administered. Predictions from the model are used as constraints in a 0-1 linear programming model for constrained adaptive testing that maximizes the accuracy of the trait estimator. The method is demonstrated empirically using an item bank from the Armed Services Vocational Aptitude Battery. 10acomputerized adaptive testing1 avan der Linden, WJ1 aScrams, D J1 aSchnipke, D L uhttp://www.iacat.org/content/using-response-time-constraints-control-differential-speededness-computerized-adaptive00507nas a2200097 4500008004100000245013100041210006900172260003400241100001000275856012400285 1999 eng d00aWISCAT: Een computergestuurd toetspakket voor rekenen en wiskunde [A computerized test package for arithmetic and mathematics]0 aWISCAT Een computergestuurd toetspakket voor rekenen en wiskunde aCito: Arnhem, The Netherlands1 aCito. uhttp://www.iacat.org/content/wiscat-een-computergestuurd-toetspakket-voor-rekenen-en-wiskunde-computerized-test-package00633nas a2200109 4500008004100000245011500041210006900156260014400225100001600369700001300385856012500398 1998 eng d00aAdaptive mastery testing using the Rasch model and Bayesian sequential decision theory (Research Report 98-15)0 aAdaptive mastery testing using the Rasch model and Bayesian sequ aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aVos, H J uhttp://www.iacat.org/content/adaptive-mastery-testing-using-rasch-model-and-bayesian-sequential-decision-theory-research00348nas a2200121 4500008004100000245003300041210003300074260001700107100001100124700001300135700001600148856006200164 1998 eng d00aAdaptive testing without IRT0 aAdaptive testing without IRT aSan Diego CA1 aYan, D1 aLewis, C1 aStocking, M uhttp://www.iacat.org/content/adaptive-testing-without-irt00404nas a2200109 4500008004100000245005700041210005700098260002000155100001400175700002100189856008400210 1998 eng d00aAlternatives for scoring computerized adaptive tests0 aAlternatives for scoring computerized adaptive tests aPhiladelphia PA1 aDodd, B G1 aFitzpatrick, S J uhttp://www.iacat.org/content/alternatives-scoring-computerized-adaptive-tests-000493nas a2200133 4500008004100000245005700041210005700098260005700155100001400212700002100226700001600247700001400263856008200277 1998 eng d00aAlternatives for scoring computerized adaptive tests0 aAlternatives for scoring computerized adaptive tests aMahwah, N.J., USAbLawrence Erlbaum Associates, Inc.1 aDodd, B G1 aFitzpatrick, S J1 aFremer, J J1 aWard, W C uhttp://www.iacat.org/content/alternatives-scoring-computerized-adaptive-tests00469nas a2200109 4500008004100000245009500041210006900136260001400205100001300219700001500232856011200247 1998 eng d00aApplication of an IRT ideal point model to computer adaptive assessment of job performance0 aApplication of an IRT ideal point model to computer adaptive ass aDallas TX1 aStark, S1 aDrasgow, F uhttp://www.iacat.org/content/application-irt-ideal-point-model-computer-adaptive-assessment-job-performance00448nas a2200097 4500008004100000245009600041210006900137260001700206100001500223856011200238 1998 eng d00aApplication of direct optimization for on-line calibration in computerized adaptive testing0 aApplication of direct optimization for online calibration in com aSan Diego CA1 aKrass, I A uhttp://www.iacat.org/content/application-direct-optimization-line-calibration-computerized-adaptive-testing00486nam a2200097 4500008004100000245006700041210006700108260010400175100001700279856009200296 1998 eng d00aApplications of network flows to computerized adaptive testing0 aApplications of network flows to computerized adaptive testing aDissertation, Rutgers Center for Operations Research (RUTCOR), Rutgers University, New Brunswick NJ1 aCordova, M J uhttp://www.iacat.org/content/applications-network-flows-computerized-adaptive-testing-001456nas a2200133 4500008004100000245006700041210006700108300000900175490000700184520098800191653003401179100001901213856009001232 1998 eng d00aApplications of network flows to computerized adaptive testing0 aApplications of network flows to computerized adaptive testing a08550 v593 aRecently, the concept of Computerized Adaptive Testing (CAT) has been receiving ever growing attention from the academic community. This is so because of both practical and theoretical considerations. Its practical importance lies in the advantages of CAT over the traditional (perhaps outdated) paper-and-pencil test in terms of time, accuracy, and money. The theoretical interest is sparked by its natural relationship to Item Response Theory (IRT). This dissertation offers a mathematical programming approach which creates a model that generates a CAT that takes care of many questions concerning the test, such as feasibility, accuracy and time of testing, as well as item pool security. The CAT generated is designed to obtain the most information about a single test taker. Several methods for eatimating the examinee's ability, based on the (dichotomous) responses to the items in the test, are also offered here. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aClaudio, M J C uhttp://www.iacat.org/content/applications-network-flows-computerized-adaptive-testing00412nas a2200109 4500008004100000245006700041210006500108260001700173100001600190700001300206856008300219 1998 eng d00aA Bayesian approach to detection of item preknowledge in a CAT0 aBayesian approach to detection of item preknowledge in a CAT aSan Diego CA1 aMcLeod, L D1 aLewis, C uhttp://www.iacat.org/content/bayesian-approach-detection-item-preknowledge-cat01291nas a2200145 4500008004100000245007300041210006900114300001200183490000700195520080400202100001701006700001501023700001101038856009601049 1998 eng d00aBayesian identification of outliers in computerized adaptive testing0 aBayesian identification of outliers in computerized adaptive tes a910-9190 v933 aWe consider the problem of identifying examinees with aberrant response patterns in a computerized adaptive test (CAT). The vec-tor of responses yi of person i from the CAT comprise a multivariate response vector. Multivariate observations may be outlying in manydi erent directions and we characterize speci c directions as corre- sponding to outliers with different interpretations. We develop a class of outlier statistics to identify different types of outliers based on a con-trol chart type methodology. The outlier methodology is adaptable to general longitudinal discrete data structures. We consider several procedures to judge how extreme a particular outlier is. Data from the National Council Licensure EXamination (NCLEX) motivates our development and is used to illustrate the results.1 aBradlow, E T1 aWeiss, R E1 aCho, M uhttp://www.iacat.org/content/bayesian-identification-outliers-computerized-adaptive-testing00394nas a2200109 4500008004100000245005800041210005800099300001200157490000700169100002300176856008500199 1998 eng d00aBayesian item selection criteria for adaptive testing0 aBayesian item selection criteria for adaptive testing a201-2160 v631 avan der Linden, WJ uhttp://www.iacat.org/content/bayesian-item-selection-criteria-adaptive-testing-000602nas a2200109 4500008004100000245008900041210006900130260014400199100002300343700001600366856011000382 1998 eng d00aCapitalization on item calibration error in adaptive testing (Research Report 98-07)0 aCapitalization on item calibration error in adaptive testing Res aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ1 aGlas, C A W uhttp://www.iacat.org/content/capitalization-item-calibration-error-adaptive-testing-research-report-98-0700336nas a2200097 4500008004100000245003300041210003100074260005800105100001500163856006000178 1998 eng d00aCASTISEL [Computer software]0 aCASTISEL Computer software aPhiladelphia, PA: National Board of Medical Examiners1 aLuecht, RM uhttp://www.iacat.org/content/castisel-computer-software00324nas a2200121 4500008004100000245002500041210002500066260001400091100001100105700001800116700001400134856005400148 1998 eng d00aCAT item calibration0 aCAT item calibration aSan Diego1 aHsu, Y1 aThompson, T D1 aChen, W-H uhttp://www.iacat.org/content/cat-item-calibration00481nas a2200097 4500008004100000245011200041210006900153260001800222100001900240856012400259 1998 eng d00aCAT Item exposure control: New evaluation tools, alternate methods and integration into a total CAT program0 aCAT Item exposure control New evaluation tools alternate methods aSan Diego, CA1 aThomasson, G L uhttp://www.iacat.org/content/cat-item-exposure-control-new-evaluation-tools-alternate-methods-and-integration-total-cat00687nas a2200169 4500008004100000020003000041245009600071210006900167260006400236100001900300700001700319700002100336700001300357700001700370700001500387856011500402 1998 eng d aETS Research Report 98-3800aComparability of paper-and-pencil and computer adaptive test scores on the GRE General Test0 aComparability of paperandpencil and computer adaptive test score aPrinceton, N.J.bEducational Testing ServicescAugust, 19981 aSchaeffer, G A1 aBridgeman, B1 aGolub-Smith, M L1 aLewis, C1 aPotenza, M T1 aSteffen, M uhttp://www.iacat.org/content/comparability-paper-and-pencil-and-computer-adaptive-test-scores-gre-general-test00729nas a2200157 4500008004100000245018900041210006900230260004700299100001700346700001700363700002100380700001300401700001700414700001500431856012500446 1998 eng d00aComparability of paper-and-pencil and computer adaptive test scores on the GRE General Test (GRE Board Professional Report No 95-08P; Educational Testing Service Research Report 98-38)0 aComparability of paperandpencil and computer adaptive test score aPrinceton, NJ: Educational Testing Service1 aSchaeffer, G1 aBridgeman, B1 aGolub-Smith, M L1 aLewis, C1 aPotenza, M T1 aSteffen, M uhttp://www.iacat.org/content/comparability-paper-and-pencil-and-computer-adaptive-test-scores-gre-general-test-gre-board00521nas a2200109 4500008004100000245009000041210006900131260007000200100001500270700001300285856011300298 1998 eng d00aA comparative study of item exposure control methods in computerized adaptive testing0 acomparative study of item exposure control methods in computeriz aResearch Report Series 98-3, Iowa City: American College Testing.1 aChang, S-W1 aTwu, B-Y uhttp://www.iacat.org/content/comparative-study-item-exposure-control-methods-computerized-adaptive-testing-000499nam a2200097 4500008004100000245009000041210006900131260007300200100001500273856011300288 1998 eng d00aA comparative study of item exposure control methods in computerized adaptive testing0 acomparative study of item exposure control methods in computeriz aUnpublished doctoral dissertation, University of Iowa , Iowa City IA1 aChang, S-W uhttp://www.iacat.org/content/comparative-study-item-exposure-control-methods-computerized-adaptive-testing-100496nas a2200109 4500008004100000245012000041210006900161260001400230100001200244700001200256856011800268 1998 eng d00aComparing and combining dichotomous and polytomous items with SPRT procedure in computerized classification testing0 aComparing and combining dichotomous and polytomous items with SP aSan Diego1 aLau, CA1 aWang, T uhttp://www.iacat.org/content/comparing-and-combining-dichotomous-and-polytomous-items-sprt-procedure-computerized00466nas a2200121 4500008004100000245008300041210006900124300001200193490000700205100001300212700001500225856010400240 1998 eng d00aA comparison of item exposure control methods in computerized adaptive testing0 acomparison of item exposure control methods in computerized adap a311-3270 v351 aRevuelta1 aPonsoda, V uhttp://www.iacat.org/content/comparison-item-exposure-control-methods-computerized-adaptive-testing00544nas a2200133 4500008004100000245012500041210006900166300001200235490000700247100001200254700001100266700001400277856011900291 1998 eng d00aA comparison of maximum likelihood estimation and expected a posteriori estimation in CAT using the partial credit model0 acomparison of maximum likelihood estimation and expected a poste a569-5950 v581 aChen, S1 aHou, L1 aDodd, B G uhttp://www.iacat.org/content/comparison-maximum-likelihood-estimation-and-expected-posteriori-estimation-cat-using00470nas a2200109 4500008004100000245009400041210006900135100001200204700001300216700001900229856011200248 1998 eng d00aA comparison of two methods of controlling item exposure in computerized adaptive testing0 acomparison of two methods of controlling item exposure in comput1 aTang, L1 aJiang, H1 aChang, Hua-Hua uhttp://www.iacat.org/content/comparison-two-methods-controlling-item-exposure-computerized-adaptive-testing00506nas a2200109 4500008004100000245008000041210006900121260006100190100001900251700001500270856011100285 1998 eng d00aComputer adaptive testing – Approaches for item selection and measurement0 aComputer adaptive testing Approaches for item selection and meas aRutgers Center for Operations Research, New Brunswick NJ1 aArmstrong, R D1 aJones, D H uhttp://www.iacat.org/content/computer-adaptive-testing-%E2%80%93-approaches-item-selection-and-measurement00413nas a2200109 4500008004100000245006600041210006500107300001300172490000800185100001500193856009500208 1998 eng d00aComputer-assisted test assembly using optimization heuristics0 aComputerassisted test assembly using optimization heuristics a224-236.0 v22 1 aLuecht, RM uhttp://www.iacat.org/content/computer-assisted-test-assembly-using-optimization-heuristics00557nas a2200157 4500008004100000245007600041210006900117260001400186100001600200700001600216700002000232700001500252700001400267700001800281856010000299 1998 eng d00aComputerized adaptive rating scales that measure contextual performance0 aComputerized adaptive rating scales that measure contextual perf aDallas TX1 aBorman, W C1 aHanson, M A1 aMontowidlo, S J1 aDrasgow, F1 aFoster, L1 aKubisiak, U C uhttp://www.iacat.org/content/computerized-adaptive-rating-scales-measure-contextual-performance00879nas a2200133 4500008004100000245006300041210006200104300001000166490000700176520043400183100002400617700001600641856008800657 1998 eng d00aComputerized adaptive testing: What it is and how it works0 aComputerized adaptive testing What it is and how it works a45-520 v383 aDescribes the workings of computerized adaptive testing (CAT). Focuses on the key concept of information and then discusses two important components of a CAT system: the calibrated item bank and the testing algorithm. Describes a CAT that was designed for making placement decisions on the basis of two typical test administrations and notes the most significant differences between traditional paper-based testing and CAT. (AEF)1 aStraetmans, G J J M1 aEggen, Theo uhttp://www.iacat.org/content/computerized-adaptive-testing-what-it-and-how-it-works00446nas a2200121 4500008004100000245006400041210006400105260001500169100001900184700001500203700001600218856009000234 1998 eng d00aComputerized adaptive testing with multiple form structures0 aComputerized adaptive testing with multiple form structures aUrbana, IL1 aArmstrong, R D1 aJones, D H1 aBerliner, N uhttp://www.iacat.org/content/computerized-adaptive-testing-multiple-form-structures-000448nas a2200121 4500008004100000245006600041210006600107260001400173100001600187700001300203700001600216856009400232 1998 eng d00aConstructing adaptive tests to parallel conventional programs0 aConstructing adaptive tests to parallel conventional programs aSan Diego1 aThompson, T1 aDavey, T1 aNering, M L uhttp://www.iacat.org/content/constructing-adaptive-tests-parallel-conventional-programs-100462nas a2200121 4500008004100000245007300041210006900114260001500183100001600198700001300214700001600227856009700243 1998 eng d00aConstructing passage-based tests that parallel conventional programs0 aConstructing passagebased tests that parallel conventional progr aUrbana, IL1 aThompson, T1 aDavey, T1 aNering, M L uhttp://www.iacat.org/content/constructing-passage-based-tests-parallel-conventional-programs00413nas a2200109 4500008004100000245006000041210006000101260002400161100001300185700001600198856008900214 1998 eng d00aControlling item exposure and maintaining item security0 aControlling item exposure and maintaining item security a” Philadelphia PA1 aDavey, T1 aNering, M L uhttp://www.iacat.org/content/controlling-item-exposure-and-maintaining-item-security01273nas a2200133 4500008004100000245008600041210006900127300001000196490000700206520078600213100001800999700001301017856010901030 1998 eng d00aControlling item exposure conditional on ability in computerized adaptive testing0 aControlling item exposure conditional on ability in computerized a57-750 v233 aThe interest in the application of large-scale adaptive testing for secure tests has served to focus attention on issues that arise when theoretical advances are made operational. One such issue is that of ensuring item and pool security in the continuous testing environment made possible by the computerized admin-istration of a test, as opposed to the more periodic testing environment typically used for linear paper-and-pencil tests. This article presents a new method of controlling the exposure rate of items conditional on ability level in this continuous testing environment. The properties of such conditional control on the exposure rates of items, when used in conjunction with a particular adaptive testing algorithm, are explored through studies with simulated data. 1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/controlling-item-exposure-conditional-ability-computerized-adaptive-testing00580nas a2200121 4500008004100000245009500041210006900136260009200205100001300297700001500310700001800325856011500343 1998 eng d00aDeveloping, maintaining, and renewing the item inventory to support computer-based testing0 aDeveloping maintaining and renewing the item inventory to suppor aComputer-Based Testing: Building the Foundation for Future Assessments, Philadelphia PA1 aWay, W D1 aSteffen, M1 aAnderson, G S uhttp://www.iacat.org/content/developing-maintaining-and-renewing-item-inventory-support-computer-based-testing00493nas a2200109 4500008004100000245007700041210006900118260006500187100001600252700001400268856010100282 1998 eng d00aDevelopment and evaluation of online calibration procedures (TCN 96-216)0 aDevelopment and evaluation of online calibration procedures TCN  aChampaign IL: Algorithm Design and Measurement Services, Inc1 aLevine, M L1 aWilliams. uhttp://www.iacat.org/content/development-and-evaluation-online-calibration-procedures-tcn-96-21600484nas a2200109 4500008004100000245007800041210006900119260004600188100001700234700001900251856010400270 1998 eng d00aDoes adaptive testing violate local independence? (Research Report 98-33)0 aDoes adaptive testing violate local independence Research Report aPrinceton NJ: Educational Testing Service1 aMislevy, R J1 aChang, Hua-Hua uhttp://www.iacat.org/content/does-adaptive-testing-violate-local-independence-research-report-98-3301753nas a2200217 4500008004100000245015600041210006900197300001100266490000600277520090700283653004001190653002201230653002401252653002301276653003701299653001001336653002401346653002701370100001801397856012001415 1998 eng d00aThe effect of item pool restriction on the precision of ability measurement for a Rasch-based CAT: comparisons to traditional fixed length examinations0 aeffect of item pool restriction on the precision of ability meas a97-1220 v23 aThis paper describes a method for examining the precision of a computerized adaptive test with a limited item pool. Standard errors of measurement ascertained in the testing of simulees with a CAT using a restricted pool were compared to the results obtained in a live paper-and-pencil achievement testing of 4494 nursing students on four versions of an examination of calculations of drug administration. CAT measures of precision were considered when the simulated examine pools were uniform and normal. Precision indices were also considered in terms of the number of CAT items required to reach the precision of the traditional tests. Results suggest that regardless of the size of the item pool, CAT provides greater precision in measurement with a smaller number of items administered even when the choice of items is limited but fails to achieve equiprecision along the entire ability continuum.10a*Decision Making, Computer-Assisted10aComparative Study10aComputer Simulation10aEducation, Nursing10aEducational Measurement/*methods10aHuman10aModels, Statistical10aPsychometrics/*methods1 aHalkitis, P N uhttp://www.iacat.org/content/effect-item-pool-restriction-precision-ability-measurement-rasch-based-cat-comparisons00477nas a2200109 4500008004100000245009400041210006900135260001700204100001600221700001500237856011500252 1998 eng d00aEffect of item selection on item exposure rates within a computerized classification test0 aEffect of item selection on item exposure rates within a compute aSan Diego CA1 aKalohn, J C1 aSpray, J A uhttp://www.iacat.org/content/effect-item-selection-item-exposure-rates-within-computerized-classification-test00468nas a2200097 4500008004100000245011700041210006900158260001500227100001300242856011500255 1998 eng d00aAn empirical Bayes approach to Mantel-Haenszel DIF analysis: Theoretical development and application to CAT data0 aempirical Bayes approach to MantelHaenszel DIF analysis Theoreti aUrbana, IL1 aZwick, R uhttp://www.iacat.org/content/empirical-bayes-approach-mantel-haenszel-dif-analysis-theoretical-development-and00465nas a2200121 4500008004100000245007700041210006900118260001400187100001200201700001100213700001600224856010300240 1998 eng d00aEssentially unbiased Bayesian estimates in computerized adaptive testing0 aEssentially unbiased Bayesian estimates in computerized adaptive aSan Diego1 aWang, T1 aLau, C1 aHanson, B A uhttp://www.iacat.org/content/essentially-unbiased-bayesian-estimates-computerized-adaptive-testing00430nas a2200109 4500008004100000245007000041210006900111260001500180100001300195700001600208856009600224 1998 eng d00aEvaluating and insuring measurement precision in adaptive testing0 aEvaluating and insuring measurement precision in adaptive testin aUrbana, IL1 aDavey, T1 aNering, M L uhttp://www.iacat.org/content/evaluating-and-insuring-measurement-precision-adaptive-testing00435nas a2200109 4500008004100000245008200041210006900123260001500192100001500207700001100222856009200233 1998 eng d00aEvaluation of methods for the use of underutilized items in a CAT environment0 aEvaluation of methods for the use of underutilized items in a CA aUrbana, IL1 aSteffen, M1 aLiu, M uhttp://www.iacat.org/content/evaluation-methods-use-underutilized-items-cat-environment00395nas a2200097 4500008004100000245007200041210006800113260001400181100001500195856008700210 1998 eng d00aAn examination of item-level response times from an operational CAT0 aexamination of itemlevel response times from an operational CAT aUrbana IL1 aSwygert, K uhttp://www.iacat.org/content/examination-item-level-response-times-operational-cat00417nas a2200109 4500008004100000245006800041210006800109260001400177100001300191700001300204856009000217 1998 eng d00aExpected losses for individuals in Computerized Mastery Testing0 aExpected losses for individuals in Computerized Mastery Testing aSan Diego1 aSmith, R1 aLewis, C uhttp://www.iacat.org/content/expected-losses-individuals-computerized-mastery-testing00523nas a2200109 4500008004100000245010600041210006900147260004100216100001400257700001800271856012400289 1998 eng d00aFeasibility studies of two-stage testing in large-scale educational assessment: Implications for NAEP0 aFeasibility studies of twostage testing in largescale educationa aAmerican Institutes for Research, CA1 aBock, R D1 aZimowski, M F uhttp://www.iacat.org/content/feasibility-studies-two-stage-testing-large-scale-educational-assessment-implications-naep00380nas a2200097 4500008004100000245005200041210005000093260004600143100001800189856007500207 1998 eng d00aA framework for comparing adaptive test designs0 aframework for comparing adaptive test designs aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/framework-comparing-adaptive-test-designs00453nas a2200097 4500008004100000245009700041210006900138260001800207100001500225856011500240 1998 eng d00aA framework for exploring and controlling risks associated with test item exposure over time0 aframework for exploring and controlling risks associated with te aSan Diego, CA1 aLuecht, RM uhttp://www.iacat.org/content/framework-exploring-and-controlling-risks-associated-test-item-exposure-over-time00478nas a2200121 4500008004100000245008300041210006900124260001500193100001600208700001300224700001600237856010300253 1998 eng d00aA hybrid method for controlling item exposure in computerized adaptive testing0 ahybrid method for controlling item exposure in computerized adap aUrbana, IL1 aNering, M L1 aDavey, T1 aThompson, T uhttp://www.iacat.org/content/hybrid-method-controlling-item-exposure-computerized-adaptive-testing00480nas a2200121 4500008004100000245008300041210006900124260001500193100001600208700001300224700001600237856010500253 1998 eng d00aA hybrid method for controlling item exposure in computerized adaptive testing0 ahybrid method for controlling item exposure in computerized adap aUrbana, IL1 aNering, M L1 aDavey, T1 aThompson, T uhttp://www.iacat.org/content/hybrid-method-controlling-item-exposure-computerized-adaptive-testing-000427nas a2200109 4500008004100000245007600041210006900117260001700186100000700203700001400210856009300224 1998 eng d00aThe impact of nonmodel-fitting responses in a realistic CAT environment0 aimpact of nonmodelfitting responses in a realistic CAT environme aSan Diego CA1 aYi1 aNering, M uhttp://www.iacat.org/content/impact-nonmodel-fitting-responses-realistic-cat-environment00408nas a2200109 4500008004100000245006800041210006400109260001500173100001100188700001500199856008400214 1998 eng d00aThe impact of scoring flawed items on ability estimation in CAT0 aimpact of scoring flawed items on ability estimation in CAT aUrbana, IL1 aLiu, M1 aSteffen, M uhttp://www.iacat.org/content/impact-scoring-flawed-items-ability-estimation-cat00553nas a2200097 4500008004100000245008000041210006900121260014400190100001700334856010400351 1998 eng d00aInnovations in computer-based ability testing: Promise, problems and perils0 aInnovations in computerbased ability testing Promise problems an aIn Hakel, M.D. (Ed.) Beyond multiple choice: Alternatives to traditional testing for selection. Hillsdale, NJ: Lawrence Erlbaum Associates.1 aMcBride, J R uhttp://www.iacat.org/content/innovations-computer-based-ability-testing-promise-problems-and-perils00580nas a2200109 4500008004100000245001700041210001700058490000600075520032700081100001600408856004600424 1998 eng d00aItem banking0 aItem banking0 v63 aDiscusses the advantages and disadvantages of using item banks while providing useful information to those who are considering implementing an item banking project in their school district. The primary advantage of item banking is in test development. Also describes start-up activities in implementing item banking. (SLD)1 aRudner, L M uhttp://www.iacat.org/content/item-banking00419nas a2200097 4500008004100000245007600041210006900117260001700186100001800203856010000221 1998 eng d00aItem development and pretesting in a computer-based testing environment0 aItem development and pretesting in a computerbased testing envir aPhiladelphia1 aParshall, C G uhttp://www.iacat.org/content/item-development-and-pretesting-computer-based-testing-environment00516nas a2200097 4500008004100000245013300041210006900174260003500243100001600278856012400294 1998 eng d00aItem selection in adaptive testing with the sequential probability ratio test (Measurement and Research Department Report, 98-1)0 aItem selection in adaptive testing with the sequential probabili aArnhem, The Netherlands: Cito.1 aEggen, Theo uhttp://www.iacat.org/content/item-selection-adaptive-testing-sequential-probability-ratio-test-measurement-and-research00510nas a2200121 4500008004100000245010100041210006900142300001200211490000700223100001300230700001900243856012600262 1998 eng d00aItem selection in computerized adaptive testing: Should more discriminating items be used first?0 aItem selection in computerized adaptive testing Should more disc a249-2660 v381 aHau, K T1 aChang, Hua-Hua uhttp://www.iacat.org/content/item-selection-computerized-adaptive-testing-should-more-discriminating-items-be-used-firs-000569nas a2200097 4500008004100000245020300041210006900244100001300313700001900326856012600345 1998 eng d00aItem selection in computerized adaptive testing: Should more discriminating items be used first? Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA0 aItem selection in computerized adaptive testing Should more disc1 aHau, K T1 aChang, Hua-Hua uhttp://www.iacat.org/content/item-selection-computerized-adaptive-testing-should-more-discriminating-items-be-used-firs-101240nas a2200157 4500008004100000245006600041210006600107300001000173490000600183520071600189653003400905100001500939700001700954700001900971856009200990 1998 eng d00aMaintaining content validity in computerized adaptive testing0 aMaintaining content validity in computerized adaptive testing a29-410 v33 aThe authors empirically demonstrate some of the trade-offs which can occur when content balancing is imposed in computerized adaptive testing (CAT) forms or conversely, when it is ignored. The authors contend that the content validity of a CAT form can actually change across a score scale when content balancing is ignored. However they caution that, efficiency and score precision can be severely reduced by over specifying content restrictions in a CAT form. The results from 2 simulation studies are presented as a means of highlighting some of the trade-offs that could occur between content and statistical considerations in CAT form assembly. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aLuecht, RM1 aChamplain, A1 aNungester, R J uhttp://www.iacat.org/content/maintaining-content-validity-computerized-adaptive-testing00395nas a2200121 4500008004100000245005100041210005100092300001200143490000700155100001100162700002000173856008000193 1998 eng d00aMeasuring change conventionally and adaptively0 aMeasuring change conventionally and adaptively a882-8970 v581 aMay, K1 aNicewander, W A uhttp://www.iacat.org/content/measuring-change-conventionally-and-adaptively01439nas a2200145 4500008004100000245005300041210005100094300001200145490000700157520098100164653003401145100002301179700001501202856007601217 1998 eng d00aA model for optimal constrained adaptive testing0 amodel for optimal constrained adaptive testing a259-2700 v223 aA model for constrained computerized adaptive testing is proposed in which the information in the test at the trait level (0) estimate is maximized subject to a number of possible constraints on the content of the test. At each item-selection step, a full test is assembled to have maximum information at the current 0 estimate, fixing the items already administered. Then the item with maximum in-formation is selected. All test assembly is optimal because a linear programming (LP) model is used that automatically updates to allow for the attributes of the items already administered and the new value of the 0 estimator. The LP model also guarantees that each adaptive test always meets the entire set of constraints. A simulation study using a bank of 753 items from the Law School Admission Test showed that the 0 estimator for adaptive tests of realistic lengths did not suffer any loss of efficiency from the presence of 433 constraints on the item selection process. 10acomputerized adaptive testing1 avan der Linden, WJ1 aReese, L M uhttp://www.iacat.org/content/model-optimal-constrained-adaptive-testing00459nas a2200109 4500008004100000245009100041210006900132260001500201100001600216700001300232856010400245 1998 eng d00aA new approach for the detection of item preknowledge in computerized adaptive testing0 anew approach for the detection of item preknowledge in computeri aUrbana, IL1 aMcLeod, L D1 aLewis, C uhttp://www.iacat.org/content/new-approach-detection-item-preknowledge-computerized-adaptive-testing00466nas a2200109 4500008004100000245009200041210006900133260001700202100000700219700001400226856011600240 1998 eng d00aNonmodel-fitting responses and robust ability estimation in a realistic CAT environment0 aNonmodelfitting responses and robust ability estimation in a rea aSan Diego CA1 aYi1 aNering, M uhttp://www.iacat.org/content/nonmodel-fitting-responses-and-robust-ability-estimation-realistic-cat-environment00438nas a2200121 4500008004100000245006700041210006700108300001200175490000700187100001800194700001500212856008900227 1998 eng d00aOptimal design of item pools for computerized adaptive testing0 aOptimal design of item pools for computerized adaptive testing a271-2790 v221 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/optimal-design-item-pools-computerized-adaptive-testing00390nas a2200109 4500008004100000245006000041210005900101300001200160490001000172100001300182856008500195 1998 eng d00aOptimal sequential rules for computer-based instruction0 aOptimal sequential rules for computerbased instruction a133-1540 v19(2)1 aVos, H J uhttp://www.iacat.org/content/optimal-sequential-rules-computer-based-instruction00414nas a2200109 4500008004100000245006500041210006500106300001200171490000700183100002300190856009100213 1998 eng d00aOptimal test assembly of psychological and educational tests0 aOptimal test assembly of psychological and educational tests a195-2110 v221 avan der Linden, WJ uhttp://www.iacat.org/content/optimal-test-assembly-psychological-and-educational-tests00411nas a2200109 4500008004100000245006300041210006300104260001800167100001400185700001500199856008700214 1998 eng d00aPatterns of item exposure using a randomized CAT algorithm0 aPatterns of item exposure using a randomized CAT algorithm aSan Diego, CA1 aLunz, M E1 aStahl, J A uhttp://www.iacat.org/content/patterns-item-exposure-using-randomized-cat-algorithm00644nas a2200109 4500008004100000245011100041210006900152260014400221100002700365700001600392856012600408 1998 eng d00aPerson fit based on statistical process control in an adaptive testing environment (Research Report 98-13)0 aPerson fit based on statistical process control in an adaptive t aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://www.iacat.org/content/person-fit-based-statistical-process-control-adaptive-testing-environment-research-report-9800367nas a2200109 4500008004100000245005100041210005100092300001200143490000700155100001800162856007700180 1998 eng d00aPractical issues in computerized test assembly0 aPractical issues in computerized test assembly a292-3020 v221 aWightman, L F uhttp://www.iacat.org/content/practical-issues-computerized-test-assembly00459nas a2200121 4500008004100000245007800041210006900119300001200188490000700200100001200207700001700219856010100236 1998 eng d00aProperties of ability estimation methods in computerized adaptive testing0 aProperties of ability estimation methods in computerized adaptiv a109-1350 v351 aWang, T1 aVispoel, W P uhttp://www.iacat.org/content/properties-ability-estimation-methods-computerized-adaptive-testing00398nas a2200109 4500008004100000245006400041210006400105300001000169490001000179100001300189856008600202 1998 eng d00aProtecting the integrity of computerized testing item pools0 aProtecting the integrity of computerized testing item pools a17-270 v17(4)1 aWay, W D uhttp://www.iacat.org/content/protecting-integrity-computerized-testing-item-pools00522nas a2200109 4500008004100000245013500041210006900176300002300245490000700268100001700275856012000292 1998 eng d00aPsychometric characteristics of computer-adaptive and self-adaptive vocabulary tests: The role of answer feedback and test anxiety0 aPsychometric characteristics of computeradaptive and selfadaptiv a328-347 or 155-1670 v351 aVispoel, W P uhttp://www.iacat.org/content/psychometric-characteristics-computer-adaptive-and-self-adaptive-vocabulary-tests-role00586nas a2200097 4500008004100000245010000041210006900141260014400210100001600354856011800370 1998 eng d00aQuality control of on-line calibration in computerized adaptive testing (Research Report 98-03)0 aQuality control of online calibration in computerized adaptive t aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W uhttp://www.iacat.org/content/quality-control-line-calibration-computerized-adaptive-testing-research-report-98-0300598nas a2200133 4500008004100000245012500041210006900166260004600235100001400281700001600295700001600311700001400327856012300341 1998 eng d00aThe relationship between computer familiarity and performance on computer-based TOEFL test tasks (Research Report 98-08)0 arelationship between computer familiarity and performance on com aPrinceton NJ: Educational Testing Service1 aTaylor, C1 aJamieson, J1 aEignor, D R1 aKirsch, I uhttp://www.iacat.org/content/relationship-between-computer-familiarity-and-performance-computer-based-toefl-test-tasks00464nas a2200109 4500008004100000245009100041210006900132300001200201490000700213100001700220856011700237 1998 eng d00aReviewing and changing answers on computer-adaptive and self-adaptive vocabulary tests0 aReviewing and changing answers on computeradaptive and selfadapt a328-3450 v351 aVispoel, W P uhttp://www.iacat.org/content/reviewing-and-changing-answers-computer-adaptive-and-self-adaptive-vocabulary-tests00559nas a2200109 4500008004100000245008700041210006900128260011900197100001000316700001400326856010900340 1998 eng d00aSimulating nonmodel-fitting responses in a CAT Environment (Research Report 98-10)0 aSimulating nonmodelfitting responses in a CAT Environment Resear aIowa City IA: ACT Inc. (Also presented at National Council on Measurement in Education, 1999: ERIC No. ED 427 042)1 aYi, Q1 aNering, L uhttp://www.iacat.org/content/simulating-nonmodel-fitting-responses-cat-environment-research-report-98-1000654nas a2200109 4500008004100000245012200041210006900163260014400232100001600376700002700392856012500419 1998 eng d00aSimulating the null distribution of person-fit statistics for conventional and adaptive tests (Research Report 98-02)0 aSimulating the null distribution of personfit statistics for con aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/simulating-null-distribution-person-fit-statistics-conventional-and-adaptive-tests-research01298nas a2200157 4500008004100000245007500041210006900116300001000185490000700195520076100202653003400963100001800997700001401015700001701029856009401046 1998 eng d00aSimulating the use of disclosed items in computerized adaptive testing0 aSimulating the use of disclosed items in computerized adaptive t a48-680 v353 aRegular use of questions previously made available to the public (i.e., disclosed items) may provide one way to meet the requirement for large numbers of questions in a continuous testing environment, that is, an environment in which testing is offered at test taker convenience throughout the year rather than on a few prespecified test dates. First it must be shown that such use has effects on test scores small enough to be acceptable. In this study simulations are used to explore the use of disclosed items under a worst-case scenario which assumes that disclosed items are always answered correctly. Some item pool and test designs were identified in which the use of disclosed items produces effects on test scores that may be viewed as negligible.10acomputerized adaptive testing1 aStocking, M L1 aWard, W C1 aPotenza, M T uhttp://www.iacat.org/content/simulating-use-disclosed-items-computerized-adaptive-testing00435nas a2200085 4500008004100000245010200041210006900143100001600212856012100228 1998 eng d00aSome considerations for eliminating biases in ability estimation in computerized adaptive testing0 aSome considerations for eliminating biases in ability estimation1 aSamejima, F uhttp://www.iacat.org/content/some-considerations-eliminating-biases-ability-estimation-computerized-adaptive-testing00493nas a2200097 4500008004100000245013400041210006900175260001500244100001500259856012100274 1998 eng d00aSome item response theory to provide scale scores based on linear combinations of testlet scores, for computerized adaptive tests0 aSome item response theory to provide scale scores based on linea aUrbana, IL1 aThissen, D uhttp://www.iacat.org/content/some-item-response-theory-provide-scale-scores-based-linear-combinations-testlet-scores00455nas a2200121 4500008004100000245007200041210006900113300001200182490000700194100001500201700001900216856009800235 1998 eng d00aSome practical examples of computerized adaptive sequential testing0 aSome practical examples of computerized adaptive sequential test a229-2490 v351 aLuecht, RM1 aNungester, R J uhttp://www.iacat.org/content/some-practical-examples-computerized-adaptive-sequential-testing00422nas a2200109 4500008004100000245006400041210006400105260001500169100002000184700001900204856008900223 1998 eng d00aSome reliability estimators for computerized adaptive tests0 aSome reliability estimators for computerized adaptive tests aUrbana, IL1 aNicewander, W A1 aThomasson, G L uhttp://www.iacat.org/content/some-reliability-estimators-computerized-adaptive-tests00596nas a2200145 4500008004100000020001000041245007300051210006900124260010000193300000700293100001600300700001600316700002300332856009500355 1998 eng d a98-0100aStatistical tests for person misfit in computerized adaptive testing0 aStatistical tests for person misfit in computerized adaptive tes aEnschede, The NetherlandsbFaculty of Educational Science and Technology, Univeersity of Twente a281 aGlas, C A W1 aMeijer, R R1 aKrimpen-Stoop, E M uhttp://www.iacat.org/content/statistical-tests-person-misfit-computerized-adaptive-testing00650nas a2200121 4500008004100000245009700041210006900138260014500207100001600352700001600368700002700384856011700411 1998 eng d00aStatistical tests for person misfit in computerized adaptive testing (Research Report 98-01)0 aStatistical tests for person misfit in computerized adaptive tes aEnschede, The Netherlands : University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://www.iacat.org/content/statistical-tests-person-misfit-computerized-adaptive-testing-research-report-98-0100492nas a2200109 4500008004100000245010500041210006900146300001200215490000700227100002300234856012500257 1998 eng d00aStochastic order in dichotomous item response models for fixed, adaptive, and multidimensional tests0 aStochastic order in dichotomous item response models for fixed a a211-2260 v631 avan der Linden, WJ uhttp://www.iacat.org/content/stochastic-order-dichotomous-item-response-models-fixed-adaptive-and-multidimensional-tests00523nas a2200121 4500008004100000245012000041210006900161300001200230490000600242100001600248700001700264856012000281 1998 eng d00aSwedish Enlistment Battery: Construct validity and latent variable estimation of cognitive abilities by the CAT-SEB0 aSwedish Enlistment Battery Construct validity and latent variabl a107-1140 v61 aMardberg, B1 aCarlstedt, B uhttp://www.iacat.org/content/swedish-enlistment-battery-construct-validity-and-latent-variable-estimation-cognitive00430nas a2200121 4500008004100000245005900041210005900100260001800159100001800177700001300195700001600208856008400224 1998 eng d00aTest development exposure control for adaptive testing0 aTest development exposure control for adaptive testing aSan Diego, CA1 aParshall, C G1 aDavey, T1 aNering, M L uhttp://www.iacat.org/content/test-development-exposure-control-adaptive-testing00557nas a2200145 4500008004100000245010200041210006900143300001000212490000700222100001600229700001600245700001400261700001400275856012200289 1998 eng d00aTesting word knowledge by telephone to estimate general cognitive aptitude using an adaptive test0 aTesting word knowledge by telephone to estimate general cognitiv a91-980 v261 aLegree, P J1 aFischl, M A1 aGade, P A1 aWilson, M uhttp://www.iacat.org/content/testing-word-knowledge-telephone-estimate-general-cognitive-aptitude-using-adaptive-test00584nas a2200121 4500008004100000245014200041210006900183260004700252100001700299700001400316700001400330856011800344 1998 eng d00aThree response types for broadening the conception of mathematical problem solving in computerized-adaptive tests (Research Report 98-45)0 aThree response types for broadening the conception of mathematic aPrinceton NJ : Educational Testing Service1 aBennett, R E1 aMorley, M1 aQuardt, D uhttp://www.iacat.org/content/three-response-types-broadening-conception-mathematical-problem-solving-computerized00677nas a2200121 4500008004100000245012000041210006900161260014400230100002300374700001600397700001800413856012400431 1998 eng d00aUsing response-time constraints to control for differential speededness in adaptive testing (Research Report 98-06)0 aUsing responsetime constraints to control for differential speed aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ1 aScrams, D J1 aSchnipke, D L uhttp://www.iacat.org/content/using-response-time-constraints-control-differential-speededness-adaptive-testing-research00584nas a2200145 4500008004100000245011400041210006900155260001200224100001400236700001700250700001600267700001600283700001900299856012000318 1997 eng d00aThe accuracy of examinee judgments of relative item difficulty: Implication for computerized adaptive testing0 aaccuracy of examinee judgments of relative item difficulty Impli aChicago1 aWise, S L1 aFreeman, S A1 aFinney, S J1 aEnders, C K1 aSeverance, D D uhttp://www.iacat.org/content/accuracy-examinee-judgments-relative-item-difficulty-implication-computerized-adaptive00395nas a2200145 4500008004100000245003300041210003300074300001200107490000700119100001700126700001500143700001600158700001600174856005900190 1997 eng d00aAdapting to adaptive testing0 aAdapting to adaptive testing a171-1850 v501 aOverton, R C1 aHarms, H J1 aTaylor, L R1 aZickar, M J uhttp://www.iacat.org/content/adapting-adaptive-testing00383nas a2200097 4500008004100000245006400041210006400105260001500169100001200184856008900196 1997 eng d00aAdministering and scoring the computerized adaptive testing0 aAdministering and scoring the computerized adaptive testing aChicago IL1 aZara, A uhttp://www.iacat.org/content/administering-and-scoring-computerized-adaptive-testing00382nas a2200097 4500008004100000245006300041210006200104260001500166100001400181856008900195 1997 eng d00aAlternate methods of scoring computer-based adaptive tests0 aAlternate methods of scoring computerbased adaptive tests aChicago IL1 aGreen, BF uhttp://www.iacat.org/content/alternate-methods-scoring-computer-based-adaptive-tests00368nas a2200109 4500008004100000245005300041210005000094300001200144490000700156100001800163856007700181 1997 eng d00aAn alternative method for scoring adaptive tests0 aalternative method for scoring adaptive tests a365-3890 v211 aStocking, M L uhttp://www.iacat.org/content/alternative-method-scoring-adaptive-tests-000525nas a2200097 4500008004100000245009900041210006900140260008500209100001300294856012000307 1997 eng d00aApplications of Bayesian decision theory to sequential mastery testing (Research Report 97-06)0 aApplications of Bayesian decision theory to sequential mastery t aTwente, The Netherlands: Department of Educational Measurement and Data Analysis1 aVos, H J uhttp://www.iacat.org/content/applications-bayesian-decision-theory-sequential-mastery-testing-research-report-97-0600364nas a2200097 4500008004100000245005400041210005400095260002100149100001600170856008000186 1997 eng d00aApplications of multidimensional adaptive testing0 aApplications of multidimensional adaptive testing aMontreal, Canada1 aSegall, D O uhttp://www.iacat.org/content/applications-multidimensional-adaptive-testing00457nas a2200121 4500008004100000245006900041210006700110260001500177100001600192700001600208700001600224856009500240 1997 eng d00aAssessing speededness in variable-length computer-adaptive tests0 aAssessing speededness in variablelength computeradaptive tests aChicago IL1 aBontempo, B1 aJulian, E R1 aGorham, J L uhttp://www.iacat.org/content/assessing-speededness-variable-length-computer-adaptive-tests00430nas a2200097 4500008004100000245008700041210006900128260001500197100001300212856010700225 1997 eng d00aA Bayesian enhancement of Mantel Haenszel DIF analysis for computer adaptive tests0 aBayesian enhancement of Mantel Haenszel DIF analysis for compute aChicago IL1 aZwick, R uhttp://www.iacat.org/content/bayesian-enhancement-mantel-haenszel-dif-analysis-computer-adaptive-tests00521nas a2200121 4500008004100000245010200041210006900143260001800212100001500230700001800245700001600263856012000279 1997 eng d00aCalibration of CAT items administered online for classification: Assumption of local independence0 aCalibration of CAT items administered online for classification  aGatlinburg TN1 aSpray, J A1 aParshall, C G1 aHuang, C -H uhttp://www.iacat.org/content/calibration-cat-items-administered-online-classification-assumption-local-independence00414nas a2200109 4500008004100000245003600041210003500077260009900112100001700211700001600228856006000244 1997 eng d00aCAST 5 for Windows users' guide0 aCAST 5 for Windows users guide aContract No. "MDA903-93-D-0032, DO 0054. Alexandria, VA: Human Resources Research Organization1 aMcBride, J R1 aCooper, R R uhttp://www.iacat.org/content/cast-5-windows-users-guide00535nas a2200121 4500008004100000245004000041210003900081260017700120100001400297700001600311700001700327856006900344 1997 eng d00aCAT-ASVAB cost and benefit analyses0 aCATASVAB cost and benefit analyses aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computer adaptive testing: From inquiry to operation (pp. 227-236). Washington, DC: American Psychological Association.1 aWise, L L1 aCurran, L T1 aMcBride, J R uhttp://www.iacat.org/content/cat-asvab-cost-and-benefit-analyses00500nas a2200097 4500008004100000245004600041210004500087260017900132100001600311856007500327 1997 eng d00aCAT-ASVAB operational test and evaluation0 aCATASVAB operational test and evaluation aW. A. Sands, B. K. Waters, and . R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 199-205). Washington DC: American Psychological Association.1 aMoreno, K E uhttp://www.iacat.org/content/cat-asvab-operational-test-and-evaluation00555nas a2200109 4500008004100000245013000041210006900171260004600240100001800286700001500304856012600319 1997 eng d00aCATSIB: A modified SIBTEST procedure to detect differential item functioning in computerized adaptive tests (Research report)0 aCATSIB A modified SIBTEST procedure to detect differential item  aNewtown, PA: Law School Admission Council1 aNandakumar, R1 aRoussos, L uhttp://www.iacat.org/content/catsib-modified-sibtest-procedure-detect-differential-item-functioning-computerized-adaptive00491nas a2200109 4500008004100000245010400041210006900145100001600214700002000230700001200250856011900262 1997 eng d00aComparability and validity of computerized adaptive testing with the MMPI-2 using a clinical sample0 aComparability and validity of computerized adaptive testing with1 aHandel, R W1 aBen-Porath, Y S1 aWatt, M uhttp://www.iacat.org/content/comparability-and-validity-computerized-adaptive-testing-mmpi-2-using-clinical-sample02915nas a2200133 4500008004100000245016300041210006900204300000800273490000700281520232300288653003402611100001402645856012202659 1997 eng d00aA comparison of maximum likelihood estimation and expected a posteriori estimation in computerized adaptive testing using the generalized partial credit model0 acomparison of maximum likelihood estimation and expected a poste a4530 v583 aA simulation study was conducted to investigate the application of expected a posteriori (EAP) trait estimation in computerized adaptive tests (CAT) based on the generalized partial credit model (Muraki, 1992), and to compare the performance of EAP with maximum likelihood trait estimation (MLE). The performance of EAP was evaluated under different conditions: the number of quadrature points (10, 20, and 30), and the type of prior distribution (normal, uniform, negatively skewed, and positively skewed). The relative performance of the MLE and EAP estimation methods were assessed under two distributional forms of the latent trait, one normal and the other negatively skewed. Also, both the known item parameters and estimated item parameters were employed in the simulation study. Descriptive statistics, correlations, scattergrams, accuracy indices, and audit trails were used to compare the different methods of trait estimation in CAT. The results showed that, regardless of the latent trait distribution, MLE and EAP with a normal prior, a uniform prior, or the prior that matches the latent trait distribution using either 20 or 30 quadrature points provided relatively accurate estimation in CAT based on the generalized partial credit model. However, EAP using only 10 quadrature points did not work well in the generalized partial credit CAT. Also, the study found that increasing the number of quadrature points from 20 to 30 did not increase the accuracy of EAP estimation. Therefore, it appears 20 or more quadrature points are sufficient for accurate EAP estimation. The results also showed that EAP with a negatively skewed prior and positively skewed prior performed poorly for the normal data set, and EAP with positively skewed prior did not provide accurate estimates for the negatively skewed data set. Furthermore, trait estimation in CAT using estimated item parameters produced results similar to those obtained using known item parameters. In general, when at least 20 quadrature points are used, EAP estimation with a normal prior, a uniform prior or the prior that matches the latent trait distribution appears to be a good alternative to MLE in the application of polytomous CAT based on the generalized partial credit model. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aChen, S-K uhttp://www.iacat.org/content/comparison-maximum-likelihood-estimation-and-expected-posteriori-estimation-computerized00451nas a2200109 4500008004100000245008100041210006900122260001600191100001800207700001500225856010100240 1997 eng d00aA comparison of testlet-based test designs for computerized adaptive testing0 acomparison of testletbased test designs for computerized adaptiv aChicago, IL1 aSchnipke, D L1 aReese, L M uhttp://www.iacat.org/content/comparison-testlet-based-test-designs-computerized-adaptive-testing00402nas a2200109 4500008004100000245006200041210006200103260001500165100001400180700001500194856008300209 1997 eng d00aComputer assembly of tests so that content reigns supreme0 aComputer assembly of tests so that content reigns supreme aChicago IL1 aCase, S M1 aLuecht, RM uhttp://www.iacat.org/content/computer-assembly-tests-so-content-reigns-supreme00435nas a2200097 4500008004100000245008900041210006900130490001300199100001600212856010900228 1997 eng d00aComputer-adaptive testing of listening comprehension: A blueprint of CAT Development0 aComputeradaptive testing of listening comprehension A blueprint 0 vno. 10. 1 aDunkel, P A uhttp://www.iacat.org/content/computer-adaptive-testing-listening-comprehension-blueprint-cat-development00567nas a2200133 4500008004100000245013800041210006900179300001000248490000700258100001700265700001200282700001500294856012400309 1997 eng d00aComputerized adaptive and fixed-item testing of music listening skill: A comparison of efficiency, precision, and concurrent validity0 aComputerized adaptive and fixeditem testing of music listening s a43-630 v341 aVispoel, W P1 aWang, T1 aBleiler, T uhttp://www.iacat.org/content/computerized-adaptive-and-fixed-item-testing-music-listening-skill-comparison-efficiency-000533nas a2200121 4500008004100000245013800041210006900179300001000248490000700258100001200265700001200277856012200289 1997 eng d00aComputerized adaptive and fixed-item testing of music listening skill: A comparison of efficiency, precision, and concurrent validity0 aComputerized adaptive and fixeditem testing of music listening s a43-630 v341 aVispoel1 aWang, T uhttp://www.iacat.org/content/computerized-adaptive-and-fixed-item-testing-music-listening-skill-comparison-efficiency01686nam a2200145 4500008004100000245006100041210006000102260006200162520115300224653003401377100001501411700001601426700001701442856008101459 1997 eng d00aComputerized adaptive testing: From inquiry to operation0 aComputerized adaptive testing From inquiry to operation aWashington, D.C., USAbAmerican Psychological Association3 a(from the cover) This book traces the development of computerized adaptive testing (CAT) from its origins in the 1960s to its integration with the Armed Services Vocational Aptitude Battery (ASVAB) in the 1990s. A paper-and-pencil version of the battery (P&P-ASVAB) has been used by the Defense Department since the 1970s to measure the abilities of applicants for military service. The test scores are used both for initial qualification and for classification into entry-level training opportunities. /// This volume provides the developmental history of the CAT-ASVAB through its various stages in the Joint-Service arena. Although the majority of the book concerns the myriad technical issues that were identified and resolved, information is provided on various political and funding support challenges that were successfully overcome in developing, testing, and implementing the battery into one of the nation's largest testing programs. The book provides useful information to professionals in the testing community and everyone interested in personnel assessment and evaluation. (PsycINFO Database Record (c) 2004 APA, all rights reserved).10acomputerized adaptive testing1 aSands, W A1 aWaters, B K1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-inquiry-operation02024nas a2200289 4500008004100000245012700041210006900168300001300237490000800250520105800258653003401316653003301350653002301383653001501406653001001421653002601431653001001457653001501467653001801482653003101500100001501531700001601546700001401562700001701576700001601593856012501609 1997 eng d00aA computerized adaptive testing system for speech discrimination measurement: The Speech Sound Pattern Discrimination Test0 acomputerized adaptive testing system for speech discrimination m a2289-2980 v1013 aA computerized, adaptive test-delivery system for the measurement of speech discrimination, the Speech Sound Pattern Discrimination Test, is described and evaluated. Using a modified discrimination task, the testing system draws on a pool of 130 items spanning a broad range of difficulty to estimate an examinee's location along an underlying continuum of speech processing ability, yet does not require the examinee to possess a high level of English language proficiency. The system is driven by a mathematical measurement model which selects only test items which are appropriate in difficulty level for a given examinee, thereby individualizing the testing experience. Test items were administered to a sample of young deaf adults, and the adaptive testing system evaluated in terms of respondents' sensory and perceptual capabilities, acoustic and phonetic dimensions of speech, and theories of speech perception. Data obtained in this study support the validity, reliability, and efficiency of this test as a measure of speech processing ability.10a*Diagnosis, Computer-Assisted10a*Speech Discrimination Tests10a*Speech Perception10aAdolescent10aAdult10aAudiometry, Pure-Tone10aHuman10aMiddle Age10aPsychometrics10aReproducibility of Results1 aBochner, J1 aGarrison, W1 aPalmer, L1 aMacKenzie, D1 aBraveman, A uhttp://www.iacat.org/content/computerized-adaptive-testing-system-speech-discrimination-measurement-speech-sound-pattern00352nas a2200085 4500008004100000245006100041210006100102100001700163856008600180 1997 eng d00aComputerized adaptive testing through the World Wide Web0 aComputerized adaptive testing through the World Wide Web1 aShermis, M D uhttp://www.iacat.org/content/computerized-adaptive-testing-through-world-wide-web00468nas a2200133 4500008004100000245006100041210006100102260002400163100001700187700001500204700001300219700001400232856008800246 1997 eng d00aComputerized adaptive testing through the World Wide Web0 aComputerized adaptive testing through the World Wide Web a(ERIC No. ED414536)1 aShermis, M D1 aMzumara, H1 aBrown, M1 aLillig, C uhttp://www.iacat.org/content/computerized-adaptive-testing-through-world-wide-web-000548nas a2200097 4500008003900000245009000039210006900129260012700198100001400325856011100339 1997 d00aComputerized adaptive testing using the partial credit model for attitude measurement0 aComputerized adaptive testing using the partial credit model for aM. Wilson, G. Engelhard Jr and K. Draney (Eds.), Objective measurement: Theory into practice, volume 4. Norwood NJ: Ablex.1 aBaek, S G uhttp://www.iacat.org/content/computerized-adaptive-testing-using-partial-credit-model-attitude-measurement00500nas a2200121 4500008004100000245008900041210006900130260001500199100001700214700001500231700001500246856011700261 1997 eng d00aControlling test and computer anxiety: Test performance under CAT and SAT conditions0 aControlling test and computer anxiety Test performance under CAT aChicago IL1 aShermis, M D1 aMzumara, H1 aBublitz, S uhttp://www.iacat.org/content/controlling-test-and-computer-anxiety-test-performance-under-cat-and-sat-conditions00493nas a2200109 4500008004100000245003400041210003400075260017900109100001600288700001600304856006300320 1997 eng d00aCurrent and future challenges0 aCurrent and future challenges aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.). Computerized adaptive testing: From inquiry to operation (pp 257-269). Washington DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E uhttp://www.iacat.org/content/current-and-future-challenges00353nas a2200097 4500008004100000245005300041210005300094260001600147100001500163856007700178 1997 eng d00aDetecting misbehaving items in a CAT environment0 aDetecting misbehaving items in a CAT environment aChicago, IL1 aSwygert, K uhttp://www.iacat.org/content/detecting-misbehaving-items-cat-environment00353nas a2200097 4500008004100000245005100041210005100092260001500143100002300158856007400181 1997 eng d00aDetection of aberrant response patterns in CAT0 aDetection of aberrant response patterns in CAT aChicago IL1 avan der Linden, WJ uhttp://www.iacat.org/content/detection-aberrant-response-patterns-cat00475nas a2200133 4500008004100000245007300041210006900114300001000183490000700193100001300200700001100213700001800224856009900242 1997 eng d00aDeveloping and scoring an innovative computerized writing assessment0 aDeveloping and scoring an innovative computerized writing assess a21-410 v341 aDavey, T1 aGodwin1 aMittelholz, D uhttp://www.iacat.org/content/developing-and-scoring-innovative-computerized-writing-assessment00484nas a2200121 4500008004100000245008900041210006900130300000900199490000700208100001800215700001800233856011100251 1997 eng d00aDiagnostic adaptive testing: Effects of remedial instruction as empirical validation0 aDiagnostic adaptive testing Effects of remedial instruction as e a3-200 v341 aTatsuoka, K K1 aTatsuoka, M M uhttp://www.iacat.org/content/diagnostic-adaptive-testing-effects-remedial-instruction-empirical-validation01733nas a2200169 4500008004100000245009900041210006900140300001200209490000700221520112300228653002101351653003001372653000801402653002301410100001601433856011401449 1997 eng d00aThe distribution of indexes of person fit within the computerized adaptive testing environment0 adistribution of indexes of person fit within the computerized ad a115-1270 v213 aThe extent to which a trait estimate represents the underlying latent trait of interest can be estimated by using indexes of person fit. Several statistical methods for indexing person fit have been proposed to identify nonmodel-fitting response vectors. These person-fit indexes have generally been found to follow a standard normal distribution for conventionally administered tests. The present investigation found that within the context of computerized adaptive testing (CAT) these indexes tended not to follow a standard normal distribution. As the item pool became less discriminating, as the CAT termination criterion became less stringent, and as the number of items in the pool decreased, the distributions of the indexes approached a standard normal distribution. It was determined that under these conditions the indexes' distributions approached standard normal distributions because more items were being administered. However, even when over 50 items were administered in a CAT the indexes were distributed in a fashion that was different from what was expected. (PsycINFO Database Record (c) 2006 APA )10aAdaptive Testing10aComputer Assisted Testing10aFit10aPerson Environment1 aNering, M L uhttp://www.iacat.org/content/distribution-indexes-person-fit-within-computerized-adaptive-testing-environment00495nas a2200109 4500008004100000245012500041210006900166300001200235490000700247100001300254856011800267 1997 eng d00aThe effect of adaptive administration on the variability of the Mantel-Haenszel measure of differential item functioning0 aeffect of adaptive administration on the variability of the Mant a412-4210 v571 aZwick, R uhttp://www.iacat.org/content/effect-adaptive-administration-variability-mantel-haenszel-measure-differential-item01799nas a2200169 4500008004100000245014100041210006900182300001200251490000700263520113700270653003401407100001401441700001301455700002101468700001401489856012601503 1997 eng d00aThe effect of population distribution and method of theta estimation on computerized adaptive testing (CAT) using the rating scale model0 aeffect of population distribution and method of theta estimation a422-4390 v573 aInvestigated the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori estimation (EAP) in a simulation study of computerized adaptive testing (CAT) based on D. Andrich's (1978) rating scale model. Comparisons were made among MLE and EAP with a normal prior distribution and EAP with a uniform prior distribution within 2 data sets: one generated using a normal trait distribution and the other using a negatively skewed trait distribution. Descriptive statistics, correlations, scattergrams, and accuracy indices were used to compare the different methods of trait estimation. The EAP estimation with a normal prior or uniform prior yielded results similar to those obtained with MLE, even though the prior did not match the underlying trait distribution. An additional simulation study based on real data suggested that more work is needed to determine the optimal number of quadrature points for EAP in CAT based on the rating scale model. The choice between MLE and EAP for particular measurement situations is discussed. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aChen, S-K1 aHou, L Y1 aFitzpatrick, S J1 aDodd, B G uhttp://www.iacat.org/content/effect-population-distribution-and-method-theta-estimation-computerized-adaptive-testing-cat00596nas a2200145 4500008004100000245014200041210006900183300001200252490000700264100001200271700001100283700002100294700001200315856012300327 1997 eng d00aThe effect of population distribution and methods of theta estimation on computerized adaptive testing (CAT) using the rating scale model0 aeffect of population distribution and methods of theta estimatio a422-4390 v571 aChen, S1 aHou, L1 aFitzpatrick, S J1 aDodd, B uhttp://www.iacat.org/content/effect-population-distribution-and-methods-theta-estimation-computerized-adaptive-testing00406nas a2200097 4500008004100000245007400041210006900115260001500184100001600199856009300215 1997 eng d00aThe effects of motivation on equating adaptive and conventional tests0 aeffects of motivation on equating adaptive and conventional test aChicago IL1 aSegall, D O uhttp://www.iacat.org/content/effects-motivation-equating-adaptive-and-conventional-tests00440nas a2200097 4500008004100000245002700041210002600068260018000094100001600274856005200290 1997 eng d00aEquating the CAT-ASVAB0 aEquating the CATASVAB aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 181-198). Washington DC: American Psychological Association.1 aSegall, D O uhttp://www.iacat.org/content/equating-cat-asvab00402nas a2200097 4500008004100000245007200041210006900113260001200182100001200194856009800206 1997 eng d00aEssentially unbiased EAP estimates in computerized adaptive testing0 aEssentially unbiased EAP estimates in computerized adaptive test aChicago1 aWang, T uhttp://www.iacat.org/content/essentially-unbiased-eap-estimates-computerized-adaptive-testing00578nas a2200133 4500008003900000245013100039210006900170100001700239700001500256700001700271700001400288700001700302856012500319 1997 d00aEvaluating an automatically scorable, open-ended response type for measuring mathematical reasoning in computer-adaptive tests0 aEvaluating an automatically scorable openended response type for1 aBennett, R E1 aSteffen, M1 aSingley, M K1 aMorley, M1 aJacquemin, D uhttp://www.iacat.org/content/evaluating-automatically-scorable-open-ended-response-type-measuring-mathematical-reasoning00480nas a2200109 4500008004100000245010300041210006900144260001200213100001200225700001500237856011800252 1997 eng d00aEvaluating comparability in computerized adaptive testing: A theoretical framework with an example0 aEvaluating comparability in computerized adaptive testing A theo aChicago1 aWang, T1 aKolen, M J uhttp://www.iacat.org/content/evaluating-comparability-computerized-adaptive-testing-theoretical-framework-example00620nas a2200121 4500008004100000245007200041210006900113260017000182100001600352700001600368700001600384856009800400 1997 eng d00aEvaluating item calibration medium in computerized adaptive testing0 aEvaluating item calibration medium in computerized adaptive test aW.A. Sands, B.K. Waters and J.R. McBride, Computerized adaptive testing: From inquiry to operation (pp. 161-168). Washington, DC: American Psychological Association.1 aHetter, R D1 aSegall, D O1 aBloxom, B M uhttp://www.iacat.org/content/evaluating-item-calibration-medium-computerized-adaptive-testing00275nas a2200097 4500008004100000245002700041210002700068260001500095100001400110856005300124 1997 eng d00aExaminee issues in CAT0 aExaminee issues in CAT aChicago IL1 aWise, S L uhttp://www.iacat.org/content/examinee-issues-cat00390nas a2200121 4500008004100000245005000041210005000091300001000141490000600151100001700157700001800174856007600192 1997 eng d00aFlawed items in computerized adaptive testing0 aFlawed items in computerized adaptive testing a79-960 v41 aPotenza, M T1 aStocking, M L uhttp://www.iacat.org/content/flawed-items-computerized-adaptive-testing00391nas a2200097 4500008004100000245005600041210005600097260004300153100001500196856008200211 1997 eng d00aGetting more precision on computer adaptive testing0 aGetting more precision on computer adaptive testing aUniversity of Tennessee, Knoxville, TN1 aKrass, I A uhttp://www.iacat.org/content/getting-more-precision-computer-adaptive-testing00460nas a2200097 4500008004100000245009900041210006900140260001500209100001900224856011900243 1997 eng d00aThe goal of equity within and between computerized adaptive tests and paper and pencil forms. 0 agoal of equity within and between computerized adaptive tests an aChicago IL1 aThomasson, G L uhttp://www.iacat.org/content/goal-equity-within-and-between-computerized-adaptive-tests-and-paper-and-pencil-forms02398nas a2200253 4500008004100000020002200041245012400063210006900187250001500256260000800271300001200279490000600291520152400297653001901821653003001840653002101870653003301891653002401924653001101948653002701959100001701986700001502003856012602018 1997 eng d a0962-9343 (Print)00aHealth status assessment for the twenty-first century: item response theory, item banking and computer adaptive testing0 aHealth status assessment for the twentyfirst century item respon a1997/08/01 cAug a595-6000 v63 aHealth status assessment is frequently used to evaluate the combined impact of human immunodeficiency virus (HIV) disease and its treatment on functioning and well-being from the patient's perspective. No single health status measure can efficiently cover the range of problems in functioning and well-being experienced across HIV disease stages. Item response theory (IRT), item banking and computer adaptive testing (CAT) provide a solution to measuring health-related quality of life (HRQoL) across different stages of HIV disease. IRT allows us to examine the response characteristics of individual items and the relationship between responses to individual items and the responses to each other item in a domain. With information on the response characteristics of a large number of items covering a HRQoL domain (e.g. physical function, and psychological well-being), and information on the interrelationships between all pairs of these items and the total scale, we can construct more efficient scales. Item banks consist of large sets of questions representing various levels of a HRQoL domain that can be used to develop brief, efficient scales for measuring the domain. CAT is the application of IRT and item banks to the tailored assessment of HRQoL domains specific to individual patients. Given the results of IRT analyses and computer-assisted test administration, more efficient and brief scales can be used to measure multiple domains of HRQoL for clinical trials and longitudinal observational studies.10a*Health Status10a*HIV Infections/diagnosis10a*Quality of Life10aDiagnosis, Computer-Assisted10aDisease Progression10aHumans10aPsychometrics/*methods1 aRevicki, D A1 aCella, D F uhttp://www.iacat.org/content/health-status-assessment-twenty-first-century-item-response-theory-item-banking-and-computer00470nas a2200121 4500008004100000245006900041210006900110260002500179100001700204700001800221700001400239856009500253 1997 eng d00aIdentifying similar item content clusters on multiple test forms0 aIdentifying similar item content clusters on multiple test forms aGatlinburg, TN, June1 aReckase, M D1 aThompson, T D1 aNering, M uhttp://www.iacat.org/content/identifying-similar-item-content-clusters-multiple-test-forms00463nas a2200097 4500008004100000245009100041210006900132260003700201100001700238856011000255 1997 eng d00aImproving the quality of music aptitude tests through adaptive administration of items0 aImproving the quality of music aptitude tests through adaptive a aUniversity of Iowa, Iowa City IA1 aVispoel, W P uhttp://www.iacat.org/content/improving-quality-music-aptitude-tests-through-adaptive-administration-items00536nas a2200121 4500008004100000245009400041210006900135260004600204100001500250700001800265700001600283856011500299 1997 eng d00aIncorporating content constraints into a multi-stage adaptive testlet design: LSAC report0 aIncorporating content constraints into a multistage adaptive tes aNewtown, PA: Law School Admission Council1 aReese, L M1 aSchnipke, D L1 aLuebke, S W uhttp://www.iacat.org/content/incorporating-content-constraints-multi-stage-adaptive-testlet-design-lsac-report00426nas a2200109 4500008004100000245007200041210006900113260001200182100001300194700001300207856009600220 1997 eng d00aIncorporating decision consistency into Bayesian sequential testing0 aIncorporating decision consistency into Bayesian sequential test aChicago1 aSmith, R1 aLewis, C uhttp://www.iacat.org/content/incorporating-decision-consistency-bayesian-sequential-testing00512nas a2200145 4500008004100000245008100041210006900122300001200191490000700203100001500210700001400225700001200239700001600251856009900267 1997 eng d00aAn investigation of self-adapted testing in a Spanish high school population0 ainvestigation of selfadapted testing in a Spanish high school po a210-2210 v571 aPonsoda, V1 aWise, S L1 aOlea, J1 aRevuelta, J uhttp://www.iacat.org/content/investigation-self-adapted-testing-spanish-high-school-population00922nas a2200145 4500008004100000245003900041210003800080260006100118300001200179520047000191100001600661700001700677700001700694856006500711 1997 eng d00aItem exposure control in CAT-ASVAB0 aItem exposure control in CATASVAB aWashington D.C., USAbAmerican Psychological Association a141-1443 aDescribes the method used to control item exposure in computerized adaptive testing-Armed Services Vocational Aptitude Battery (CAT-ASVAB). The method described was developed specifically to ensure that CAT-ASVAB items were expose no more often than the items in the printers ASVAB's alternate forms, ensuring that CAT ASVAB is nor more vulnerable than printed ASVAB forms to comprise from item exposure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)1 aHetter, R D1 aSympson, J B1 aMcBride, J R uhttp://www.iacat.org/content/item-exposure-control-cat-asvab00543nas a2200121 4500008004100000245004100041210004100082260018000123100001600303700001600319700001600335856007000351 1997 eng d00aItem pool development and evaluation0 aItem pool development and evaluation aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 117-130). Washington DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aHetter, D H uhttp://www.iacat.org/content/item-pool-development-and-evaluation00328nas a2200097 4500008004100000245004200041210004200083260001500125100001900140856007100159 1997 eng d00aItem pool development and maintenance0 aItem pool development and maintenance aChicago IL1 aKingsbury, G G uhttp://www.iacat.org/content/item-pool-development-and-maintenance00542nas a2200109 4500008004100000245011600041210006900157260004600226100001600272700001800288856012600306 1997 eng d00aLinking scores for computer-adaptive and paper-and-pencil administrations of the SAT (Research Report No 97-12)0 aLinking scores for computeradaptive and paperandpencil administr aPrinceton NJ: Educational Testing Service1 aLawrence, I1 aFeigenbaum, M uhttp://www.iacat.org/content/linking-scores-computer-adaptive-and-paper-and-pencil-administrations-sat-research-report-no00412nas a2200121 4500008004100000245005400041210005400095260001500149100001600164700001600180700001800196856007600214 1997 eng d00aMaintaining a CAT item pool with operational data0 aMaintaining a CAT item pool with operational data aChicago IL1 aLevine, M L1 aSegall, D O1 aWilliams, B A uhttp://www.iacat.org/content/maintaining-cat-item-pool-operational-data00449nas a2200109 4500008004100000245008000041210006900121260001600190100001700206700001500223856010100238 1997 eng d00aMaintaining item and test security in a CAT environment: A simulation study0 aMaintaining item and test security in a CAT environment A simula aChicago IL)1 aPatsula, L N1 aSteffen, M uhttp://www.iacat.org/content/maintaining-item-and-test-security-cat-environment-simulation-study00410nas a2200097 4500008004100000245007300041210006900114260001500183100001500198856009900213 1997 eng d00aMathematical programming approaches to computerized adaptive testing0 aMathematical programming approaches to computerized adaptive tes aChicago IL1 aJones, D H uhttp://www.iacat.org/content/mathematical-programming-approaches-computerized-adaptive-testing00545nas a2200097 4500008004100000245011500041210006900156260008500225100001300310856012400323 1997 eng d00aA minimax sequential procedure in the context of computerized adaptive mastery testing (Research Report 97-07)0 aminimax sequential procedure in the context of computerized adap aTwente, The Netherlands: Department of Educational Measurement and Data Analysis1 aVos, H J uhttp://www.iacat.org/content/minimax-sequential-procedure-context-computerized-adaptive-mastery-testing-research-report00630nas a2200109 4500008004100000245011500041210006900156260013700225100001700362700001600379856012500395 1997 eng d00aModification of the Computerized Adaptive Screening Test (CAST) for use by recruiters in all military services0 aModification of the Computerized Adaptive Screening Test CAST fo aFinal Technical Report FR-WATSD-97-24, Contract No. MDA903-93-D-0032, DO 0054. Alexandria VA: Human Resources Research Organization.1 aMcBride, J R1 aCooper, R R uhttp://www.iacat.org/content/modification-computerized-adaptive-screening-test-cast-use-recruiters-all-military-services00564nas a2200097 4500008004100000245010200041210006900143260010900212100002300321856012200344 1997 eng d00aMultidimensional adaptive testing with a minimum error-variance criterion (Research Report 97-03)0 aMultidimensional adaptive testing with a minimum errorvariance c aEnschede, The Netherlands: University of Twente, Department of Educational Measurement and Data Analysis1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-minimum-error-variance-criterion-research-report-97-0300423nas a2200097 4500008004100000245007800041210006900119260001200188100002300200856010200223 1997 eng d00aMultidimensional adaptive testing with a minimum error-variance criterion0 aMultidimensional adaptive testing with a minimum errorvariance c aChicago1 avan der Linden, WJ uhttp://www.iacat.org/content/multidimensional-adaptive-testing-minimum-error-variance-criterion-000322nas a2200097 4500008004100000245004300041210004200084100001900126700001200145856006700157 1997 eng d00aMulti-stage CAT with stratified design0 aMultistage CAT with stratified design1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/multi-stage-cat-stratified-design00487nas a2200097 4500008004100000245012300041210006900164100001900233700001200252856012500264 1997 eng d00aNonlinear sequential designs for logistic item response theory models with applications to computerized adaptive tests0 aNonlinear sequential designs for logistic item response theory m1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/nonlinear-sequential-designs-logistic-item-response-theory-models-applications-computerized01318nas a2200265 4500008004100000245005500041210005400096300001200150490000600162520053000168653003800698653002000736653001400756653003500770653003100805653001100836653001900847653001800866653002800884100001300912700001500925700001700940700001400957856008100971 1997 eng d00aOn-line performance assessment using rating scales0 aOnline performance assessment using rating scales a173-1910 v13 aThe purpose of this paper is to report on the development of the on-line performance assessment instrument--the Assessment of Motor and Process Skills (AMPS). Issues that will be addressed in the paper include: (a) the establishment of the scoring rubric and its implementation in an extended Rasch model, (b) training of raters, (c) validation of the scoring rubric and procedures for monitoring the internal consistency of raters, and (d) technological implementation of the assessment instrument in a computerized program.10a*Outcome Assessment (Health Care)10a*Rehabilitation10a*Software10a*Task Performance and Analysis10aActivities of Daily Living10aHumans10aMicrocomputers10aPsychometrics10aPsychomotor Performance1 aStahl, J1 aShumway, R1 aBergstrom, B1 aFisher, A uhttp://www.iacat.org/content/line-performance-assessment-using-rating-scales00432nam a2200097 4500008004100000245005800041210005800099260007600157100001700233856008400250 1997 eng d00aOptimization methods in computerized adaptive testing0 aOptimization methods in computerized adaptive testing aUnpublished doctoral dissertation, Rutgers University, New Brunswick NJ1 aCordova, M J uhttp://www.iacat.org/content/optimization-methods-computerized-adaptive-testing00339nas a2200097 4500008004100000245005000041210005000091260001500141100001400156856007100170 1997 eng d00aOverview of practical issues in a CAT program0 aOverview of practical issues in a CAT program aChicago IL1 aWise, S L uhttp://www.iacat.org/content/overview-practical-issues-cat-program00329nas a2200097 4500008004100000245004800041210004500089260001500134100001500149856006700164 1997 eng d00aAn overview of the LSAC CAT research agenda0 aoverview of the LSAC CAT research agenda aChicago IL1 aPashley, P uhttp://www.iacat.org/content/overview-lsac-cat-research-agenda00393nas a2200109 4500008004100000245005700041210005700098260001500155100001500170700001900185856007900204 1997 eng d00aOverview of the USMLE Step 2 computerized field test0 aOverview of the USMLE Step 2 computerized field test aChicago IL1 aLuecht, RM1 aNungester, R J uhttp://www.iacat.org/content/overview-usmle-step-2-computerized-field-test00514nas a2200109 4500008004100000245004600041210004600087260016400133100001600297700001600313856007500329 1997 eng d00aPolicy and program management perspective0 aPolicy and program management perspective aW.A. Sands, B.K. Waters, and J.R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation. Washington, DC: American Psychological Association.1 aMartin, C J1 aHoshaw, C R uhttp://www.iacat.org/content/policy-and-program-management-perspective00664nas a2200121 4500008004100000245009200041210006900133260017800202100001700380700001600397700001600413856011300429 1997 eng d00aPreliminary psychometric research for CAT-ASVAB: Selecting an adaptive testing strategy0 aPreliminary psychometric research for CATASVAB Selecting an adap aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 83-95). Washington DC: American Psychological Association.1 aMcBride, J R1 aWetzel, C D1 aHetter, R D uhttp://www.iacat.org/content/preliminary-psychometric-research-cat-asvab-selecting-adaptive-testing-strategy00335nas a2200097 4500008004100000245005000041210005000091260001500141100001300156856006800169 1997 eng d00aProtecting the integrity of the CAT item pool0 aProtecting the integrity of the CAT item pool aChicago IL1 aWay, W D uhttp://www.iacat.org/content/protecting-integrity-cat-item-pool00459nas a2200109 4500008004100000245008700041210006900128260001500197100001400212700001500226856010800241 1997 eng d00aPsychometric mode effects and fit issues with respect to item difficulty estimates0 aPsychometric mode effects and fit issues with respect to item di aChicago IL1 aHadidi, A1 aLuecht, RM uhttp://www.iacat.org/content/psychometric-mode-effects-and-fit-issues-respect-item-difficulty-estimates00613nas a2200133 4500008004100000245005600041210005500097260018200152100001600334700001600350700001600366700001600382856008100398 1997 eng d00aPsychometric procedures for administering CAT-ASVAB0 aPsychometric procedures for administering CATASVAB aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 131-140). Washington D.C.: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aBloxom, B M1 aHetter, R D uhttp://www.iacat.org/content/psychometric-procedures-administering-cat-asvab00426nas a2200121 4500008004100000245005900041210005900100260001800159100001300177700001400190700001600204856008400220 1997 eng d00aRealistic simulation procedures for item response data0 aRealistic simulation procedures for item response data aGatlinburg TN1 aDavey, T1 aNering, M1 aThompson, T uhttp://www.iacat.org/content/realistic-simulation-procedures-item-response-data00607nas a2200145 4500008004100000245012900041210006900170260001500239100002000254700002000274700001400294700001500308700001700323856012100340 1997 eng d00aRelationship of response latency to test design, examinee ability, and item difficulty in computer-based test administration0 aRelationship of response latency to test design examinee ability aChicago IL1 aSwanson, D., B.1 aFeatherman, C M1 aCase, A M1 aLuecht, RM1 aNungester, R uhttp://www.iacat.org/content/relationship-response-latency-test-design-examinee-ability-and-item-difficulty-computer00544nas a2200109 4500008004100000245005200041210005100093260018000144100001600324700001600340856007800356 1997 eng d00aReliability and construct validity of CAT-ASVAB0 aReliability and construct validity of CATASVAB aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.). Computerized adaptive testing: From inquiry to operation (pp. 169-179). Washington DC: American Psychological Association.1 aMoreno, K E1 aSegall, O D uhttp://www.iacat.org/content/reliability-and-construct-validity-cat-asvab01814nas a2200169 4500008004100000245005300041210005300094250001000147260006000157300001000217520125400227653003401481100001701515700001601532700001701548856007901565 1997 eng d00aResearch antecedents of applied adaptive testing0 aResearch antecedents of applied adaptive testing axviii aWashington D.C. USAbAmerican Psychological Association a47-573 a(from the chapter) This chapter sets the stage for the entire computerized adaptive testing Armed Services Vocational Aptitude Battery (CAT-ASVAB) development program by describing the state of the art immediately preceding its inception. By the mid-l970s, a great deal of research had been conducted that provided the technical underpinnings needed to develop adaptive tests, but little research had been done to corroborate empirically the promising results of theoretical analyses and computer simulation studies. In this chapter, the author summarizes much of the important theoretical and simulation research prior to 1977. In doing so, he describes a variety of approaches to adaptive testing, and shows that while many methods for adaptive testing had been proposed, few practical attempts had been made to implement it. Furthermore, the few instances of adaptive testing were based primarily on traditional test theory, and were developed in laboratory settings for purposes of basic research. The most promising approaches, those based on item response theory and evaluated analytically or by means of computer simulations, remained to be proven in the crucible of live testing. (PsycINFO Database Record (c) 2004 APA, all rights reserved).10acomputerized adaptive testing1 aMcBride, J R1 aWaters, B K1 aMcBride, J R uhttp://www.iacat.org/content/research-antecedents-applied-adaptive-testing01406nas a2200133 4500008004100000245008900041210006900130300001200199490000700211520089300218653003401111100001801145856010901163 1997 eng d00aRevising item responses in computerized adaptive tests: A comparison of three models0 aRevising item responses in computerized adaptive tests A compari a129-1420 v213 aInterest in the application of large-scale computerized adaptive testing has focused attention on issues that arise when theoretical advances are made operational. One such issue is that of the order in which exaniinees address questions within a test or separately timed test section. In linear testing, this order is entirely under the control of the examinee, who can look ahead at questions and return and revise answers to questions. Using simulation, this study investigated three models that permit restricted examinee control over revising previous answers in the context of adaptive testing. Even under a worstcase model of examinee revision behavior, two of the models of permitting item revisions worked well in preserving test fairness and accuracy. One model studied may also preserve some cognitive processing styles developed by examinees for a linear testing environment. 10acomputerized adaptive testing1 aStocking, M L uhttp://www.iacat.org/content/revising-item-responses-computerized-adaptive-tests-comparison-three-models00411nas a2200133 4500008004100000245005400041210004900095300001000144490000700154100001400161700001400175700001500189856007300204 1997 eng d00aThe role of item feedback in self-adapted testing0 arole of item feedback in selfadapted testing a85-980 v571 aRoos, L L1 aWise, S L1 aPlake, B S uhttp://www.iacat.org/content/role-item-feedback-self-adapted-testing01522nas a2200121 4500008004100000245008800041210006900129300001100198490001000209520105600219100001501275856011001290 1997 eng d00aSelf-adapted testing: Improving performance by modifying tests instead of examinees0 aSelfadapted testing Improving performance by modifying tests ins a83-1040 v10(1)3 aThis paper describes self-adapted testing and some of the evidence concerning its effects, presents possible theoretical explanations for those effects, and discusses some of the practical concerns regarding self-adapted testing. Self-adapted testing is a variant of computerized adapted testing in which the examine makes dynamic choices about the difficulty of the items he or she attempts. Self-adapted testing generates scores that are, in constrast to computerized adapted test and fixed-item tests, uncorrelated with a measure of trait test anxiety. This lack of correlation with an irrelevant attribute of the examine is evidence of an improvement in the construct validity of the scores. This improvement comes at the cost of a decrease in testing efficiency. The interaction between test anxiety and test administration mode is more consistent with an interference theory of test anxiety than a deficit theory. Some of the practical concerns regarding self-adapted testing can be ruled out logically, but others await empirical investigation.1 aRocklin, T uhttp://www.iacat.org/content/self-adapted-testing-improving-performance-modifying-tests-instead-examinees00542nas a2200121 4500008004100000245009900041210006900140260004600209100001800255700001400273700001700287856011600304 1997 eng d00aSimulating the use of disclosed items in computerized adaptive testing (Research Report 97-10)0 aSimulating the use of disclosed items in computerized adaptive t aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aWard, W C1 aPotenza, M T uhttp://www.iacat.org/content/simulating-use-disclosed-items-computerized-adaptive-testing-research-report-97-1000384nas a2200121 4500008004100000245004400041210004400085260001800129100001400147700001800161700001300179856007000192 1997 eng d00aSimulation of realistic ability vectors0 aSimulation of realistic ability vectors aGatlinburg TN1 aNering, M1 aThompson, T D1 aDavey, T uhttp://www.iacat.org/content/simulation-realistic-ability-vectors00547nas a2200121 4500008004100000245013100041210006900172260001500241100001400256700001500270700001700285856012300302 1997 eng d00aA simulation study of the use of the Mantel-Haenszel and logistic regression procedures for assessing DIF in a CAT environment0 asimulation study of the use of the MantelHaenszel and logistic r aChicago IL1 aRoss, L P1 aNandakumar1 aClauser, B E uhttp://www.iacat.org/content/simulation-study-use-mantel-haenszel-and-logistic-regression-procedures-assessing-dif-cat00412nas a2200121 4500008004100000245005800041210005800099300001200157490000700169100001100176700002000187856008300207 1997 eng d00aSome new item selection criteria for adaptive testing0 aSome new item selection criteria for adaptive testing a203-2260 v221 aBerger1 aVeerkamp, W J J uhttp://www.iacat.org/content/some-new-item-selection-criteria-adaptive-testing00414nas a2200121 4500008004100000245005800041210005800099300001200157490000700169100001300176700001800189856008500207 1997 eng d00aSome new item selection criteria for adaptive testing0 aSome new item selection criteria for adaptive testing a203-2260 v221 aVeerkamp1 aBerger, M P F uhttp://www.iacat.org/content/some-new-item-selection-criteria-adaptive-testing-000464nas a2200097 4500008004100000245010700041210006900148260001500217100001900232856011500251 1997 eng d00aSome questions that must be addressed to develop and maintain an item pool for use in an adaptive test0 aSome questions that must be addressed to develop and maintain an aChicago IL1 aKingsbury, G G uhttp://www.iacat.org/content/some-questions-must-be-addressed-develop-and-maintain-item-pool-use-adaptive-test00445nam a2200097 4500008004100000245005800041210005800099260008700157100002000244856008300264 1997 eng d00aStatistical methods for computerized adaptive testing0 aStatistical methods for computerized adaptive testing aUnpublished doctoral dissertation, University of Twente, Enschede, The Netherlands1 aVeerkamp, W J J uhttp://www.iacat.org/content/statistical-methods-computerized-adaptive-testing00442nas a2200097 4500008004100000245002600041210002600067260017900093100001700272856005500289 1997 eng d00aTechnical perspective0 aTechnical perspective aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 29-44). Washington, DC: American Psychological Association.1 aMcBride, J R uhttp://www.iacat.org/content/technical-perspective00542nas a2200121 4500008004500000245012600045210007100171300000800242490000600250100001600256700001500272856013300287 1997 Spandsh 00aUna solución a la estimatión inicial en los tests adaptivos informatizados [A solution to initial estimation in CATs.] 0 aUna solución a la estimatión inicial en los tests adaptivos info a1-60 v21 aRevuelta, J1 aPonsoda, V uhttp://www.iacat.org/content/una-soluci%C3%B3n-la-estimati%C3%B3n-inicial-en-los-tests-adaptivos-informatizados-solution-initial00608nas a2200133 4500008004100000245014700041210006900188260002600257100001500283700002200298700001600320700001200336856012600348 1997 eng d00aUnidimensional approximations for a computerized adaptive test when the item pool and latent space are multidimensional (Research Report 97-5)0 aUnidimensional approximations for a computerized adaptive test w aIowa City IA: ACT Inc1 aSpray, J A1 aAbdel-Fattah, A A1 aHuang, C -Y1 aLau, CA uhttp://www.iacat.org/content/unidimensional-approximations-computerized-adaptive-test-when-item-pool-and-latent-space-are01950nas a2200133 4500008004100000245005600041210005600097260002100153520149700174653003401671100001801705700001701723856007601740 1997 eng d00aValidation of CATSIB To investigate DIF of CAT data0 aValidation of CATSIB To investigate DIF of CAT data aChicago, IL. USA3 aThis paper investigates the performance of CATSIB (a modified version of the SIBTEST computer program) to assess differential item functioning (DIF) in the context of computerized adaptive testing (CAT). One of the distinguishing features of CATSIB is its theoretically built-in regression correction to control for the Type I error rates when the distributions of the reference and focal groups differ on the intended ability. This phenomenon is also called impact. The Type I error rate of CATSIB with the regression correction (WRC) was compared with that of CATSIB without the regression correction (WORC) to see if the regression correction was indeed effective. Also of interest was the power level of CATSIB after the regression correction. The subtest size was set at 25 items, and sample size, the impact level, and the amount of DIF were varied. Results show that the regression correction was very useful in controlling for the Type I error, CATSIB WORC had inflated observed Type I errors, especially when impact levels were high. The CATSIB WRC had observed Type I error rates very close to the nominal level of 0.05. The power rates of CATSIB WRC were impressive. As expected, the power increased as the sample size increased and as the amount of DIF increased. Even for small samples with high impact rates, power rates were 64% or higher for high DIF levels. For large samples, power rates were over 90% for high DIF levels. (Contains 12 tables and 7 references.) (Author/SLD)10acomputerized adaptive testing1 aNandakumar, R1 aRoussos, L A uhttp://www.iacat.org/content/validation-catsib-investigate-dif-cat-data00617nas a2200145 4500008004100000245005200041210005100093260016700144100001600311700001600327700002100343700001600364700001700380856007400397 1997 eng d00aValidation of the experimental CAT-ASVAB system0 aValidation of the experimental CATASVAB system aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation. Washington, DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aKieckhaefer, W F1 aVicino, F L1 aMcBride, J R uhttp://www.iacat.org/content/validation-experimental-cat-asvab-system00717nas a2200121 4500008004100000245008100041210006900122260025000191100001700441700001800458700001600476856010300492 1996 eng d00aAdaptive assessment and training using the neighbourhood of knowledge states0 aAdaptive assessment and training using the neighbourhood of know aFrasson, C. and Gauthier, G. and Lesgold, A. (eds.) Intelligent Tutoring Systems, Third International Conference, ITS'96, Montral, Canada, June 1996 Proceedings. Lecture Notes in Computer Science 1086. Berlin Heidelberg: Springer-Verlag 578-587.1 aDowling, C E1 aHockemeyer, C1 aLudwig, A H uhttp://www.iacat.org/content/adaptive-assessment-and-training-using-neighbourhood-knowledge-states00704nas a2200121 4500008004100000245007200041210006900113260025200182100001700434700001500451700001500466856010100481 1996 eng d00aAdaptive assessment using granularity hierarchies and Bayesian nets0 aAdaptive assessment using granularity hierarchies and Bayesian n aFrasson, C. and Gauthier, G. and Lesgold, A. (Eds.) Intelligent Tutoring Systems, Third International Conference, ITS'96, Montréal, Canada, June 1996 Proceedings. Lecture Notes in Computer Science 1086. Berlin Heidelberg: Springer-Verlag 569-577.1 aCollins, J A1 aGreer, J E1 aHuang, S X uhttp://www.iacat.org/content/adaptive-assessment-using-granularity-hierarchies-and-bayesian-nets00373nam a2200097 4500008004100000245003800041210003800079260007900117100001700196856006200213 1996 eng d00aAdaptive testing with granularity0 aAdaptive testing with granularity aMasters thesis, University of Saskatchewan, Department of Computer Science1 aCollins, J A uhttp://www.iacat.org/content/adaptive-testing-granularity00366nas a2200109 4500008004100000245005300041210005000094300001200144490000700156100001800163856007500181 1996 eng d00aAn alternative method for scoring adaptive tests0 aalternative method for scoring adaptive tests a365-3890 v211 aStocking, M L uhttp://www.iacat.org/content/alternative-method-scoring-adaptive-tests00392nas a2200109 4500008004100000245005800041210005800099300001200157490000700169100002300176856008300199 1996 eng d00aBayesian item selection criteria for adaptive testing0 aBayesian item selection criteria for adaptive testing a201-2160 v631 avan der Linden, WJ uhttp://www.iacat.org/content/bayesian-item-selection-criteria-adaptive-testing00503nas a2200097 4500008004100000245008200041210006900123260008500192100002300277856010500300 1996 eng d00aBayesian item selection criteria for adaptive testing (Research Report 96-01)0 aBayesian item selection criteria for adaptive testing Research R aTwente, The Netherlands: Department of Educational Measurement and Data Analysis1 avan der Linden, WJ uhttp://www.iacat.org/content/bayesian-item-selection-criteria-adaptive-testing-research-report-96-0100445nas a2200109 4500008004100000245007200041210006900113260002700182100001900209700001200228856009500240 1996 eng d00aBuilding a statistical foundation for computerized adaptive testing0 aBuilding a statistical foundation for computerized adaptive test aBanff, Alberta, Canada1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/building-statistical-foundation-computerized-adaptive-testing00647nas a2200133 4500008004100000245020300041210006900244260001600313100001700329700001700346700001200363700001700375856012100392 1996 eng d00aCan examinees use a review option to positively bias their scores on a computerized adaptive test? Paper presented at the annual meeting of the National council on Measurement in Education, New York0 aCan examinees use a review option to positively bias their score aNew York NY1 aRocklin, T R1 aVispoel, W P1 aWang, T1 aBleiler, T L uhttp://www.iacat.org/content/can-examinees-use-review-option-positively-bias-their-scores-computerized-adaptive-test00530nam a2200097 4500008004100000245011800041210006900159260006300228100001600291856012500307 1996 eng d00aA comparison of adaptive self-referenced testing and classical approaches to the measurement of individual change0 acomparison of adaptive selfreferenced testing and classical appr aUnpublished doctoral dissertation, University of Minnesota1 aVanLoy, W J uhttp://www.iacat.org/content/comparison-adaptive-self-referenced-testing-and-classical-approaches-measurement-individual00534nas a2200121 4500008004100000245012700041210006900168300001200237490000700249100001500256700001700271856012400288 1996 eng d00aComparison of SPRT and sequential Bayes procedures for classifying examinees into two categories using a computerized test0 aComparison of SPRT and sequential Bayes procedures for classifyi a405-4140 v211 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/comparison-sprt-and-sequential-bayes-procedures-classifying-examinees-two-categories-using00561nas a2200121 4500008004100000245011900041210006900160260002100229653003400250653001900284100001400303856012200317 1996 eng d00aA comparison of the traditional maximum information method and the global information method in CAT item selection0 acomparison of the traditional maximum information method and the aNew York, NY USA10acomputerized adaptive testing10aitem selection1 aTang, K L uhttp://www.iacat.org/content/comparison-traditional-maximum-information-method-and-global-information-method-cat-item00484nas a2200133 4500008004100000245007400041210006900115300001000184490001000194100001700204700001700221700001400238856009800252 1996 eng d00aComputerized adaptive skill assessment in a statewide testing program0 aComputerized adaptive skill assessment in a statewide testing pr a49-670 v29(1)1 aShermis, M D1 aStemmer, P M1 aWebb, P M uhttp://www.iacat.org/content/computerized-adaptive-skill-assessment-statewide-testing-program00541nas a2200109 4500008004100000245012900041210006900170260003400239100001600273700002400289856011800313 1996 eng d00aComputerized adaptive testing for classifying examinees into three categories (Measurement and Research Department Rep 96-3)0 aComputerized adaptive testing for classifying examinees into thr aArnhem, The Netherlands: Cito1 aEggen, Theo1 aStraetmans, G J J M uhttp://www.iacat.org/content/computerized-adaptive-testing-classifying-examinees-three-categories-measurement-and00450nas a2200109 4500008004100000245008300041210006900124300001000193100001700203700001200220856010800232 1996 eng d00aComputerized adaptive testing for reading assessment and diagnostic assessment0 aComputerized adaptive testing for reading assessment and diagnos a18-201 aShermis, M D1 aet. al. uhttp://www.iacat.org/content/computerized-adaptive-testing-reading-assessment-and-diagnostic-assessment00440nas a2200109 4500008004100000245007700041210006900118300001200187490000700199100002400206856010000230 1996 eng d00aComputerized adaptive testing for the national certification examination0 aComputerized adaptive testing for the national certification exa a119-1240 v641 aBergstrom, Betty, A uhttp://www.iacat.org/content/computerized-adaptive-testing-national-certification-examination-000395nas a2200085 4500008004100000245007700041210006900118100002400187856009800211 1996 eng d00aComputerized adaptive testing for the national certification examination0 aComputerized adaptive testing for the national certification exa1 aBergstrom, Betty, A uhttp://www.iacat.org/content/computerized-adaptive-testing-national-certification-examination00439nas a2200109 4500008004100000245007200041210006900113260001600182100001600198700001800214856009700232 1996 eng d00aComputing scores for incomplete GRE General computer adaptive tests0 aComputing scores for incomplete GRE General computer adaptive te aNew York NY1 aSlater, S C1 aSchaffer, G A uhttp://www.iacat.org/content/computing-scores-incomplete-gre-general-computer-adaptive-tests00446nas a2200145 4500008004100000245005100041210005000092300001200142490000700154100001400161700001400175700001400189700001700203856008000220 1996 eng d00aConducting self-adapted testing using MicroCAT0 aConducting selfadapted testing using MicroCAT a821-8270 v561 aRoos, L L1 aWise, S L1 aYoes, M E1 aRocklin, T R uhttp://www.iacat.org/content/conducting-self-adapted-testing-using-microcat00415nas a2200109 4500008004100000245006600041210006600107260001300173100001300186700001400199856009200213 1996 eng d00aConstructing adaptive tests to parallel conventional programs0 aConstructing adaptive tests to parallel conventional programs aNew York1 aDavey, T1 aThomas, L uhttp://www.iacat.org/content/constructing-adaptive-tests-parallel-conventional-programs00672nas a2200097 4500008004100000245008600041210006900127260025400196100001500450856010900465 1996 eng d00aA content-balanced adaptive testing algorithm for computer-based training systems0 acontentbalanced adaptive testing algorithm for computerbased tra aFrasson, C. and Gauthier, G. and Lesgold, A. (Eds.), Intelligent Tutoring Systems, Third International Conference, ITS'96, Montr�al, Canada, June 1996 Proceedings. Lecture Notes in Computer Science 1086. Berlin Heidelberg: Springer-Verlag 306-314.1 aHuang, S X uhttp://www.iacat.org/content/content-balanced-adaptive-testing-algorithm-computer-based-training-systems00450nas a2200097 4500008004100000245010100041210006900142260001300211100001400224856011400238 1996 eng d00aA critical analysis of the argument for and against item review in computerized adaptive testing0 acritical analysis of the argument for and against item review in aNew York1 aWise, S L uhttp://www.iacat.org/content/critical-analysis-argument-and-against-item-review-computerized-adaptive-testing00450nas a2200085 4500008004100000245011100041210006900152100001700221856012600238 1996 eng d00aCurrent research in computer-based testing for personnel selection and classification in the United States0 aCurrent research in computerbased testing for personnel selectio1 aMcBride, J R uhttp://www.iacat.org/content/current-research-computer-based-testing-personnel-selection-and-classification-united-states00864nas a2200205 4500008004100000245004600041210004600087260001200133300000800145490000600153520029600159653002900455653001500484653001100499653001800510653002400528653001800552100001700570856007100587 1996 eng d00aDispelling myths about the new NCLEX exam0 aDispelling myths about the new NCLEX exam cJan-Feb a6-70 v93 aThe new computerized NCLEX system is working well. Most new candidates, employers, and board of nursing representatives like the computerized adaptive testing system and the fast report of results. But, among the candidates themselves some myths have grown which cause them needless anxiety.10a*Educational Measurement10a*Licensure10aHumans10aNursing Staff10aPersonnel Selection10aUnited States1 aJohnson, S H uhttp://www.iacat.org/content/dispelling-myths-about-new-nclex-exam02576nas a2200133 4500008004100000245009100041210006900132300000900201490000700210520206600217653003402283100001402317856011102331 1996 eng d00aDynamic scaling: An ipsative procedure using techniques from computer adaptive testing0 aDynamic scaling An ipsative procedure using techniques from comp a58240 v563 aThe purpose of this study was to create a prototype method for scaling items using computer adaptive testing techniques and to demonstrate the method with a working model program. The method can be used to scale items, rank individuals with respect to the scaled items, and to re-scale the items with respect to the individuals' responses. When using this prototype method, the items to be scaled are part of a database that contains not only the items, but measures of how individuals respond to each item. After completion of all presented items, the individual is assigned an overall scale value which is then compared with each item responded to, and an individual "error" term is stored with each item. After several individuals have responded to the items, the item error terms are used to revise the placement of the scaled items. This revision feature allows the natural adaptation of one general list to reflect subgroup differences, for example, differences among geographic areas or ethnic groups. It also provides easy revision and limited authoring of the scale items by the computer program administrator. This study addressed the methodology, the instrumentation needed to handle the scale-item administration, data recording, item error analysis, and scale-item database editing required by the method, and the behavior of a prototype vocabulary test in use. Analyses were made of item ordering, response profiles, item stability, reliability and validity. Although slow, the movement of unordered words used as items in the prototype program was accurate as determined by comparison with an expert word ranking. Person scores obtained by multiple administrations of the prototype test were reliable and correlated at.94 with a commercial paper-and-pencil vocabulary test, while holding a three-to-one speed advantage in administration. Although based upon self-report data, dynamic scaling instruments like the model vocabulary test could be very useful for self-assessment, for pre (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aBerg, S R uhttp://www.iacat.org/content/dynamic-scaling-ipsative-procedure-using-techniques-computer-adaptive-testing00482nas a2200121 4500008004100000245007900041210006900120260002300189100002200212700001200234700001500246856009900261 1996 eng d00aEffect of altering passing score in CAT when unidimensionality is violated0 aEffect of altering passing score in CAT when unidimensionality i aNew York NYcApril1 aAbdel-Fattah, A A1 aLau, CA1 aSpray, J A uhttp://www.iacat.org/content/effect-altering-passing-score-cat-when-unidimensionality-violated02613nas a2200133 4500008004100000245011400041210006900155300000900224490000700233520206700240653003402307100001602341856012202357 1996 eng d00aThe effect of individual differences variables on the assessment of ability for Computerized Adaptive Testing0 aeffect of individual differences variables on the assessment of  a40850 v573 aComputerized Adaptive Testing (CAT) continues to gain momentum as the accepted testing modality for a growing number of certification, licensure, education, government and human resource applications. However, the developers of these tests have for the most part failed to adequately explore the impact of individual differences such as test anxiety on the adaptive testing process. It is widely accepted that non-cognitive individual differences variables interact with the assessment of ability when using written examinations. Logic would dictate that individual differences variables would equally affect CAT. Two studies were used to explore this premise. In the first study, 507 examinees were given a test anxiety survey prior to taking a high stakes certification exam using CAT or using a written format. All examinees had already completed their course of study, and the examination would be their last hurdle prior to being awarded certification. High test anxious examinees performed worse than their low anxious counterparts on both testing formats. The second study replicated the finding that anxiety depresses performance in CAT. It also addressed the differential effect of anxiety on within test performance. Examinees were candidates taking their final certification examination following a four year college program. Ability measures were calculated for each successive part of the test for 923 subjects. Within subject performance varied depending upon test position. High anxious examinees performed poorly at all points in the test, while low and medium anxious examinee performance peaked in the middle of the test. If test anxiety and performance measures were actually the same trait, then low anxious individuals should have performed equally well throughout the test. The observed interaction of test anxiety and time on task serves as strong evidence that test anxiety has motivationally mediated as well as cognitively mediated effects. The results of the studies are di (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGershon, RC uhttp://www.iacat.org/content/effect-individual-differences-variables-assessment-ability-computerized-adaptive-testing00570nas a2200121 4500008004100000245015700041210006900198100001700267700001600284700001300300700001500313856012000328 1996 eng d00aEffects of answer feedback and test anxiety on the psychometric and motivational characteristics of computer-adaptive and self-adaptive vocabulary tests0 aEffects of answer feedback and test anxiety on the psychometric 1 aVispoel, W P1 aBrunsman, B1 aForte, E1 aBleiler, T uhttp://www.iacat.org/content/effects-answer-feedback-and-test-anxiety-psychometric-and-motivational-characteristics00557nas a2200121 4500008004100000245015500041210006900196260001300265100001500278700001300293700001100306856011800317 1996 eng d00aEffects of answer review and test anxiety on the psychometric and motivational characteristics of computer-adaptive and self-adaptive vocabulary tests0 aEffects of answer review and test anxiety on the psychometric an aNew York1 aVispoel, W1 aForte, E1 aBoo, J uhttp://www.iacat.org/content/effects-answer-review-and-test-anxiety-psychometric-and-motivational-characteristics00584nas a2200133 4500008004100000245013900041210006900180260001600249100001100265700001200276700001700288700002100305856012400326 1996 eng d00aThe effects of methods of theta estimation, prior distribution, and number of quadrature points on CAT using the graded response model0 aeffects of methods of theta estimation prior distribution and nu aNew York NY1 aHou, L1 aChen, S1 aG., Dodd., B1 aFitzpatrick, S J uhttp://www.iacat.org/content/effects-methods-theta-estimation-prior-distribution-and-number-quadrature-points-cat-using00442nam a2200097 4500008003900000245006600039210006200105260007600167100001600243856008500259 1996 d00aThe effects of person misfit in computerized adaptive testing0 aeffects of person misfit in computerized adaptive testing aUnpublished doctoral dissertation, University of Minnesota, Minneapolis1 aNering, M L uhttp://www.iacat.org/content/effects-person-misfit-computerized-adaptive-testing00543nas a2200121 4500008004100000245012100041210006900162260001300231100002000244700001800264700001400282856012500296 1996 eng d00aEffects of randomesque item selection on CAT item exposure rates and proficiency estimation under 1- and 2-PL models0 aEffects of randomesque item selection on CAT item exposure rates aNew York1 aFeatherman, C M1 aSubhiyah, R G1 aHadadi, A uhttp://www.iacat.org/content/effects-randomesque-item-selection-cat-item-exposure-rates-and-proficiency-estimation-under00461nas a2200109 4500008004100000245008200041210006900123260002700192100001500219700001800234856009900252 1996 eng d00aAn evaluation of a two-stage testlet design for computerized adaptive testing0 aevaluation of a twostage testlet design for computerized adaptiv aBanff, Alberta, Canada1 aReese, L M1 aSchnipke, D L uhttp://www.iacat.org/content/evaluation-two-stage-testlet-design-computerized-adaptive-testing01733nas a2200145 4500008004100000020001400041245006700055210006500122300001200187490000700199520125900206100001901465700001201484856009101496 1996 eng d a0146-621600aA global information approach to computerized adaptive testing0 aglobal information approach to computerized adaptive testing a213-2290 v203 abased on Fisher information (or item information). At each stage, an item is selected to maximize the Fisher information at the currently estimated trait level (&thetas;). However, this application of Fisher information could be much less efficient than assumed if the estimators are not close to the true &thetas;, especially at early stages of an adaptive test when the test length (number of items) is too short to provide an accurate estimate for true &thetas;. It is argued here that selection procedures based on global information should be used, at least at early stages of a test when &thetas; estimates are not likely to be close to the true &thetas;. For this purpose, an item selection procedure based on average global information is proposed. Results from pilot simulation studies comparing the usual maximum item information item selection with the proposed global information approach are reported, indicating that the new method leads to improvement in terms of bias and mean squared error reduction under many circumstances. Index terms: computerized adaptive testing, Fisher information, global information, information surface, item information, item response theory, Kullback-Leibler information, local information, test information.1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/global-information-approach-computerized-adaptive-testing00439nas a2200121 4500008004500000245006700045210006500112300001200177490000700189100001600196700001200212856009300224 1996 Engldsh 00aA Global Information Approach to Computerized Adaptive Testing0 aGlobal Information Approach to Computerized Adaptive Testing a213-2290 v201 aChang, H -H1 aYing, Z uhttp://www.iacat.org/content/global-information-approach-computerized-adaptive-testing-100473nas a2200121 4500008004100000245007400041210006900115260001600184100001500200700001400215700001900229856010300248 1996 eng d00aHeuristic-based CAT: Balancing item information, content and exposure0 aHeuristicbased CAT Balancing item information content and exposu aNew York NY1 aLuecht, RM1 aHadadi, A1 aNungester, R J uhttp://www.iacat.org/content/heuristic-based-cat-balancing-item-information-content-and-exposure-000472nas a2200121 4500008004100000245007500041210006900116260001600185100001500201700001400216700001900230856010100249 1996 eng d00aHeuristic-based CAT: Balancing item information, content, and exposure0 aHeuristicbased CAT Balancing item information content and exposu aNew York NY1 aLuecht, RM1 aHadadi, A1 aNungester, R J uhttp://www.iacat.org/content/heuristic-based-cat-balancing-item-information-content-and-exposure00474nas a2200121 4500008004100000245007600041210006900117260001600186100001500202700001900217700001400236856010200250 1996 eng d00aHeuristics based CAT: Balancing item information, content, and exposure0 aHeuristics based CAT Balancing item information content and expo aNew York NY1 aLuecht, RM1 aNungester, R J1 aHadadi, A uhttp://www.iacat.org/content/heuristics-based-cat-balancing-item-information-content-and-exposure00311nas a2200097 4500008004100000245003700041210003700078260001300115100001900128856006600147 1996 eng d00aItem review and adaptive testing0 aItem review and adaptive testing aNew York1 aKingsbury, G G uhttp://www.iacat.org/content/item-review-and-adaptive-testing01528nas a2200229 4500008004100000020004100041245010500082210006900187250001500256260001200271300000900283490000700292520069800299653002500997653002501022653004301047653003701090653001101127100001601138700001801154856012601172 1996 eng d a0363-3624 (Print)0363-3624 (Linking)00aMethodologic trends in the healthcare professions: computer adaptive and computer simulation testing0 aMethodologic trends in the healthcare professions computer adapt a1996/07/01 cJul-Aug a13-40 v213 aAssessing knowledge and performance on computer is rapidly becoming a common phenomenon in testing and measurement. Computer adaptive testing presents an individualized test format in accordance with the examinee's ability level. The efficiency of the testing process enables a more precise estimate of performance, often with fewer items than traditional paper-and-pencil testing methodologies. Computer simulation testing involves performance-based, or authentic, assessment of the examinee's clinical decision-making abilities. The authors discuss the trends in assessing performance through computerized means and the application of these methodologies to community-based nursing practice.10a*Clinical Competence10a*Computer Simulation10aComputer-Assisted Instruction/*methods10aEducational Measurement/*methods10aHumans1 aForker, J E1 aMcDonald, M E uhttp://www.iacat.org/content/methodologic-trends-healthcare-professions-computer-adaptive-and-computer-simulation-testing00553nas a2200121 4500008004500000245015200045210006900197300001200266490000700278100001600285700001500301856011500316 1996 Spandsh 00aMetodos sencillos para el control de las tasas de exposicion en tests adaptativos informatizados [Simple methods for item exposure control in CATs]0 aMetodos sencillos para el control de las tasas de exposicion en  a161-1720 v171 aRevuelta, J1 aPonsoda, V uhttp://www.iacat.org/content/metodos-sencillos-para-el-control-de-las-tasas-de-exposicion-en-tests-adaptativos00550nas a2200109 4500008004100000245013000041210006900171260004600240100001700286700001300303856012400316 1996 eng d00aMissing responses and IRT ability estimation: Omits, choice, time limits, and adaptive testing (Research Report RR-96-30-ONR)0 aMissing responses and IRT ability estimation Omits choice time l aPrinceton NJ: Educational Testing Service1 aMislevy, R J1 aWu, P -K uhttp://www.iacat.org/content/missing-responses-and-irt-ability-estimation-omits-choice-time-limits-and-adaptive-testing00436nas a2200097 4500008004100000245008600041210006900127260001600196100001900212856010700231 1996 eng d00aA model for score maximization within a computerized adaptive testing environment0 amodel for score maximization within a computerized adaptive test aNew York NY1 aChang, Hua-Hua uhttp://www.iacat.org/content/model-score-maximization-within-computerized-adaptive-testing-environment00465nas a2200121 4500008004100000245008000041210006900121260001300190100001300203700001200216700001300228856010200241 1996 eng d00aModifying the NCLEXTM CAT item selection algorithm to improve item exposure0 aModifying the NCLEXTM CAT item selection algorithm to improve it aNew York1 aWay, W D1 aZara, A1 aLeahy, J uhttp://www.iacat.org/content/modifying-nclextm-cat-item-selection-algorithm-improve-item-exposure00978nas a2200121 4500008004100000245003800041210003800079300001200117490000700129520063700136100001600773856006700789 1996 eng d00aMultidimensional adaptive testing0 aMultidimensional adaptive testing a331-3540 v613 aMaximum likelihood and Bayesian procedures for item selection and scoring of multidimensional adaptive tests are presented. A demonstration using simulated response data illustrates that multidimensional adaptive testing (MAT) can provide equal or higher reliabilities with about one-third fewer items than are required by one-dimensional adaptive testing (OAT). Furthermore, holding test-length constant across the MAT and OAT approaches, substantial improvements in reliability can be obtained from multidimensional assessment. A number of issues relating to the operational use of multidimensional adaptive testing are discussed.1 aSegall, D O uhttp://www.iacat.org/content/multidimensional-adaptive-testing00331nas a2200109 4500008004100000245003800041210003800079300001200117490000700129100001600136856006900152 1996 eng d00aMultidimensional adaptive testing0 aMultidimensional adaptive testing a331-3540 v611 aSegall, D O uhttp://www.iacat.org/content/multidimensional-adaptive-testing-000359nas a2200109 4500008004100000245004700041210004700088260001600135100001100151700001100162856007600173 1996 eng d00aMultidimensional computer adaptive testing0 aMultidimensional computer adaptive testing aNew York NY1 aFan, M1 aHsu, Y uhttp://www.iacat.org/content/multidimensional-computer-adaptive-testing01610nas a2200133 4500008004100000245009100041210006900132300001200201490000700213520109200220653003401312100001501346856011501361 1996 eng d00aMultidimensional computerized adaptive testing in a certification or licensure context0 aMultidimensional computerized adaptive testing in a certificatio a389-4040 v203 a(from the journal abstract) Multidimensional item response theory (MIRT) computerized adaptive testing, building on a recent work by D. O. Segall (1996), is applied in a licensing/certification context. An example of a medical licensure test is used to demonstrate situations in which complex, integrated content must be balanced at the total test level for validity reasons, but items assigned to reportable subscore categories may be used under a MIRT adaptive paradigm to improve the reliability of the subscores. A heuristic optimization framework is outlined that generalizes to both univariate and multivariate statistical objective functions, with additional systems of constraints included to manage the content balancing or other test specifications on adaptively constructed test forms. Simulation results suggested that a multivariate treatment of the problem, although complicating somewhat the objective function used and the estimation of traits, nonetheless produces advantages from a psychometric perspective. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aLuecht, RM uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-certification-or-licensure-context00466nas a2200109 4500008004500000245009100045210006900136300001200205490000700217100001500224856011700239 1996 Engldsh 00aMultidimensional Computerized Adaptive Testing in a Certification or Licensure Context0 aMultidimensional Computerized Adaptive Testing in a Certificatio a389-4040 v201 aLuecht, RM uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-certification-or-licensure-context-000520nas a2200121 4500008004100000245010300041210006900144260001300213100002000226700001800246700001400264856012000278 1996 eng d00aNew algorithms for item selection and exposure and proficiency estimation under 1- and 2-PL models0 aNew algorithms for item selection and exposure and proficiency e aNew York1 aFeatherman, C M1 aSubhiyah, R G1 aHadadi, A uhttp://www.iacat.org/content/new-algorithms-item-selection-and-exposure-and-proficiency-estimation-under-1-and-2-pl00501nas a2200109 4500008004100000245009100041210006900132260004600201100001800247700001500265856011100280 1996 eng d00aOptimal design of item pools for computerized adaptive testing (Research Report 96-34)0 aOptimal design of item pools for computerized adaptive testing R aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/optimal-design-item-pools-computerized-adaptive-testing-research-report-96-3400399nas a2200109 4500008004100000245006100041210006000102260001300162100001600175700001300191856008500204 1996 eng d00aPerson-fit indices and their role in the CAT environment0 aPersonfit indices and their role in the CAT environment aNew York1 aMcLeod, L D1 aLewis, C uhttp://www.iacat.org/content/person-fit-indices-and-their-role-cat-environment-000399nas a2200109 4500008004100000245006100041210006000102260001600162100001500178700001300193856008300206 1996 eng d00aPerson-fit indices and their role in the CAT environment0 aPersonfit indices and their role in the CAT environment aNew York NY1 aDavid, L A1 aLewis, C uhttp://www.iacat.org/content/person-fit-indices-and-their-role-cat-environment00432nas a2200121 4500008004100000245006600041210006500107300001200172490000600184100001000190700001800200856009200218 1996 eng d00aPractical issues in large-scale computerized adaptive testing0 aPractical issues in largescale computerized adaptive testing a287-3040 v91 aMills1 aStocking, M L uhttp://www.iacat.org/content/practical-issues-large-scale-computerized-adaptive-testing00570nas a2200121 4500008004100000245009500041210006900136260008100205100001500286700001200301700001700313856011800330 1996 eng d00aPreliminary cost-effectiveness analysis of alternative ASVAB testing concepts at MET sites0 aPreliminary costeffectiveness analysis of alternative ASVAB test aInterim report to Defense Manpower Data Center. Fairfax, VA: Lewin-VHI, Inc.1 aHogan, P F1 aDall, T1 aMcBride, J R uhttp://www.iacat.org/content/preliminary-cost-effectiveness-analysis-alternative-asvab-testing-concepts-met-sites00637nas a2200145 4500008004500000245018700045210006900232300001000301490000700311100001300318700001500331700001600346700001400362856011500376 1996 Spandsh 00aPropiedades psicometricas du un test adaptivo informatizado do vocabulario ingles [Psychometric properties of a computerized adaptive tests for the measurement of English vocabulary]0 aPropiedades psicometricas du un test adaptivo informatizado do v a61-730 v551 aOlea., J1 aPonsoda, V1 aRevuelta, J1 aBelchi, J uhttp://www.iacat.org/content/propiedades-psicometricas-du-un-test-adaptivo-informatizado-do-vocabulario-ingles00520nas a2200109 4500008004100000245009800041210006900139260004600208100001900254700001200273856012500285 1996 eng d00aRecursive maximum likelihood estimation, sequential design, and computerized adaptive testing0 aRecursive maximum likelihood estimation sequential design and co aPrinceton NJ: Educational Testing Service1 aChang, Hua-Hua1 aYing, Z uhttp://www.iacat.org/content/recursive-maximum-likelihood-estimation-sequential-design-and-computerized-adaptive-testing00494nas a2200097 4500008004100000245010200041210006900143260004600212100001800258856012000276 1996 eng d00aRevising item responses in computerized adaptive testing: A comparison of three models (RR-96-12)0 aRevising item responses in computerized adaptive testing A compa aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/revising-item-responses-computerized-adaptive-testing-comparison-three-models-rr-96-1200522nam a2200097 4500008003900000245010900039210006900148260007200217100001200289856012300301 1996 d00aRobustness of a unidimensional computerized testing mastery procedure with multidimensional testing data0 aRobustness of a unidimensional computerized testing mastery proc aUnpublished doctoral dissertation, University of Iowa, Iowa City IA1 aLau, CA uhttp://www.iacat.org/content/robustness-unidimensional-computerized-testing-mastery-procedure-multidimensional-testing00509nas a2200109 4500008004100000245012400041210006900165260001300234100001300247700001300260856012600273 1996 eng d00aA search procedure to determine sets of decision points when using testlet-based Bayesian sequential testing procedures0 asearch procedure to determine sets of decision points when using aNew York1 aSmith, R1 aLewis, C uhttp://www.iacat.org/content/search-procedure-determine-sets-decision-points-when-using-testlet-based-bayesian-sequential00512nas a2200109 4500008004100000245009000041210006900131260005400200100001500254700001900269856011400288 1996 eng d00aSome practical examples of computerized adaptive sequential testing (Internal Report)0 aSome practical examples of computerized adaptive sequential test aPhiladelphia: National Board of Medical Examiners1 aLuecht, RM1 aNungester, R J uhttp://www.iacat.org/content/some-practical-examples-computerized-adaptive-sequential-testing-internal-report00432nas a2200121 4500008004100000245006500041210006500106260001400171100001300185700001200198700001300210856008700223 1996 eng d00aStrategies for managing item pools to maximize item security0 aStrategies for managing item pools to maximize item security aSan Diego1 aWay, W D1 aZara, A1 aLeahy, J uhttp://www.iacat.org/content/strategies-managing-item-pools-maximize-item-security00437nas a2200109 4500008004100000245006800041210006600109260003000175100001200205700001500217856009500232 1996 eng d00aTest adaptativos informatizados [Computerized adaptive testing]0 aTest adaptativos informatizados Computerized adaptive testing aMadrid, UNEDbUniversitas1 aOlea, J1 aPonsoda, V uhttp://www.iacat.org/content/test-adaptativos-informatizados-computerized-adaptive-testing00489nas a2200097 4500008004100000245012400041210006900165260001900234100001500253856012300268 1996 eng d00aA Type I error rate study of a modified SIBTEST DIF procedure with potential application to computerized adaptive tests0 aType I error rate study of a modified SIBTEST DIF procedure with aAlberta Canada1 aRoussos, L uhttp://www.iacat.org/content/type-i-error-rate-study-modified-sibtest-dif-procedure-potential-application-computerized00425nam a2200097 4500008004100000245006200041210006000103260004700163100003600210856008100246 1996 eng d00aUsers manual for the MicroCAT testing system, Version 3.50 aUsers manual for the MicroCAT testing system Version 35 aSt Paul MN: Assessment Systems Corporation1 aAssessment-Systems-Corporation. uhttp://www.iacat.org/content/users-manual-microcat-testing-system-version-3500515nas a2200121 4500008004100000245010200041210006900143260001400212100001200226700002200238700001500260856011800275 1996 eng d00aUsing unidimensional IRT models for dichotomous classification via CAT with multidimensional data0 aUsing unidimensional IRT models for dichotomous classification v aBoston MA1 aLau, CA1 aAbdel-Fattah, A A1 aSpray, J A uhttp://www.iacat.org/content/using-unidimensional-irt-models-dichotomous-classification-cat-multidimensional-data00478nas a2200109 4500008004100000245009900041210006900140260001600209100001100225700001100236856012100247 1996 eng d00aUtility of Fisher information, global information and different starting abilities in mini CAT0 aUtility of Fisher information global information and different s aNew York NY1 aFan, M1 aHsu, Y uhttp://www.iacat.org/content/utility-fisher-information-global-information-and-different-starting-abilities-mini-cat00523nas a2200121 4500008004100000245012100041210006900162300001200231490000600243100001400249700001700263856012100280 1996 eng d00aValidity of item selection: A comparison of automated computerized adaptive and manual paper and pencil examinations0 aValidity of item selection A comparison of automated computerize a152-1570 v81 aLunz, M E1 aDeville, C W uhttp://www.iacat.org/content/validity-item-selection-comparison-automated-computerized-adaptive-and-manual-paper-and02609nas a2200133 4500008004100000245012000041210006900161300000900230490000700239520205500246653003402301100001602335856012402351 1995 eng d00aAssessment of scaled score consistency in adaptive testing from a multidimensional item response theory perspective0 aAssessment of scaled score consistency in adaptive testing from  a55980 v553 aThe purpose of this study was twofold: (a) to examine whether the unidimensional adaptive testing estimates are comparable for different ability levels of examinees when the true examinee-item interaction is correctly modeled using a compensatory multidimensional item response theory (MIRT) model; and (b) to investigate the effects of adaptive testing estimation when the procedure of item selection of computerized adaptive testing (CAT) is controlled by either content-balancing or selecting the most informative item in a user specified direction at the current estimate of unidimensional ability. A series of Monte Carlo simulations were conducted in this study. Deviation from the reference composite angle was used as an index of the theta1,theta2-composite consistency across the different levels of unidimensional CAT estimates. In addition, the effect of the content-balancing item selection procedure and the fixed-direction item selection procedure were compared across the different ability levels. The characteristics of item selection, test information and the relationship between unidimensional and multidimensional models were also investigated. In addition to employing statistical analysis to examine the robustness of the CAT procedure violations of unidimensionality, this research also included graphical analyses to present the results. The results were summarized as follows: (a) the reference angles for the no-control-item-selection method were disparate across the unidimensional ability groups; (b) the unidimensional CAT estimates from the content-balancing item selection method did not offer much improvement; (c) the fixed-direction-item selection method did provide greater consistency for the unidimensional CAT estimates across the different levels of ability; (d) and, increasing the CAT test length did not provide greater score scale consistency. Based on the results of this study, the following conclusions were drawn: (a) without any controlling (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aFan, Miechu uhttp://www.iacat.org/content/assessment-scaled-score-consistency-adaptive-testing-multidimensional-item-response-theory00421nas a2200109 4500008004100000245006700041210006500108260002100173100001500194700001300209856008900222 1995 eng d00aA Bayesian computerized mastery model with multiple cut scores0 aBayesian computerized mastery model with multiple cut scores aSan Francisco CA1 aSmith, R L1 aLewis, C uhttp://www.iacat.org/content/bayesian-computerized-mastery-model-multiple-cut-scores00351nas a2200097 4500008004100000245004800041210004800089260001900137100002300156856007400179 1995 eng d00aBayesian item selection in adaptive testing0 aBayesian item selection in adaptive testing aMinneapolis MN1 avan der Linden, WJ uhttp://www.iacat.org/content/bayesian-item-selection-adaptive-testing01549nas a2200181 4500008004100000020002200041245008000063210006900143250001500212260000800227300001100235490000700246520096300253100001501216700002001231700001701251856009901268 1995 eng d a0022-3891 (Print)00aComparability and validity of computerized adaptive testing with the MMPI-20 aComparability and validity of computerized adaptive testing with a1995/10/01 cOct a358-710 v653 aThe comparability and validity of a computerized adaptive (CA) Minnesota Multiphasic Personality Inventory-2 (MMPI-2) were assessed in a sample of 571 undergraduate college students. The CA MMPI-2 administered adaptively Scales L, E the 10 clinical scales, and the 15 content scales, utilizing the countdown method (Butcher, Keller, & Bacon, 1985). All subjects completed the MMPI-2 twice, with three experimental conditions: booklet test-retest, booklet-CA, and conventional computerized (CC)-CA. Profiles across administration modalities show a high degree of similarity, providing evidence for the comparability of the three forms. Correlations between MMPI-2 scales and other psychometric measures (Beck Depression Inventory; Symptom Checklist-Revised; State-Trait Anxiety and Anger Scales; and the Anger Expression Scale) support the validity of the CA MMPI-2. Substantial item savings may be realized with the implementation of the countdown procedure.1 aRoper, B L1 aBen-Porath, Y S1 aButcher, J N uhttp://www.iacat.org/content/comparability-and-validity-computerized-adaptive-testing-mmpi-2-000447nas a2200109 4500008004100000245007900041210006900120260001800189100001600207700001800223856009600241 1995 eng d00aComparability studies for the GRE CAT General Test and the NCLEX using CAT0 aComparability studies for the GRE CAT General Test and the NCLEX aSan Francisco1 aEignor, D R1 aSchaffer, G A uhttp://www.iacat.org/content/comparability-studies-gre-cat-general-test-and-nclex-using-cat00542nas a2200121 4500008004100000245011400041210006900155260002100224100001500245700001800260700001800278856012400296 1995 eng d00aA comparison of classification agreement between adaptive and full-length test under the 1-PL and 2-PL models0 acomparison of classification agreement between adaptive and full aSan Francisco CA1 aLewis, M J1 aSubhiyah, R G1 aMorrison, C A uhttp://www.iacat.org/content/comparison-classification-agreement-between-adaptive-and-full-length-test-under-1-pl-and-200522nas a2200109 4500008004100000245012500041210006900166260002100235100001700256700001900273856012000292 1995 eng d00aA comparison of gender differences on paper-and-pencil and computer-adaptive versions of the Graduate Record Examination0 acomparison of gender differences on paperandpencil and computera aSan Francisco CA1 aBridgeman, B1 aSchaeffer, G A uhttp://www.iacat.org/content/comparison-gender-differences-paper-and-pencil-and-computer-adaptive-versions-graduate00445nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001400215856009400229 1995 eng d00aA comparison of item selection routines in linear and adaptive tests0 acomparison of item selection routines in linear and adaptive tes a227-2420 v321 aSchnipke1 aGreen, BF uhttp://www.iacat.org/content/comparison-item-selection-routines-linear-and-adaptive-tests00533nas a2200121 4500008004100000245011800041210006900159260001800228100001300246700001300259700001500272856012400287 1995 eng d00aA comparison of two IRT-based models for computerized mastery testing when item parameter estimates are uncertain0 acomparison of two IRTbased models for computerized mastery testi aSan Francisco1 aWay, W D1 aLewis, C1 aSmith, R L uhttp://www.iacat.org/content/comparison-two-irt-based-models-computerized-mastery-testing-when-item-parameter-estimates00535nas a2200109 4500008004100000245013700041210006900178260001800247100001800265700001900283856012300302 1995 eng d00aComputer adaptive testing in a medical licensure setting: A comparison of outcomes under the one- and two- parameter logistic models0 aComputer adaptive testing in a medical licensure setting A compa aSan Francisco1 aMorrison, C A1 aNungester, R J uhttp://www.iacat.org/content/computer-adaptive-testing-medical-licensure-setting-comparison-outcomes-under-one-and-two00452nas a2200145 4500008004100000245005700041210005500098300001400153490000700167100001200174700001400186700001300200700001300213856008000226 1995 eng d00aComputer-adaptive testing: A new breed of assessment0 aComputeradaptive testing A new breed of assessment a1326-13270 v951 aRuiz, B1 aFitz, P A1 aLewis, C1 aReidy, C uhttp://www.iacat.org/content/computer-adaptive-testing-new-breed-assessment00454nas a2200145 4500008004100000245005700041210005500098300001400153490000700167100001200174700001400186700001300200700001300213856008200226 1995 eng d00aComputer-adaptive testing: A new breed of assessment0 aComputeradaptive testing A new breed of assessment a1326-13270 v951 aRuiz, B1 aFitz, P A1 aLewis, C1 aReidy, C uhttp://www.iacat.org/content/computer-adaptive-testing-new-breed-assessment-000432nas a2200109 4500008004100000245007800041210006900119300000800188490000600196100001700202856010300219 1995 eng d00aComputer-adaptive testing: CAT: A Bayesian maximum-falsification approach0 aComputeradaptive testing CAT A Bayesian maximumfalsification app a4120 v91 aLinacre, J M uhttp://www.iacat.org/content/computer-adaptive-testing-cat-bayesian-maximum-falsification-approach00474nam a2200097 4500008004100000245007400041210006900115260007900184100001400263856009900277 1995 eng d00aComputerized adaptive attitude testing using the partial credit model0 aComputerized adaptive attitude testing using the partial credit  aDissertation Abstracts International-A, 55(7-A), 1922 (UMI No. AAM9430378)1 aBaek, S G uhttp://www.iacat.org/content/computerized-adaptive-attitude-testing-using-partial-credit-model01388nas a2200133 4500008004100000245007200041210006900113300001200182490000700194520091500201100001401116700002401130856010001154 1995 eng d00aComputerized adaptive testing: Tracking candidate response patterns0 aComputerized adaptive testing Tracking candidate response patter a151-1620 v133 aTracked the effect of candidate response patterns on a computerized adaptive test. Data were from a certification examination in laboratory science administered in 1992 to 155 candidates, using a computerized adaptive algorithm. The 90-item certification examination was divided into 9 units of 10 items each to track the pattern of initial responses and response alterations on ability estimates and test precision across the 9 test units. The precision of the test was affected most by response alterations during early segments of the test. While candidates generally benefited from altering responses, individual candidates showed different patterns of response alterations across test segments. Test precision was minimally affected, suggesting that the tailoring of computerized adaptive testing is minimally affected by response alterations. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aLunz, M E1 aBergstrom, Betty, A uhttp://www.iacat.org/content/computerized-adaptive-testing-tracking-candidate-response-patterns00436nas a2200133 4500008004500000245005600045210005600101300000900157490000700166100001400173700001800187700001500205856008200220 1995 Engldsh 00aComputerized Adaptive Testing With Polytomous Items0 aComputerized Adaptive Testing With Polytomous Items a5-220 v191 aDodd, B G1 aDe Ayala, R J1 aKoch. W.R. uhttp://www.iacat.org/content/computerized-adaptive-testing-polytomous-items-001008nas a2200145 4500008004100000245005600041210005600097300001200153490000700165520056200172100001400734700002000748700001400768856008000782 1995 eng d00aComputerized adaptive testing with polytomous items0 aComputerized adaptive testing with polytomous items a5–22.0 v193 aDiscusses polytomous item response theory models and the research that has been conducted to investigate a variety of possible operational procedures (item bank, item selection, trait estimation, stopping rule) for polytomous model-based computerized adaptive testing (PCAT). Studies are reviewed that compared PCAT systems based on competing item response theory models that are appropriate for the same measurement objective, as well as applications of PCAT in marketing and educational psychology. Directions for future research using PCAT are suggested.1 aDodd, B G1 ade Ayala, R. J.1 aKoch, W R uhttp://www.iacat.org/content/computerized-adaptive-testing-polytomous-items00438nas a2200097 4500008004100000245003900041210003900080260014300119100001400262856006400276 1995 eng d00aComputerized testing for licensure0 aComputerized testing for licensure aJ. Impara (ed.), Licensure testing: Purposes, procedures, and Practices (pp. 291-320). Lincoln NE: Buros Institute of Mental Measurements.1 aVale, C D uhttp://www.iacat.org/content/computerized-testing-licensure00533nas a2200109 4500008004100000245011000041210006900151260004700220100001800267700001300285856012500298 1995 eng d00aControlling item exposure conditional on ability in computerized adaptive testing (Research Report 95-25)0 aControlling item exposure conditional on ability in computerized aPrinceton NJ: Educational Testing Service.1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/controlling-item-exposure-conditional-ability-computerized-adaptive-testing-research-report00328nas a2200109 4500008004100000245003400041210003300075260001800108100001600126700001700142856005900159 1995 eng d00aDoes cheating on CAT pay: Not0 aDoes cheating on CAT pay Not aSan Francisco1 aGershon, RC1 aBergstrom, B uhttp://www.iacat.org/content/does-cheating-cat-pay-not00466nas a2200109 4500008004100000245009500041210006900136260001900205100001100224700001100235856011000246 1995 eng d00aThe effect of ability estimation for polytomous CAT in different item selection procedures0 aeffect of ability estimation for polytomous CAT in different ite aMinneapolis MN1 aFan, M1 aHsu, Y uhttp://www.iacat.org/content/effect-ability-estimation-polytomous-cat-different-item-selection-procedures00592nas a2200133 4500008004100000245013900041210006900180260002000249100001500269700001600284700001400300700001800314856012600332 1995 eng d00aThe effect of model misspecification on classification decisions made using a computerized test: 3-PLM vs. 1PLM (and UIRT versus MIRT)0 aeffect of model misspecification on classification decisions mad aMinneapolis, MN1 aSpray, J A1 aKalohn, J C1 aSchulz, M1 aFleer, Jr., P uhttp://www.iacat.org/content/effect-model-misspecification-classification-decisions-made-using-computerized-test-3-plm-vs00517nas a2200109 4500008004100000245011800041210006900159260001900228100002200247700001600269856012200285 1995 eng d00aThe effect of model misspecification on classification decisions made using a computerized test: UIRT versus MIRT0 aeffect of model misspecification on classification decisions mad aMinneapolis MN1 aAbdel-Fattah, A A1 aLau, C -M A uhttp://www.iacat.org/content/effect-model-misspecification-classification-decisions-made-using-computerized-test-uirt00552nas a2200133 4500008004100000245011000041210006900151260001800220100001200238700001100250700002100261700001400282856012200296 1995 eng d00aThe effect of population distribution and methods of theta estimation on CAT using the rating scale model0 aeffect of population distribution and methods of theta estimatio aSan Francisco1 aChen, S1 aHou, L1 aFitzpatrick, S J1 aDodd, B G uhttp://www.iacat.org/content/effect-population-distribution-and-methods-theta-estimation-cat-using-rating-scale-model00505nas a2200133 4500008003900000245008900039210006900128300001200197490000700209100001300216700001600229700001700245856010900262 1995 d00aEffect of Rasch calibration on ability and DIF estimation in computer-adaptive tests0 aEffect of Rasch calibration on ability and DIF estimation in com a341-3630 v321 aZwick, R1 aThayer, D T1 aWingersky, M uhttp://www.iacat.org/content/effect-rasch-calibration-ability-and-dif-estimation-computer-adaptive-tests00458nas a2200133 4500008004100000245006200041210006100103300001200164490000700176100001700183700002100200700001500221856008800236 1995 eng d00aEffects and underlying mechanisms of self-adapted testing0 aEffects and underlying mechanisms of selfadapted testing a103-1160 v871 aRocklin, T R1 aO’Donnell, A M1 aHolst, P M uhttp://www.iacat.org/content/effects-and-underlying-mechanisms-self-adapted-testing00402nas a2200097 4500008004100000245007200041210006800113260001600181100001600197856009100213 1995 eng d00aThe effects of item compromise on computerized adaptive test scores0 aeffects of item compromise on computerized adaptive test scores aOrlando, FL1 aSegall, D O uhttp://www.iacat.org/content/effects-item-compromise-computerized-adaptive-test-scores00560nam a2200097 4500008004100000245013500041210006900176260007800245100001600323856012300339 1995 eng d00aEl control de la exposicin de los items en tests adaptativos informatizados [Item exposure control in computerized adaptive tests]0 aEl control de la exposicin de los items en tests adaptativos inf aUnpublished master’s dissertation, Universidad Autonma de Madrid, Spain1 aRevuelta, J uhttp://www.iacat.org/content/el-control-de-la-exposicin-de-los-items-en-tests-adaptativos-informatizados-item-exposure00500nas a2200109 4500008004100000245010300041210006900144260001800213100001400231700002400245856012100269 1995 eng d00aEquating computerized adaptive certification examinations: The Board of Registry series of studies0 aEquating computerized adaptive certification examinations The Bo aSan Francisco1 aLunz, M E1 aBergstrom, Betty, A uhttp://www.iacat.org/content/equating-computerized-adaptive-certification-examinations-board-registry-series-studies00375nas a2200097 4500008004100000245006000041210005800101260001800159100001600177856008400193 1995 eng d00aEquating the CAT-ASVAB: Experiences and lessons learned0 aEquating the CATASVAB Experiences and lessons learned aSan Francisco1 aSegall, D O uhttp://www.iacat.org/content/equating-cat-asvab-experiences-and-lessons-learned00365nas a2200109 4500008004100000245004800041210004600089260001800135100001600153700001400169856007200183 1995 eng d00aEquating the CAT-ASVAB: Issues and approach0 aEquating the CATASVAB Issues and approach aSan Francisco1 aSegall, D O1 aCarter, G uhttp://www.iacat.org/content/equating-cat-asvab-issues-and-approach00414nas a2200097 4500008004100000245008200041210006900123260000700192100001700199856010000216 1995 eng d00aEquating the computerized adaptive edition of the Differential Aptitude Tests0 aEquating the computerized adaptive edition of the Differential A aCA1 aMcBride, J R uhttp://www.iacat.org/content/equating-computerized-adaptive-edition-differential-aptitude-tests00401nas a2200097 4500008004100000245007400041210006900115100001300184700001100197856009500208 1995 eng d00aEstimation of item difficulty from restricted CAT calibration samples0 aEstimation of item difficulty from restricted CAT calibration sa1 aSykes, R1 aIto, K uhttp://www.iacat.org/content/estimation-item-difficulty-restricted-cat-calibration-samples00643nas a2200121 4500008004100000245013600041210006900177260010500246100001500351700001700366700001600383856012200399 1995 eng d00aAn evaluation of alternative concepts for administering the Armed Services Vocational Aptitude Battery to applicants for enlistment0 aevaluation of alternative concepts for administering the Armed S aDMDC Technical Report 95-013. Monterey, CA: Personnel Testing Division, Defense Manpower Data Center1 aHogan, P F1 aMcBride, J R1 aCurran, L T uhttp://www.iacat.org/content/evaluation-alternative-concepts-administering-armed-services-vocational-aptitude-battery00583nas a2200097 4500008004100000245007600041210006900117260019000186100001500376856009400391 1995 eng d00aFrom adaptive testing to automated scoring of architectural simulations0 aFrom adaptive testing to automated scoring of architectural simu aL. E. Mancall and P. G. Bashook (Eds.), Assessing clinical reasoning: The oral examination and alternative methods (pp. 115-130. Evanston IL: The American Board of Medical Specialities.1 aBejar, I I uhttp://www.iacat.org/content/adaptive-testing-automated-scoring-architectural-simulations00404nas a2200097 4500008004100000245006700041210006500108260002100173100001900194856009300213 1995 eng d00aA global information approach to computerized adaptive testing0 aglobal information approach to computerized adaptive testing aSan Francisco CA1 aChang, Hua-Hua uhttp://www.iacat.org/content/global-information-approach-computerized-adaptive-testing-000441nam a2200097 4500008004100000245007500041210006900116260002600185100003500211856009700246 1995 eng d00aGuidelines for computer-adaptive test development and use in education0 aGuidelines for computeradaptive test development and use in educ aWashington DC: Author1 aAmerican-Council-on-Education. uhttp://www.iacat.org/content/guidelines-computer-adaptive-test-development-and-use-education00636nas a2200097 4500008004100000245010900041210006900150260018000219100001400399856012500413 1995 eng d00aImproving individual differences measurement with item response theory and computerized adaptive testing0 aImproving individual differences measurement with item response  aD. Lubinski and R. V. Dawis (Eds.), Assessing individual differences in human behavior: New concepts, methods, and findings (pp. 49-79). Palo Alto CA: Davies-Black Publishing.1 aWeiss, DJ uhttp://www.iacat.org/content/improving-individual-differences-measurement-item-response-theory-and-computerized-adaptive00449nas a2200097 4500008004100000245004400041210004400085260013900129100001700268856006600285 1995 eng d00aIndividualized testing in the classroom0 aIndividualized testing in the classroom aAnderson, L.W. (Ed.), International Encyclopedia of Teaching and Teacher Education. Oxford, New York, Tokyo: Elsevier Science 295-299.1 aLinacre, J M uhttp://www.iacat.org/content/individualized-testing-classroom00477nas a2200109 4500008004100000245009500041210006900136260002100205100001100226700001600237856011400253 1995 eng d00aThe influence of examinee test-taking behavior motivation in computerized adaptive testing0 ainfluence of examinee testtaking behavior motivation in computer aSan Francisco CA1 aKim, J1 aMcLean, J E uhttp://www.iacat.org/content/influence-examinee-test-taking-behavior-motivation-computerized-adaptive-testing00648nas a2200133 4500008004100000245017200041210006900213260004600282100001900328700001700347700001500364700001300379856012200392 1995 eng d00aThe introduction and comparability of the computer-adaptive GRE General Test (GRE Board Professional Report 88-08ap; Educational Testing Service Research Report 95-20)0 aintroduction and comparability of the computeradaptive GRE Gener aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M L1 aMills, C N1 aDurso, R uhttp://www.iacat.org/content/introduction-and-comparability-computer-adaptive-gre-general-test-gre-board-professional00474nas a2200109 4500008004100000245009300041210006900134260002200203100001600225700001300241856011000254 1995 eng d00aAn investigation of item calibration procedures for a computerized licensure examination0 ainvestigation of item calibration procedures for a computerized  aSan Francisco, CA1 aHaynie, K A1 aWay, W D uhttp://www.iacat.org/content/investigation-item-calibration-procedures-computerized-licensure-examination00513nas a2200121 4500008004100000245011200041210006900153300001300222490000700235100001400242700001400256856012100270 1995 eng d00aAn investigation of procedures for computerized adaptive testing using the successive intervals Rasch model0 ainvestigation of procedures for computerized adaptive testing us a976-990.0 v551 aKoch, W R1 aDodd, B G uhttp://www.iacat.org/content/investigation-procedures-computerized-adaptive-testing-using-successive-intervals-rasch00446nam a2200097 4500008004100000245007200041210006900113260006100182100001200243856009300255 1995 eng d00aItem equivalence from paper-and-pencil to computer adaptive testing0 aItem equivalence from paperandpencil to computer adaptive testin aUnpublished doctoral dissertation, University of Chicago1 aChae, S uhttp://www.iacat.org/content/item-equivalence-paper-and-pencil-computer-adaptive-testing00506nas a2200121 4500008004100000245009100041210006900132260002100201100001600222700001300238700001700251856011600268 1995 eng d00aItem exposure rates for unconstrained and content-balanced computerized adaptive tests0 aItem exposure rates for unconstrained and contentbalanced comput aSan Francisco CA1 aMorrison, C1 aSubhiyah1 aNungester, R uhttp://www.iacat.org/content/item-exposure-rates-unconstrained-and-content-balanced-computerized-adaptive-tests00399nas a2200097 4500008004100000245006700041210006700108260001900175100001400194856009300208 1995 eng d00aItem review and answer changing in computerized adaptive tests0 aItem review and answer changing in computerized adaptive tests aTrier, Germany1 aWise, S L uhttp://www.iacat.org/content/item-review-and-answer-changing-computerized-adaptive-tests00431nas a2200109 4500008004100000245007100041210006900112300001200181490001800193100001600211856009400227 1995 eng d00aItem times in computerized testing: A new differential information0 aItem times in computerized testing A new differential informatio a108-1090 v11 (Suppl. 1)1 aHornke, L F uhttp://www.iacat.org/content/item-times-computerized-testing-new-differential-information00480nas a2200109 4500008004100000245009400041210006900135260002100204100001300225700001800238856011400256 1995 eng d00aNew algorithms for item selection and exposure control with computerized adaptive testing0 aNew algorithms for item selection and exposure control with comp aSan Francisco CA1 aDavey, T1 aParshall, C G uhttp://www.iacat.org/content/new-algorithms-item-selection-and-exposure-control-computerized-adaptive-testing00421nas a2200097 4500008004100000245007500041210006900116260001900185100001900204856010000223 1995 eng d00aNew item exposure control algorithms for computerized adaptive testing0 aNew item exposure control algorithms for computerized adaptive t aMinneapolis MN1 aThomasson, G L uhttp://www.iacat.org/content/new-item-exposure-control-algorithms-computerized-adaptive-testing00522nas a2200109 4500008004100000245010300041210006900144260004600213100001800259700001300277856012200290 1995 eng d00aA new method of controlling item exposure in computerized adaptive testing (Research Report 95-25)0 anew method of controlling item exposure in computerized adaptive aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/new-method-controlling-item-exposure-computerized-adaptive-testing-research-report-95-2500529nas a2200109 4500008004100000245010200041210006900143260004800212100001500260700001800275856012600293 1995 eng d00aPractical issues in large-scale high-stakes computerized adaptive testing (Research Report 95-23)0 aPractical issues in largescale highstakes computerized adaptive  aPrinceton, NJ: Educational Testing Service.1 aMills, C N1 aStocking, M L uhttp://www.iacat.org/content/practical-issues-large-scale-high-stakes-computerized-adaptive-testing-research-report-95-2300495nas a2200109 4500008004100000245012300041210006900164300001200233490000600245100001100251856012300262 1995 eng d00aPrecision and differential item functioning on a testlet-based test: The 1991 Law School Admissions Test as an example0 aPrecision and differential item functioning on a testletbased te a157-1870 v81 aWainer uhttp://www.iacat.org/content/precision-and-differential-item-functioning-testlet-based-test-1991-law-school-admissions00489nam a2200097 4500008004100000245008100041210006900122260008600191100001200277856010200289 1995 eng d00aThe precision of ability estimation methods in computerized adaptive testing0 aprecision of ability estimation methods in computerized adaptive aUnpublished doctoral dissertation, University of Iowa, Iowa City (UM No. 9945102)1 aWang, T uhttp://www.iacat.org/content/precision-ability-estimation-methods-computerized-adaptive-testing-000442nas a2200109 4500008004100000245007700041210006900118260001600187100001200203700001700215856010000232 1995 eng d00aPrecision of ability estimation methods in computerized adaptive testing0 aPrecision of ability estimation methods in computerized adaptive aMinneapolis1 aWang, T1 aVispoel, W P uhttp://www.iacat.org/content/precision-ability-estimation-methods-computerized-adaptive-testing00549nas a2200109 4500008004100000245007200041210006900113260013400182100001700316700001600333856009000349 1995 eng d00aPrerequisite relationships for the adaptive assessment of knowledge0 aPrerequisite relationships for the adaptive assessment of knowle aGreer, J. (Ed.) Proceedings of AIED'95, 7th World Conference on Artificial Intelligence in Education, Washington, DC, AACE 43-50.1 aDowling, C E1 aKaluscha, R uhttp://www.iacat.org/content/prerequisite-relationships-adaptive-assessment-knowledge00518nas a2200109 4500008004100000245009900041210006900140260004200209100001200251700001900263856012600282 1995 eng d00aRecursive maximum likelihood estimation, sequential designs, and computerized adaptive testing0 aRecursive maximum likelihood estimation sequential designs and c aUniversity of Twente, the Netherlands1 aYing, Z1 aChang, Hua-Hua uhttp://www.iacat.org/content/recursive-maximum-likelihood-estimation-sequential-designs-and-computerized-adaptive-testing00392nas a2200109 4500008004100000245006300041210006200104300001200166490000700178100001500185856008200200 1995 eng d00aReview of the book Computerized Adaptive Testing: A Primer0 aReview of the book Computerized Adaptive Testing A Primer a615-6200 v4?1 aAndrich, D uhttp://www.iacat.org/content/review-book-computerized-adaptive-testing-primer00369nas a2200085 4500008004100000245006700041210006700108100001800175856009000193 1995 eng d00aShortfall of questions curbs use of computerized graduate exam0 aShortfall of questions curbs use of computerized graduate exam1 aJacobson, R L uhttp://www.iacat.org/content/shortfall-questions-curbs-use-computerized-graduate-exam00443nas a2200097 4500008004100000245006900041210006700110260005700177100001500234856009600249 1995 eng d00aSome alternative CAT item selection heuristics (Internal report)0 aSome alternative CAT item selection heuristics Internal report aPhiladelphia PA: National Board of Medical Examiners1 aLuecht, RM uhttp://www.iacat.org/content/some-alternative-cat-item-selection-heuristics-internal-report00400nas a2200109 4500008004100000245005800041210005800099260001900157100001600176700001500192856008300207 1995 eng d00aSome new methods for content balancing adaptive tests0 aSome new methods for content balancing adaptive tests aMinneapolis MN1 aSegall, D O1 aDavey, T C uhttp://www.iacat.org/content/some-new-methods-content-balancing-adaptive-tests01697nas a2200229 4500008004100000020004100041245006400082210006200146250001500208260000800223300001100231490000700242520102000249653003101269653002501300653001001325653001101335653001101346653000901357100001601366856008501382 1995 jpn d a0021-5236 (Print)0021-5236 (Linking)00aA study of psychologically optimal level of item difficulty0 astudy of psychologically optimal level of item difficulty a1995/02/01 cFeb a446-530 v653 aFor the purpose of selecting items in a test, this study presented a viewpoint of psychologically optimal difficulty level, as well as measurement efficiency, of items. A paper-and-pencil test (P & P) composed of hard, moderate and easy subtests was administered to 298 students at a university. A computerized adaptive test (CAT) was also administered to 79 students. The items of both tests were selected from Shiba's Word Meaning Comprehension Test, for which the estimates of parameters of two-parameter item response model were available. The results of P & P research showed that the psychologically optimal success level would be such that the proportion of right answers is somewhere between .75 and .85. A similar result was obtained from CAT research, where the proportion of about .8 might be desirable. Traditionally a success rate of .5 has been recommended in adaptive testing. In this study, however, it was suggested that the items of such level would be too hard psychologically for many examinees.10a*Adaptation, Psychological10a*Psychological Tests10aAdult10aFemale10aHumans10aMale1 aFujimori, S uhttp://www.iacat.org/content/study-psychologically-optimal-level-item-difficulty00589nas a2200121 4500008004500000245017100045210006900216260001800285100001200303700001500315700001400330856012300344 1995 Spandsh 00aTests adaptivos y autoadaptados informatizados: Effects en la ansiedad y en la pecision de las estimaciones [SATs and CATS: Effects on enxiety and estimate precision]0 aTests adaptivos y autoadaptados informatizados Effects en la ans aMurcia, Spain1 aOlea, J1 aPonsoda, V1 aWise, S L uhttp://www.iacat.org/content/tests-adaptivos-y-autoadaptados-informatizados-effects-en-la-ansiedad-y-en-la-pecision-de00550nas a2200133 4500008004100000245012000041210006900161300001400230490000700244100001600251700001500267700001800282856011600300 1995 eng d00aTheoretical results and item selection from multidimensional item bank in the Mokken IRT model for polytomous items0 aTheoretical results and item selection from multidimensional ite a337–3520 v191 aHemker, B T1 aSijtsma, K1 aMolenaar, I W uhttp://www.iacat.org/content/theoretical-results-and-item-selection-multidimensional-item-bank-mokken-irt-model00506nas a2200109 4500008004100000245009300041210006900134260005300203100001300256700001500269856011200284 1995 eng d00aUsing simulation to select an adaptive testing strategy: An item bank evaluation program0 aUsing simulation to select an adaptive testing strategy An item  aUnpublished manuscript, University of Pittsburgh1 aHsu, T C1 aTseng, F L uhttp://www.iacat.org/content/using-simulation-select-adaptive-testing-strategy-item-bank-evaluation-program00484nas a2200133 4500008004100000245008100041210006900122300001200191490000700203100001500210700000900225700001600234856010000250 1994 eng d00aADTEST: A computer-adaptive tests based on the maximum information principle0 aADTEST A computeradaptive tests based on the maximum information a680-6860 v541 aPonsoda, V1 aOlea1 aRevuelta, J uhttp://www.iacat.org/content/adtest-computer-adaptive-tests-based-maximum-information-principle00355nam a2200097 4500008004100000245004200041210004100083260004700124100001600171856007000187 1994 eng d00aCAT software system [computer program0 aCAT software system computer program aChicago IL: Computer Adaptive Technologies1 aGershon, RC uhttp://www.iacat.org/content/cat-software-system-computer-program00344nas a2200097 4500008004100000245003200041210003100073260006500104100001600169856006100185 1994 eng d00aCAT-GATB simulation studies0 aCATGATB simulation studies aSan Diego CA: Navy Personnel Research and Development Center1 aSegall, D O uhttp://www.iacat.org/content/cat-gatb-simulation-studies00534nas a2200121 4500008004100000245011500041210006900156260001900225100001400244700001400258700001500272856012500287 1994 eng d00aComparing computerized adaptive and self-adapted tests: The influence of examinee achievement locus of control0 aComparing computerized adaptive and selfadapted tests The influe aNew Orleans LA1 aWise, S L1 aRoos, L L1 aPlake, B S uhttp://www.iacat.org/content/comparing-computerized-adaptive-and-self-adapted-tests-influence-examinee-achievement-locus00480nas a2200133 4500008004100000245007400041210006900115300001200184490000700196100001600203700001600219700001600235856009500251 1994 eng d00aA comparison of item calibration media in computerized adaptive tests0 acomparison of item calibration media in computerized adaptive te a197-2040 v181 aHetter, R D1 aSegall, D O1 aBloxom, B M uhttp://www.iacat.org/content/comparison-item-calibration-media-computerized-adaptive-tests00464nas a2200121 4500008004500000245007600045210006900121490000700190100001600197700001600213700001600229856009700245 1994 Engldsh 00aA Comparison of Item Calibration Media in Computerized Adaptive Testing0 aComparison of Item Calibration Media in Computerized Adaptive Te0 v181 aHetter, R D1 aSegall, D O1 aBloxom, B M uhttp://www.iacat.org/content/comparison-item-calibration-media-computerized-adaptive-testing00368nas a2200133 4500008004100000245003000041210003000071300001200101490000600113100001400119700002400133700001600157856006100173 1994 eng d00aComputer adaptive testing0 aComputer adaptive testing a623-6340 v61 aLunz, M E1 aBergstrom, Betty, A1 aGershon, RC uhttp://www.iacat.org/content/computer-adaptive-testing-100405nas a2200109 4500008004100000245006600041210006500107300001200172490001100184100001500195856008500210 1994 eng d00aComputer adaptive testing: A shift in the evaluation paradigm0 aComputer adaptive testing A shift in the evaluation paradigm a213-2240 v22 (3)1 aCarlson, R uhttp://www.iacat.org/content/computer-adaptive-testing-shift-evaluation-paradigm00398nas a2200121 4500008004100000245005600041210005500097300000800152490001000160100001400170700001500184856007700199 1994 eng d00aComputer adaptive testing: Assessment of the future0 aComputer adaptive testing Assessment of the future a1-30 v4 (2)1 aDiones, R1 aEverson, H uhttp://www.iacat.org/content/computer-adaptive-testing-assessment-future00496nas a2200109 4500008004100000245010200041210006900143260001900212100001700231700001600248856012200264 1994 eng d00aComputerized adaptive testing exploring examinee response time using hierarchical linear modeling0 aComputerized adaptive testing exploring examinee response time u aNew Orleans LA1 aBergstrom, B1 aGershon, RC uhttp://www.iacat.org/content/computerized-adaptive-testing-exploring-examinee-response-time-using-hierarchical-linear00452nas a2200121 4500008004100000245006600041210006600107300001000173490001600183100002400199700001600223856009100239 1994 eng d00aComputerized adaptive testing for licensure and certification0 aComputerized adaptive testing for licensure and certification a25-270 vWinter 19941 aBergstrom, Betty, A1 aGershon, RC uhttp://www.iacat.org/content/computerized-adaptive-testing-licensure-and-certification00426nas a2200109 4500008004100000245007100041210006900112300001000181490001100191100001500202856009900217 1994 eng d00aComputerized adaptive testing: Revolutionizing academic assessment0 aComputerized adaptive testing Revolutionizing academic assessmen a32-350 v65 (1)1 aSmittle, P uhttp://www.iacat.org/content/computerized-adaptive-testing-revolutionizing-academic-assessment00523nas a2200121 4500008004100000245008900041210006900130260004600199100001000245700001300255700001700268856011600285 1994 eng d00aComputerized mastery testing using fuzzy set decision theory (Research Report 94-37)0 aComputerized mastery testing using fuzzy set decision theory Res aPrinceton NJ: Educational Testing Service1 aDu, Y1 aLewis, C1 aPashley, P J uhttp://www.iacat.org/content/computerized-mastery-testing-using-fuzzy-set-decision-theory-research-report-94-3700373nas a2200097 4500008004100000245005000041210004600091260004600137100001600183856007600199 1994 eng d00aComputerized Testing (Research Report 94-22).0 aComputerized Testing Research Report 9422 aPrinceton NJ: Educational Testing Service1 aOltman, P K uhttp://www.iacat.org/content/computerized-testing-research-report-94-2200498nas a2200121 4500008004100000245010100041210006900142300001000211490000600221100001200227700001700239856012000256 1994 eng d00aComputerized-adaptive and self-adapted music-listening tests: Features and motivational benefits0 aComputerizedadaptive and selfadapted musiclistening tests Featur a25-510 v71 aVispoel1 aCoffman, D D uhttp://www.iacat.org/content/computerized-adaptive-and-self-adapted-music-listening-tests-features-and-motivational00567nas a2200121 4500008004100000245011900041210006900160260004700229100001300276700001600289700001700305856012300322 1994 eng d00aDIF analysis for pretest items in computer-adaptive testing (Educational Testing Service Research Rep No RR 94-33)0 aDIF analysis for pretest items in computeradaptive testing Educa aPrinceton NJ: Educational Testing Service.1 aZwick, R1 aThayer, D T1 aWingersky, M uhttp://www.iacat.org/content/dif-analysis-pretest-items-computer-adaptive-testing-educational-testing-service-research00355nas a2200097 4500008004100000245005700041210005600098260000700154100001700161856007900178 1994 eng d00aEarly psychometric research in the CAT-ASVAB Project0 aEarly psychometric research in the CATASVAB Project aCA1 aMcBride, J R uhttp://www.iacat.org/content/early-psychometric-research-cat-asvab-project00512nas a2200109 4500008004100000245013000041210006900171260001600240100001100256700001500267856012000282 1994 eng d00aThe effect of restricting ability distributions in the estimation of item difficulties: Implications for a CAT implementation0 aeffect of restricting ability distributions in the estimation of aNew Orleans1 aIto, K1 aSykes, R C uhttp://www.iacat.org/content/effect-restricting-ability-distributions-estimation-item-difficulties-implications-cat00477nas a2200121 4500008004100000245009200041210006900133300001200202490000600214100001500220700001400235856010600249 1994 eng d00aThe effect of review on the psychometric characteristics of computerized adaptive tests0 aeffect of review on the psychometric characteristics of computer a211-2220 v71 aStone, G E1 aLunz, M E uhttp://www.iacat.org/content/effect-review-psychometric-characteristics-computerized-adaptive-tests-000478nas a2200121 4500008004100000245009200041210006900133300001200202490000900214100001400223700001500237856010400252 1994 eng d00aThe effect of review on the psychometric characteristics of computerized adaptive tests0 aeffect of review on the psychometric characteristics of computer a211-2220 v7(3)1 aLunz, M E1 aStone, G E uhttp://www.iacat.org/content/effect-review-psychometric-characteristics-computerized-adaptive-tests01351nas a2200133 4500008004100000245009100041210006900132300001200201490000600213520086600219100001501085700001401100856010301114 1994 eng d00aThe effect of review on the psychometric characterstics of computerized adaptive tests0 aeffect of review on the psychometric characterstics of computeri a211-2220 v73 aExplored the effect of reviewing items and altering responses on examinee ability estimates, test precision, test information, decision confidence, and pass/fail status for computerized adaptive tests. Two different populations of examinees took different computerized certification examinations. For purposes of analysis, each population was divided into 3 ability groups (high, medium, and low). Ability measures before and after review were highly correlated, but slightly lower decision confidence was found after review. Pass/fail status was most affected for examinees with estimates close to the pass point. Decisions remained the same for 94% of the examinees. Test precision is only slightly affected by review, and the average information loss can be recovered by the addition of one item. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aStone, G E1 aLunz, M E uhttp://www.iacat.org/content/effect-review-psychometric-characterstics-computerized-adaptive-tests00511nam a2200097 4500008004100000245008400041210006900125260009300194100001900287856010700306 1994 eng d00aEffects of computerized adaptive test anxiety on nursing licensure examinations0 aEffects of computerized adaptive test anxiety on nursing licensu aDissertation Abstracts International, A (Humanities and Social Sciences), 54 (9-A), 34101 aArrowwood, V E uhttp://www.iacat.org/content/effects-computerized-adaptive-test-anxiety-nursing-licensure-examinations00460nas a2200109 4500008004100000245009400041210006900135260001600204100001600220700001300236856010100249 1994 eng d00aThe effects of item pool depth on the accuracy of pass/fail decisions for NCLEX using CAT0 aeffects of item pool depth on the accuracy of passfail decisions aNew Orleans1 aHaynie, K A1 aWay, W D uhttp://www.iacat.org/content/effects-item-pool-depth-accuracy-passfail-decisions-nclex-using-cat00490nas a2200133 4500008004100000245007900041210006900120260000800189300001200197490000700209100001400216700002400230856010200254 1994 eng d00aAn empirical study of computerized adaptive test administration conditions0 aempirical study of computerized adaptive test administration con cFal a251-2630 v311 aLunz, M E1 aBergstrom, Betty, A uhttp://www.iacat.org/content/empirical-study-computerized-adaptive-test-administration-conditions00609nas a2200145 4500008004100000245010000041210006900141260004400210300001200254490000600266653003400272100002400306700001400330856011900344 1994 eng d00aThe equivalence of Rasch item calibrations and ability estimates across modes of administration0 aequivalence of Rasch item calibrations and ability estimates acr aNorwood, N.J. USAbAblex Publishing Co. a122-1280 v210acomputerized adaptive testing1 aBergstrom, Betty, A1 aLunz, M E uhttp://www.iacat.org/content/equivalence-rasch-item-calibrations-and-ability-estimates-across-modes-administration00497nas a2200121 4500008004100000245009400041210006900135260002000204100001600224700001300240700001500253856010700268 1994 eng d00aEstablishing the comparability of the NCLEX using CAT with traditional NCLEX examinations0 aEstablishing the comparability of the NCLEX using CAT with tradi aNew Orleans, LA1 aEignor, D R1 aWay, W D1 aAmoss, K E uhttp://www.iacat.org/content/establishing-comparability-nclex-using-cat-traditional-nclex-examinations00363nas a2200109 4500008004100000245004700041210004600088260001600134100001600150700001400166856007300180 1994 eng d00aEvaluation and implementation of CAT-ASVAB0 aEvaluation and implementation of CATASVAB aLos Angeles1 aCurran, L T1 aWise, L L uhttp://www.iacat.org/content/evaluation-and-implementation-cat-asvab00474nam a2200097 4500008004100000245008100041210006900122260007400191100001500265856009600280 1994 eng d00aThe exploration of an alternative method for scoring computer adaptive tests0 aexploration of an alternative method for scoring computer adapti aUnpublished doctoral dissertation, Lincoln NE: University of Nebraska1 aPotenza, M uhttp://www.iacat.org/content/exploration-alternative-method-scoring-computer-adaptive-tests00430nas a2200097 4500008004100000245008400041210006900125260001800194100001500212856010500227 1994 eng d00aA few more issues to consider in multidimensional computerized adaptive testing0 afew more issues to consider in multidimensional computerized ada aSan Francisco1 aLuecht, RM uhttp://www.iacat.org/content/few-more-issues-consider-multidimensional-computerized-adaptive-testing00466nas a2200109 4500008004100000245009500041210006900136300001200205490000700217100001800224856011400242 1994 eng d00aA general approach to algorithmic design of fixed-form tests, adaptive tests, and testlets0 ageneral approach to algorithmic design of fixedform tests adapti a141-1530 v181 aBerger, M P F uhttp://www.iacat.org/content/general-approach-algorithmic-design-fixed-form-tests-adaptive-tests-and-testlets00472nas a2200109 4500008004500000245009500045210006900140300001200209490000700221100001800228856011600246 1994 Engldsh 00aA General Approach to Algorithmic Design of Fixed-Form Tests, Adaptive Tests, and Testlets0 aGeneral Approach to Algorithmic Design of FixedForm Tests Adapti a141-1530 v181 aBerger, M P F uhttp://www.iacat.org/content/general-approach-algorithmic-design-fixed-form-tests-adaptive-tests-and-testlets-000481nas a2200097 4500008004100000245010700041210006900148260002900217100001500246856012200261 1994 eng d00aThe historical developments of fit and its assessment in the computerized adaptive testing environment0 ahistorical developments of fit and its assessment in the compute aChicago, IL USAc10/19941 aStone, G E uhttp://www.iacat.org/content/historical-developments-fit-and-its-assessment-computerized-adaptive-testing-environment00524nas a2200121 4500008004100000245011800041210006900159300001200228490000700240100001800247700001600265856012100281 1994 eng d00aThe incomplete equivalence of the paper-and-pencil and computerized versions of the General Aptitude Test Battery0 aincomplete equivalence of the paperandpencil and computerized ve a852-8590 v791 aVan de Vijver1 aHarsveld, M uhttp://www.iacat.org/content/incomplete-equivalence-paper-and-pencil-and-computerized-versions-general-aptitude-test00571nas a2200133 4500008004100000245013900041210006900180300001000249490000600259100001700265700001700282700001200299856012600311 1994 eng d00aIndividual differences and test administration procedures: A comparison of fixed-item, computerized adaptive, and self-adapted testing0 aIndividual differences and test administration procedures A comp a53-790 v71 aVispoel, W P1 aRocklin, T R1 aWang, T uhttp://www.iacat.org/content/individual-differences-and-test-administration-procedures-comparison-fixed-item-computerized00508nas a2200109 4500008004100000245012100041210006900162260001900231100001500250700001400265856011900279 1994 eng d00aItem calibration considerations: A comparison of item calibrations on written and computerized adaptive examinations0 aItem calibration considerations A comparison of item calibration aNew Orleans LA1 aStone, G E1 aLunz, M E uhttp://www.iacat.org/content/item-calibration-considerations-comparison-item-calibrations-written-and-computerized00749nas a2200097 4500008004100000245025100041210007100292260013800363100001500501856013500516 1994 eng d00aLa simulation de modèle sur ordinateur en tant que méthode de recherche : le cas concret de l’étude de la distribution d’échantillonnage de l’estimateur du niveau d’habileté en testing adaptatif en fonction de deux règles d’arrêt0 aLa simulation de modèle sur ordinateur en tant que méthode de re aActes du 6e colloque de l‘Association pour la recherche au collégial. Montréal : Association pour la recherche au collégial, ARC1 aRaîche, G uhttp://www.iacat.org/content/la-simulation-de-mod%C3%A8le-sur-ordinateur-en-tant-que-m%C3%A9thode-de-recherche-le-cas-concret-de-l00500nas a2200097 4500008004100000245012400041210007200165100001500237700001500252856013500267 1994 eng d00aL'évaluation nationale individualisée et assistée par ordinateur [Large scale assessment: Tailored and computerized]0 aLévaluation nationale individualisée et assistée par ordinateur 1 aRaîche, G1 aBéland, A uhttp://www.iacat.org/content/l%C3%A9valuation-nationale-individualis%C3%A9e-et-assist%C3%A9e-par-ordinateur-large-scale-assessment00507nas a2200121 4500008004100000245009300041210006900134300000900203490000700212653003400219100001300253856011900266 1994 eng d00aMonte Carlo simulation comparison of two-stage testing and computerized adaptive testing0 aMonte Carlo simulation comparison of twostage testing and comput a25480 v5410acomputerized adaptive testing1 aKim, H-O uhttp://www.iacat.org/content/monte-carlo-simulation-comparison-two-stage-testing-and-computerized-adaptive-testing00497nas a2200133 4500008003900000245007500039210006900114260002000183100001600203700000900219700001300228700001800241856010400259 1994 d00aPinpointing PRAXIS I CAT characteristics through simulation procedures0 aPinpointing PRAXIS I CAT characteristics through simulation proc aNew Orleans, LA1 aEignor, D R1 aFolk1 aLi, M -Y1 aStocking, M L uhttp://www.iacat.org/content/pinpointing-praxis-i-cat-characteristics-through-simulation-procedures00415nas a2200109 4500008004100000245007100041210006700112300001000179490000700189100001600196856009300212 1994 eng d00aThe psychological impacts of computerized adaptive testing methods0 apsychological impacts of computerized adaptive testing methods a41-470 v341 aPowell, Z E uhttp://www.iacat.org/content/psychological-impacts-computerized-adaptive-testing-methods00530nas a2200145 4500008004100000245008600041210006900127300001000196490000600206100001400212700001400226700001000240700002700250856010700277 1994 eng d00aThe relationship between examinee anxiety and preference for self-adapted testing0 arelationship between examinee anxiety and preference for selfada a81-910 v71 aWise, S L1 aRoos, L L1 aPlake1 aNebelsick-Gullett, L J uhttp://www.iacat.org/content/relationship-between-examinee-anxiety-and-preference-self-adapted-testing00443nas a2200133 4500008004100000245005300041210005300094260002200147490000700169100001400176700002400190700001600214856007900230 1994 eng d00aReliability of alternate computer adaptive tests0 aReliability of alternate computer adaptive tests aNew JerseybAblex0 vII1 aLunz, M E1 aBergstrom, Betty, A1 aWright, B D uhttp://www.iacat.org/content/reliability-alternate-computer-adaptive-tests00448nas a2200109 4500008004100000245008200041210006900123260001900192100001500211700001700226856009500243 1994 eng d00aThe selection of test items for decision making with a computer adaptive test0 aselection of test items for decision making with a computer adap aNew Orleans LA1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/selection-test-items-decision-making-computer-adaptive-test-000446nas a2200109 4500008004100000245008200041210006900123260001900192100001700211700001500228856009300243 1994 eng d00aThe selection of test items for decision making with a computer adaptive test0 aselection of test items for decision making with a computer adap aNew Orleans LA1 aReckase, M D1 aSpray, J A uhttp://www.iacat.org/content/selection-test-items-decision-making-computer-adaptive-test00286nas a2200109 4500008004100000245002500041210002400066300000900090490000600099100001700105856005400122 1994 eng d00aSelf-adapted testing0 aSelfadapted testing a3-140 v71 aRocklin, T R uhttp://www.iacat.org/content/self-adapted-testing00435nas a2200097 4500008004100000245006800041210006600109260005100175100002000226856009100246 1994 eng d00aA simple and fast item selection procedure for adaptive testing0 asimple and fast item selection procedure for adaptive testing aResearch (Report 94-13). University of Twente.1 aVeerkamp, W J J uhttp://www.iacat.org/content/simple-and-fast-item-selection-procedure-adaptive-testing00548nas a2200133 4500008004500000245010900045210006900154300001200223490000700235100001300242700001600255700001700271856012600288 1994 Engldsh 00aA Simulation Study of Methods for Assessing Differential Item Functioning in Computerized Adaptive Tests0 aSimulation Study of Methods for Assessing Differential Item Func a121-1400 v181 aZwick, R1 aThayer, D T1 aWingersky, M uhttp://www.iacat.org/content/simulation-study-methods-assessing-differential-item-functioning-computerized-adaptive-tests00517nas a2200097 4500008004100000245012400041210006900165260004600234100001300280856012600293 1994 eng d00aA simulation study of the Mantel-Haenszel procedure for detecting DIF with the NCLEX using CAT (Technical Report xx-xx)0 asimulation study of the MantelHaenszel procedure for detecting D aPrinceton NJ: Educational Testing Service1 aWay, W D uhttp://www.iacat.org/content/simulation-study-mantel-haenszel-procedure-detecting-dif-nclex-using-cat-technical-report-xx00545nas a2200109 4500008004100000245007800041210006900119260011000188100001800298700001800316856010100334 1994 eng d00aSome new item selection criteria for adaptive testing (Research Rep 94-6)0 aSome new item selection criteria for adaptive testing Research R aEnschede, The Netherlands: University of Twente, Department of Educational Measurement and Data Analysis.1 aVeerkamp, W J1 aBerger, M P F uhttp://www.iacat.org/content/some-new-item-selection-criteria-adaptive-testing-research-rep-94-600474nas a2200097 4500008004100000245009000041210006900131260004600200100001800246856011200264 1994 eng d00aThree practical issues for modern adaptive testing item pools (Research Report 94-5),0 aThree practical issues for modern adaptive testing item pools Re aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/three-practical-issues-modern-adaptive-testing-item-pools-research-report-94-500420nas a2200109 4500008004100000245007300041210006900114300001000183490000600193100001400199856009700213 1994 eng d00aUnderstanding self-adapted testing: The perceived control hypothesis0 aUnderstanding selfadapted testing The perceived control hypothes a15-240 v71 aWise, S L uhttp://www.iacat.org/content/understanding-self-adapted-testing-perceived-control-hypothesis00679nas a2200097 4500008004100000245010900041210007000150260021800220100001500438856012800453 1994 eng d00aUtilisation de la simulation en tant que méthodologie de recherche [Simulation methodology in research]0 aUtilisation de la simulation en tant que méthodologie de recherc aAssociation pour la recherche au collégial (Ed.) : L'en-quête de la créativité [In quest of creativity]. Proceeding of the 6th Congress of the ARC. Montréal: Association pour la recherche au collégial (ARC).1 aRaîche, G uhttp://www.iacat.org/content/utilisation-de-la-simulation-en-tant-que-m%C3%A9thodologie-de-recherche-simulation-methodology00468nas a2200133 4500008004100000245007100041210006700112300001200179490000700191100001800198700001500216700001600231856008700247 1993 eng d00aThe application of an automated item selection method to real data0 aapplication of an automated item selection method to real data a167-1760 v171 aStocking, M L1 aSwanson, L1 aPearlman, M uhttp://www.iacat.org/content/application-automated-item-selection-method-real-data00501nas a2200121 4500008004100000245009700041210006900138300001400207490000700221653003400228100001200262856010500274 1993 eng d00aAn application of Computerized Adaptive Testing to the Test of English as a Foreign Language0 aapplication of Computerized Adaptive Testing to the Test of Engl a4257-42580 v5310acomputerized adaptive testing1 aMoon, O uhttp://www.iacat.org/content/application-computerized-adaptive-testing-test-english-foreign-language00513nas a2200133 4500008004100000245008100041210006900122300001000191490000700201653003400208100001900242700001600261856010200277 1993 eng d00aAssessing the utility of item response models: computerized adaptive testing0 aAssessing the utility of item response models computerized adapt a21-270 v1210acomputerized adaptive testing1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/assessing-utility-item-response-models-computerized-adaptive-testing00568nas a2200133 4500008004100000245009600041210006900137260004600206100001600252700001800268700001300286700001500299856012000314 1993 eng d00aCase studies in computer adaptive test design through simulation (Research Report RR-93-56)0 aCase studies in computer adaptive test design through simulation aPrinceton NJ: Educational Testing Service1 aEignor, D R1 aStocking, M L1 aWay, W D1 aSteffen, M uhttp://www.iacat.org/content/case-studies-computer-adaptive-test-design-through-simulation-research-report-rr-93-5600568nas a2200133 4500008004100000245009700041210006900138260004600207100001600253700001300269700001600282700001500298856012100313 1993 eng d00aCase studies in computerized adaptive test design through simulation (Research Report 93-56)0 aCase studies in computerized adaptive test design through simula aPrinceton NJ: Educational Testing Service1 aEignor, D R1 aWay, W D1 aStocking, M1 aSteffen, M uhttp://www.iacat.org/content/case-studies-computerized-adaptive-test-design-through-simulation-research-report-93-5600474nas a2200121 4500008004100000245008000041210006900121300000900190490000700199653003400206100001500240856009700255 1993 eng d00aComparability and validity of computerized adaptive testing with the MMPI-20 aComparability and validity of computerized adaptive testing with a37910 v5310acomputerized adaptive testing1 aRoper, B L uhttp://www.iacat.org/content/comparability-and-validity-computerized-adaptive-testing-mmpi-200433nam a2200097 4500008004100000245006600041210006400107260006100171100001300232856009000245 1993 eng d00aA comparison of computer adaptive test administration methods0 acomparison of computer adaptive test administration methods aUnpublished doctoral dissertation, University of Chicago1 aDolan, S uhttp://www.iacat.org/content/comparison-computer-adaptive-test-administration-methods00490nas a2200097 4500008004100000245012400041210006900165100001500234700001700249856012600266 1993 eng d00aComparison of SPRT and sequential Bayes procedures for classifying examinees into two categories using an adaptive test0 aComparison of SPRT and sequential Bayes procedures for classifyi1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/comparison-sprt-and-sequential-bayes-procedures-classifying-examinees-two-categories-using-000576nas a2200121 4500008004100000245015100041210006900192300000900261490000700270653003400277100001700311856012600328 1993 eng d00aComputer adaptive testing: A comparison of four item selection strategies when used with the golden section search strategy for estimating ability0 aComputer adaptive testing A comparison of four item selection st a17720 v5410acomputerized adaptive testing1 aCarlson, R D uhttp://www.iacat.org/content/computer-adaptive-testing-comparison-four-item-selection-strategies-when-used-golden-section00334nas a2200109 4500008004100000245004100041210004000082300000900122490001100131100001500142856006700157 1993 eng d00aComputer adaptive testing: A new era0 aComputer adaptive testing A new era a8-100 v17 (1)1 aSmittle, P uhttp://www.iacat.org/content/computer-adaptive-testing-new-era00434nas a2200109 4500008004100000245007800041210006900119300001200188490000700200100001700207856010000224 1993 eng d00aComputerized adaptive and fixed-item versions of the ITED Vocabulary test0 aComputerized adaptive and fixeditem versions of the ITED Vocabul a779-7880 v531 aVispoel, W P uhttp://www.iacat.org/content/computerized-adaptive-and-fixed-item-versions-ited-vocabulary-test00482nas a2200109 4500008004100000245009500041210006900136260002000205100001300225700001400238856012000252 1993 eng d00aComputerized adaptive testing in computer science: assessing student programming abilities0 aComputerized adaptive testing in computer science assessing stud aIndianapolis IN1 aSyang, A1 aDale, N B uhttp://www.iacat.org/content/computerized-adaptive-testing-computer-science-assessing-student-programming-abilities00412nas a2200121 4500008004100000245006000041210006000101300001000161490001000171100001000181700001300191856008600204 1993 eng d00aComputerized adaptive testing in instructional settings0 aComputerized adaptive testing in instructional settings a47-620 v41(3)1 aWelch1 aFrick, T uhttp://www.iacat.org/content/computerized-adaptive-testing-instructional-settings00561nam a2200097 4500008004100000245016500041210006900206260005500275100001200330856012100342 1993 eng d00aComputerized adaptive testing strategies: Golden section search, dichotomous search, and Z-score strategies (Doctoral dissertation, Iowa State University, 1990)0 aComputerized adaptive testing strategies Golden section search d aDissertation Abstracts International, 54-03B, 17201 aXiao, B uhttp://www.iacat.org/content/computerized-adaptive-testing-strategies-golden-section-search-dichotomous-search-and-z00733nas a2200241 4500008004100000020002200041245005700063210005600120250001500176260000800191300001100199490000700210653003500217653002400252653002900276653001900305653001100324653002700335653001800362100001800380700001500398856007800413 1993 eng d a0276-5284 (Print)00aComputerized adaptive testing: the future is upon us0 aComputerized adaptive testing the future is upon us a1993/09/01 cSep a378-850 v1410a*Computer-Assisted Instruction10a*Education, Nursing10a*Educational Measurement10a*Reaction Time10aHumans10aPharmacology/education10aPsychometrics1 aHalkitis, P N1 aLeahy, J M uhttp://www.iacat.org/content/computerized-adaptive-testing-future-upon-us01367nas a2200145 4500008004100000245013200041210006900173300001100242490000700253520078900260100001401049700001401063700002001077856012401097 1993 eng d00aComputerized adaptive testing using the partial credit model: Effects of item pool characteristics and different stopping rules0 aComputerized adaptive testing using the partial credit model Eff a61-77.0 v533 aSimulated datasets were used to research the effects of the systematic variation of three major variables on the performance of computerized adaptive testing (CAT) procedures for the partial credit model. The three variables studied were the stopping rule for terminating the CATs, item pool size, and the distribution of the difficulty of the items in the pool. Results indicated that the standard error stopping rule performed better across the variety of CAT conditions than the minimum information stopping rule. In addition it was found that item pools that consisted of as few as 30 items were adequate for CAT provided that the item pool was of medium difficulty. The implications of these findings for implementing CAT systems based on the partial credit model are discussed. 1 aDodd, B G1 aKoch, W R1 ade Ayala, R. J. uhttp://www.iacat.org/content/computerized-adaptive-testing-using-partial-credit-model-effects-item-pool-characteristics00457nas a2200133 4500008004100000245006500041210006500106300001200171490000600183100001000189700001300199700001700212856009400229 1993 eng d00aComputerized mastery testing using fuzzy set decision theory0 aComputerized mastery testing using fuzzy set decision theory a181-1930 v61 aDu, Y1 aLewis, C1 aPashley, P J uhttp://www.iacat.org/content/computerized-mastery-testing-using-fuzzy-set-decision-theory00494nas a2200097 4500008004100000245010000041210006900141260004600210100001800256856012200274 1993 eng d00aControlling item exposure rates in a realistic adaptive testing paradigm (Research Report 93-2)0 aControlling item exposure rates in a realistic adaptive testing  aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/controlling-item-exposure-rates-realistic-adaptive-testing-paradigm-research-report-93-200491nas a2200097 4500008004100000245010200041210006900143260004600212100001600258856011900274 1993 eng d00aDeriving comparable scores for computer adaptive and conventional tests: An example using the SAT0 aDeriving comparable scores for computer adaptive and conventiona aPrinceton NJ: Educational Testing Service1 aEignor, D R uhttp://www.iacat.org/content/deriving-comparable-scores-computer-adaptive-and-conventional-tests-example-using-sat00439nas a2200109 4500008004100000245008300041210006900124300001200193490000700205100001700212856010000229 1993 eng d00aThe development and evaluation of a computerized adaptive test of tonal memory0 adevelopment and evaluation of a computerized adaptive test of to a111-1360 v411 aVispoel, W P uhttp://www.iacat.org/content/development-and-evaluation-computerized-adaptive-test-tonal-memory00533nas a2200121 4500008004100000245011600041210006900157260001500226100001700241700001200258700001500270856012600285 1993 eng d00aThe efficiency, reliability, and concurrent validity of adaptive and fixed-item tests of music listening skills0 aefficiency reliability and concurrent validity of adaptive and f aAtlanta GA1 aVispoel, W P1 aWang, T1 aBleiler, T uhttp://www.iacat.org/content/efficiency-reliability-and-concurrent-validity-adaptive-and-fixed-item-tests-music-listening00385nas a2200097 4500008004100000245006500041210006500106260001500171100001500186856008600201 1993 eng d00aEstablishing time limits for the GRE computer adaptive tests0 aEstablishing time limits for the GRE computer adaptive tests aAtlanta GA1 aReese, C M uhttp://www.iacat.org/content/establishing-time-limits-gre-computer-adaptive-tests00645nas a2200145 4500008004100000245014000041210006900181260004700250100001900297700001500316700001500331700001800346700001500364856012000379 1993 eng d00aField test of a computer-based GRE general test (GRE Board Technical Report 88-8; Educational Testing Service Research Rep No RR 93-07)0 aField test of a computerbased GRE general test GRE Board Technic aPrinceton NJ: Educational Testing Service.1 aSchaeffer, G A1 aReese, C M1 aSteffen, M1 aMcKinley, R L1 aMills, C N uhttp://www.iacat.org/content/field-test-computer-based-gre-general-test-gre-board-technical-report-88-8-educational00521nas a2200109 4500008004100000245012600041210006900167260001500236100001700251700001700268856012600285 1993 eng d00aIndividual differences and test administration procedures: A comparison of fixed-item, adaptive, and self-adapted testing0 aIndividual differences and test administration procedures A comp aAtlanta GA1 aVispoel, W P1 aRocklin, T R uhttp://www.iacat.org/content/individual-differences-and-test-administration-procedures-comparison-fixed-item-adaptive-and00375nas a2200097 4500008004100000245006000041210006000101260001900161100001100180856008600191 1993 eng d00aIndividual differences in computerized adaptive testing0 aIndividual differences in computerized adaptive testing aNew Orleans LA1 aKim, J uhttp://www.iacat.org/content/individual-differences-computerized-adaptive-testing00517nas a2200121 4500008004100000245008100041210006900122260004600191100001900237700001500256700002100271856010300292 1993 eng d00aIntroduction of a computer adaptive GRE General test (Research Report 93-57)0 aIntroduction of a computer adaptive GRE General test Research Re aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M1 aGolub-Smith, M L uhttp://www.iacat.org/content/introduction-computer-adaptive-gre-general-test-research-report-93-5700414nas a2200121 4500008004100000245005600041210005200097260001500149100001400164700001900178700001600197856007900213 1993 eng d00aAn investigation of restricted self-adapted testing0 ainvestigation of restricted selfadapted testing aAtlanta GA1 aWise, S L1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/investigation-restricted-self-adapted-testing00543nas a2200121 4500008004100000245009600041210006900137260005100206100001600257700001600273700001600289856011600305 1993 eng d00aItem Calibration: Medium-of-administration effect on computerized adaptive scores (TR-93-9)0 aItem Calibration Mediumofadministration effect on computerized a aNavy Personnel Research and Development Center1 aHetter, R D1 aBloxom, B M1 aSegall, D O uhttp://www.iacat.org/content/item-calibration-medium-administration-effect-computerized-adaptive-scores-tr-93-900485nas a2200097 4500008004100000245004300041210004300084260017300127100001500300856007200315 1993 eng d00aLes tests adaptatifs en langue seconde0 aLes tests adaptatifs en langue seconde aCommunication lors de la 16e session d’étude de l’ADMÉÉ à Laval. Montréal: Association pour le développement de la mesure et de l’évaluation en éducation.1 aLaurier, M uhttp://www.iacat.org/content/les-tests-adaptatifs-en-langue-seconde00549nas a2200121 4500008004100000245014600041210006900187300001200256490000700268100001400275700001500289856012300304 1993 eng d00aLinking the standard and advanced forms of the Ravens Progressive Matrices in both the paper-and-pencil and computer-adaptive-testing formats0 aLinking the standard and advanced forms of the Ravens Progressiv a905-9250 v531 aStyles, I1 aAndrich, D uhttp://www.iacat.org/content/linking-standard-and-advanced-forms-ravens-progressive-matrices-both-paper-and-pencil-and00445nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001500215856009300230 1993 eng d00aA method for severely constrained item selection in adaptive testing0 amethod for severely constrained item selection in adaptive testi a277-2920 v171 aStocking1 aSwanson, L uhttp://www.iacat.org/content/method-severely-constrained-item-selection-adaptive-testing00456nas a2200121 4500008004500000245007300045210006900118300001200187490000700199100001800206700001500224856009500239 1993 Engldsh 00aA Method for Severely Constrained Item Selection in Adaptive Testing0 aMethod for Severely Constrained Item Selection in Adaptive Testi a277-2920 v171 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/method-severely-constrained-item-selection-adaptive-testing-100448nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001500215856009600230 1993 eng d00aA model and heuristic for solving very large item selection problems0 amodel and heuristic for solving very large item selection proble a151-1660 v171 aStocking1 aSwanson, L uhttp://www.iacat.org/content/model-and-heuristic-solving-very-large-item-selection-problems00326nas a2200097 4500008004100000245004100041210004100082260001700123100001800140856007000158 1993 eng d00aModern computerized adaptive testing0 aModern computerized adaptive testing aPrinceton NJ1 aStocking, M L uhttp://www.iacat.org/content/modern-computerized-adaptive-testing00476nas a2200109 4500008004100000245009300041210006900134260001600203100001100219700001500230856012100245 1993 eng d00aMonte Carlo simulation comparison of two-stage testing and computerized adaptive testing0 aMonte Carlo simulation comparison of twostage testing and comput aAtlanta, GA1 aKim, H1 aPlake, B S uhttp://www.iacat.org/content/monte-carlo-simulation-comparison-two-stage-testing-and-computerized-adaptive-testing-000757nas a2200241 4500008004100000020002200041245006700063210006400130250001500194260000800209300001100217490000700228653001500235653002600250653003700276653002300313653001800336100002100354700001400375700002400389700001400413856008800427 1993 eng d a0744-6314 (Print)00aMoving in a new direction: Computerized adaptive testing (CAT)0 aMoving in a new direction Computerized adaptive testing CAT a1993/01/01 cJan a80, 820 v2410a*Computers10aAccreditation/methods10aEducational Measurement/*methods10aLicensure, Nursing10aUnited States1 aJones-Dickson, C1 aDorsey, D1 aCampbell-Warnock, J1 aFields, F uhttp://www.iacat.org/content/moving-new-direction-computerized-adaptive-testing-cat00491nas a2200097 4500008004100000245010200041210006900143260004100212100001500253856012500268 1993 eng d00aMultiple-category classification using a sequential probability ratio test (Research report 93-7)0 aMultiplecategory classification using a sequential probability r aIowa City: American College Testing.1 aSpray, J A uhttp://www.iacat.org/content/multiple-category-classification-using-sequential-probability-ratio-test-research-report-9300430nas a2200121 4500008004100000245006600041210006600107250000600173300001400179490000700193100001800200856009000218 1993 eng d00aNew computer technique seen producing a revolution in testing0 aNew computer technique seen producing a revolution in testing a4 a22-23, 260 v401 aJacobson, R L uhttp://www.iacat.org/content/new-computer-technique-seen-producing-revolution-testing00455nas a2200097 4500008004100000245009900041210006900140100001900209700001600228856011300244 1993 eng d00aA practical examination of the use of free-response questions in computerized adaptive testing0 apractical examination of the use of freeresponse questions in co1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/practical-examination-use-free-response-questions-computerized-adaptive-testing00526nas a2200121 4500008004100000245011500041210006900156260001200225100001800237700001700255700001400272856011800286 1993 eng d00aA simulated comparison of testlets and a content balancing procedure for an adaptive certification examination0 asimulated comparison of testlets and a content balancing procedu aAtlanta1 aReshetar, R A1 aNorcini, J J1 aShea, J A uhttp://www.iacat.org/content/simulated-comparison-testlets-and-content-balancing-procedure-adaptive-certification00563nas a2200121 4500008004100000245014400041210006900185260001200254100001800266700001700284700001400301856012600315 1993 eng d00aA simulated comparison of two content balancing and maximum information item selection procedures for an adaptive certification examination0 asimulated comparison of two content balancing and maximum inform aAtlanta1 aReshetar, R A1 aNorcini, J J1 aShea, J A uhttp://www.iacat.org/content/simulated-comparison-two-content-balancing-and-maximum-information-item-selection-procedures00605nas a2200121 4500008004100000245016000041210006900201260004700270100001300317700001400330700001700344856012200361 1993 eng d00aA simulation study of methods for assessing differential item functioning in computer-adaptive tests (Educational Testing Service Research Rep No RR 93-11)0 asimulation study of methods for assessing differential item func aPrinceton NJ: Educational Testing Service.1 aZwick, R1 aThayer, D1 aWingersky, M uhttp://www.iacat.org/content/simulation-study-methods-assessing-differential-item-functioning-computer-adaptive-tests00434nas a2200097 4500008004100000245008800041210006900129260001700198100001300215856010800228 1993 eng d00aSome initial experiments with adaptive survey designs for structured questionnaires0 aSome initial experiments with adaptive survey designs for struct aCambridge MA1 aSingh, J uhttp://www.iacat.org/content/some-initial-experiments-adaptive-survey-designs-structured-questionnaires00475nas a2200109 4500008004100000245010100041210006900142300001000211490001100221100001100232856012200243 1993 eng d00aSome practical considerations when converting a linearly administered test to an adaptive format0 aSome practical considerations when converting a linearly adminis a15-200 v12 (1)1 aWainer uhttp://www.iacat.org/content/some-practical-considerations-when-converting-linearly-administered-test-adaptive-format00487nas a2200121 4500008004100000245008400041210006900125260001500194100001400209700001500223700002400238856010300262 1993 eng d00aTest targeting and precision before and after review on computer-adaptive tests0 aTest targeting and precision before and after review on computer aAtlanta GA1 aLunz, M E1 aStahl, J A1 aBergstrom, Betty, A uhttp://www.iacat.org/content/test-targeting-and-precision-and-after-review-computer-adaptive-tests00478nas a2200097 4500008004100000245007100041210006900112260008600181100001500267856009800282 1993 eng d00aUn test adaptatif en langue seconde : la perception des apprenants0 aUn test adaptatif en langue seconde la perception des apprenants aR.Hivon (Éd.),L’évaluation des apprentissages. Sherbrooke : Éditions du CRP.1 aLaurier, M uhttp://www.iacat.org/content/un-test-adaptatif-en-langue-seconde-la-perception-des-apprenants00468nas a2200097 4500008003900000245010200039210006900141260001800210100001700228856012500245 1992 d00aAbility measure equivalence of computer adaptive and paper and pencil tests: A research synthesis0 aAbility measure equivalence of computer adaptive and paper and p aSan Francisco1 aBergstrom, B uhttp://www.iacat.org/content/ability-measure-equivalence-computer-adaptive-and-paper-and-pencil-tests-research-synthesis01220nas a2200157 4500008004100000245006600041210006600107300001200173490000600185520069800191653003400889100002400923700001400947700001600961856008500977 1992 eng d00aAltering the level of difficulty in computer adaptive testing0 aAltering the level of difficulty in computer adaptive testing a137-1490 v53 aExamines the effect of altering test difficulty on examinee ability measures and test length in a computer adaptive test. The 225 Ss were randomly assigned to 3 test difficulty conditions and given a variable length computer adaptive test. Examinees in the hard, medium, and easy test condition took a test targeted at the 50%, 60%, or 70% probability of correct response. The results show that altering the probability of a correct response does not affect estimation of examinee ability and that taking an easier computer adaptive test only slightly increases the number of items necessary to reach specified levels of precision. (PsycINFO Database Record (c) 2002 APA, all rights reserved).10acomputerized adaptive testing1 aBergstrom, Betty, A1 aLunz, M E1 aGershon, RC uhttp://www.iacat.org/content/altering-level-difficulty-computer-adaptive-testing00418nas a2200121 4500008004100000245006300041210005900104300001000163490000700173100001800180700001600198856008200214 1992 eng d00aThe application of latent class models in adaptive testing0 aapplication of latent class models in adaptive testing a71-880 v571 aMacready, G B1 aDayton, C M uhttp://www.iacat.org/content/application-latent-class-models-adaptive-testing00410nas a2200097 4500008004100000245006900041210006900110100002400179700001500203856009400218 1992 eng d00aAssessing existing item bank depth for computer adaptive testing0 aAssessing existing item bank depth for computer adaptive testing1 aBergstrom, Betty, A1 aStahl, J A uhttp://www.iacat.org/content/assessing-existing-item-bank-depth-computer-adaptive-testing00306nas a2200121 4500008004100000245002400041210002300065300001000088490000600098100001100104700001600115856005300131 1992 eng d00aCAT-ASVAB precision0 aCATASVAB precision a22-260 v11 aMoreno1 aSegall, D O uhttp://www.iacat.org/content/cat-asvab-precision00490nas a2200097 4500008004100000245012700041210006900168260002100237100001200258856012200270 1992 eng d00aA comparison of computerized adaptive and paper-and-pencil versions of the national registered nurse licensure examination0 acomparison of computerized adaptive and paperandpencil versions  aSan Francisco CA1 aZara, A uhttp://www.iacat.org/content/comparison-computerized-adaptive-and-paper-and-pencil-versions-national-registered-nurse00441nas a2200109 4500008004100000245007300041210006900114260002100183100001700204700001600221856009400237 1992 eng d00aComparison of item targeting strategies for pass/fail adaptive tests0 aComparison of item targeting strategies for passfail adaptive te aSan Francisco CA1 aBergstrom, B1 aGershon, RC uhttp://www.iacat.org/content/comparison-item-targeting-strategies-passfail-adaptive-tests00455nam a2200097 4500008004100000245008000041210006900121260005900190100001300249856009500262 1992 eng d00aA comparison of methods for adaptive estimation of a multidimensional trait0 acomparison of methods for adaptive estimation of a multidimensio aUnpublished doctoral dissertation, Columbia University1 aTam, S S uhttp://www.iacat.org/content/comparison-methods-adaptive-estimation-multidimensional-trait00513nas a2200145 4500008004100000245007700041210006900118300001200187490000700199100001400206700001500220700001700235700001400252856010100266 1992 eng d00aA comparison of self-adapted and computerized adaptive achievement tests0 acomparison of selfadapted and computerized adaptive achievement  a329-3390 v291 aWise, S L1 aPlake, S S1 aJohnson, P L1 aRoos, S L uhttp://www.iacat.org/content/comparison-self-adapted-and-computerized-adaptive-achievement-tests00521nas a2200133 4500008004100000245009900041210006900140300001000209490000600219100001800225700001400243700001400257856011600271 1992 eng d00aA comparison of the partial credit and graded response models in computerized adaptive testing0 acomparison of the partial credit and graded response models in c a17-340 v51 aDe Ayala, R J1 aDodd, B G1 aKoch, W R uhttp://www.iacat.org/content/comparison-partial-credit-and-graded-response-models-computerized-adaptive-testing00482nas a2200133 4500008004100000245008200041210006900123300001200192490000700204100001100211700001400222700001300236856009900249 1992 eng d00aA comparison of the performance of simulated hierarchical and linear testlets0 acomparison of the performance of simulated hierarchical and line a243-2510 v291 aWainer1 aKaplan, B1 aLewis, C uhttp://www.iacat.org/content/comparison-performance-simulated-hierarchical-and-linear-testlets00400nam a2200097 4500008004100000245005200041210005000093260006100143100001700204856008100221 1992 eng d00aComputer adaptive versus paper-and-pencil tests0 aComputer adaptive versus paperandpencil tests aUnpublished doctoral dissertation, University of Chicago1 aBergstrom, B uhttp://www.iacat.org/content/computer-adaptive-versus-paper-and-pencil-tests00419nas a2200109 4500008004100000245007000041210006900111300001000180490000700190100001600197856009600213 1992 eng d00aComputer-based adaptive testing in music research and instruction0 aComputerbased adaptive testing in music research and instruction a49-630 v101 aBowers, D R uhttp://www.iacat.org/content/computer-based-adaptive-testing-music-research-and-instruction00443nas a2200097 4500008004100000245008200041210006900123260003000192100001500222856010800237 1992 eng d00aComputerized adaptive assessment of cognitive abilities among disabled adults0 aComputerized adaptive assessment of cognitive abilities among di aERIC Document No ED3012741 aEngdahl, B uhttp://www.iacat.org/content/computerized-adaptive-assessment-cognitive-abilities-among-disabled-adults00389nas a2200109 4500008004100000245005800041210005800099300001200157490000900169100001500178856008600193 1992 eng d00aComputerized adaptive mastery tests as expert systems0 aComputerized adaptive mastery tests as expert systems a187-2130 v8(2)1 aFrick, T W uhttp://www.iacat.org/content/computerized-adaptive-mastery-tests-expert-systems-000385nas a2200109 4500008004100000245005800041210005800099300001300157490000600170100001500176856008400191 1992 eng d00aComputerized adaptive mastery tests as expert systems0 aComputerized adaptive mastery tests as expert systems a187-213.0 v81 aFrick, T W uhttp://www.iacat.org/content/computerized-adaptive-mastery-tests-expert-systems00614nas a2200205 4500008004100000020002200041245004700063210004600110250001500156260000800171300000900179490000700188653001500195653002800210653003700238653001100275653003400286100001600320856007200336 1992 eng d a0022-3867 (Print)00aComputerized adaptive testing for NCLEX-PN0 aComputerized adaptive testing for NCLEXPN a1992/06/01 cJun a8-100 v4210a*Licensure10a*Programmed Instruction10aEducational Measurement/*methods10aHumans10aNursing, Practical/*education1 aFields, F A uhttp://www.iacat.org/content/computerized-adaptive-testing-nclex-pn00497nas a2200109 4500008004100000245011500041210006900156300001200225490000600237100001900243856012500262 1992 eng d00aComputerized adaptive testing: Its potential substantive contribution to psychological research and assessment0 aComputerized adaptive testing Its potential substantive contribu a129-1330 v11 aEmbretson, S E uhttp://www.iacat.org/content/computerized-adaptive-testing-its-potential-substantive-contribution-psychological-research00409nas a2200121 4500008004100000245005800041210005700099300001000156490000800166100001200174700001700186856008400203 1992 eng d00aComputerized adaptive testing of music-related skills0 aComputerized adaptive testing of musicrelated skills a29-490 v1121 aVispoel1 aCoffman, D D uhttp://www.iacat.org/content/computerized-adaptive-testing-music-related-skills00399nas a2200121 4500008004100000245005600041210005600097300001000153490001100163100000900174700001400183856008000197 1992 eng d00aComputerized adaptive testing with different groups0 aComputerized adaptive testing with different groups a23-270 v11 (2)1 aLegg1 aBuhr, D C uhttp://www.iacat.org/content/computerized-adaptive-testing-different-groups00527nas a2200109 4500008004100000245012700041210006900168260001900237100002000256700001500276856012600291 1992 eng d00aComputerized adaptive testing with the MMPI-2: Reliability, validity, and comparability to paper and pencil administration0 aComputerized adaptive testing with the MMPI2 Reliability validit aMinneapolis MN1 aBen-Porath, Y S1 aRoper, B L uhttp://www.iacat.org/content/computerized-adaptive-testing-mmpi-2-reliability-validity-and-comparability-paper-and-pencil00421nas a2200121 4500008004500000245006100045210006100106300001000167490000700177100001500184700001300199856008700212 1992 Engldsh 00aComputerized Mastery Testing With Nonequivalent Testlets0 aComputerized Mastery Testing With Nonequivalent Testlets a65-760 v161 aSheehan, K1 aLewis, C uhttp://www.iacat.org/content/computerized-mastery-testing-nonequivalent-testlets-000412nas a2200121 4500008004100000245006100041210006100102300001000163490000700173100001200180700001300192856008500205 1992 eng d00aComputerized mastery testing with nonequivalent testlets0 aComputerized mastery testing with nonequivalent testlets a65-760 v161 aSheehan1 aLewis, C uhttp://www.iacat.org/content/computerized-mastery-testing-nonequivalent-testlets01198nas a2200133 4500008004100000245009400041210006900135300001200204490000700216520068800223100002400911700001400935856011500949 1992 eng d00aConfidence in pass/fail decisions for computer adaptive and paper and pencil examinations0 aConfidence in passfail decisions for computer adaptive and paper a453-4640 v153 aCompared the level of confidence in pass/fail decisions obtained with computer adaptive tests (CADTs) and pencil-and-paper tests (PPTs). 600 medical technology students took a variable-length CADT and 2 fixed-length PPTs. The CADT was stopped when the examinee ability estimate was either 1.3 times the standard error of measurement above or below the pass/fail point or when a maximum test length was reached. Results show that greater confidence in the accuracy of the pass/fail decisions was obtained for more examinees when the CADT implemented a 90% confidence stopping rule than with PPTs of comparable test length. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aBergstrom, Betty, A1 aLunz, M E uhttp://www.iacat.org/content/confidence-passfail-decisions-computer-adaptive-and-paper-and-pencil-examinations00477nas a2200109 4500008004100000245009400041210006900135300001200204490001000216100002400226856011700250 1992 eng d00aConfidence in pass/fail decisions for computer adaptive and paper and pencil examinations0 aConfidence in passfail decisions for computer adaptive and paper a435-4640 v15(4)1 aBergstrom, Betty, A uhttp://www.iacat.org/content/confidence-passfail-decisions-computer-adaptive-and-paper-and-pencil-examinations-100474nas a2200109 4500008004100000245009400041210006900135300001200204490000700216100002400223856011700247 1992 eng d00aConfidence in pass/fail decisions for computer adaptive and paper and pencil examinations0 aConfidence in passfail decisions for computer adaptive and paper a435-4640 v151 aBergstrom, Betty, A uhttp://www.iacat.org/content/confidence-passfail-decisions-computer-adaptive-and-paper-and-pencil-examinations-000481nas a2200121 4500008004100000245008100041210006900122300000900191490000700200653003400207100002100241856009700262 1992 eng d00aThe development and evaluation of a system for computerized adaptive testing0 adevelopment and evaluation of a system for computerized adaptive a43040 v5210acomputerized adaptive testing1 aTorre Sanchez, R uhttp://www.iacat.org/content/development-and-evaluation-system-computerized-adaptive-testing00516nas a2200109 4500008004100000245005600041210005200097260014600149100001700295700001600312856007800328 1992 eng d00aThe development of alternative operational concepts0 adevelopment of alternative operational concepts aProceedings of the 34th Annual Conference of the Military Testing Association. San Diego, CA: Navy Personnel Research and Development Center.1 aMcBride, J R1 aCurran, L T uhttp://www.iacat.org/content/development-alternative-operational-concepts00465nas a2200097 4500008004100000245010100041210006900142260001700211100001300228856012600241 1992 eng d00aDifferential item functioning analysis for computer-adaptive tests and other IRT-scored measures0 aDifferential item functioning analysis for computeradaptive test aSan Diego CA1 aZwick, R uhttp://www.iacat.org/content/differential-item-functioning-analysis-computer-adaptive-tests-and-other-irt-scored-measures01335nas a2200145 4500008004100000245009600041210006900137300001000206490000700216520079300223100001401016700002401030700002401054856011101078 1992 eng d00aThe effect of review on student ability and test efficiency for computerized adaptive tests0 aeffect of review on student ability and test efficiency for comp a33-400 v163 a220 students were randomly assigned to a review condition for a medical technology test; their test instructions indicated that each item must be answered when presented, but that the responses could be reviewed and altered at the end of the test. A sample of 492 students did not have the opportunity to review and alter responses. Within the review condition, examinee ability estimates before and after review were correlated .98. The average efficiency of the test was decreased by 1% after review. Approximately 32% of the examinees improved their ability estimates after review but did not change their pass/fail status. Disallowing review on adaptive tests administered under these rules is not supported by these data. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aLunz, M E1 aBergstrom, Betty, A1 aWright, Benjamin, D uhttp://www.iacat.org/content/effect-review-student-ability-and-test-efficiency-computerized-adaptive-tests00522nas a2200133 4500008004500000245009600045210006900141300001000210490000700220100001400227700001800241700001600259856011300275 1992 Engldsh 00aThe Effect of Review on Student Ability and Test Efficiency for Computerized Adaptive Tests0 aEffect of Review on Student Ability and Test Efficiency for Comp a33-400 v161 aLunz, M E1 aBerstrom, B A1 aWright, B D uhttp://www.iacat.org/content/effect-review-student-ability-and-test-efficiency-computerized-adaptive-tests-000475nas a2200121 4500008004100000245007600041210006900117260001800186100001500204700002100219700001700240856009600257 1992 eng d00aEffects of feedback during self-adapted testing on estimates of ability0 aEffects of feedback during selfadapted testing on estimates of a aSan Francisco1 aHolst, P M1 aO’Donnell, A M1 aRocklin, T R uhttp://www.iacat.org/content/effects-feedback-during-self-adapted-testing-estimates-ability00464nas a2200121 4500008004100000245007600041210006900117260001800186100001400204700001500218700001400233856009500247 1992 eng d00aThe effects of feedback in computerized adaptive and self-adapted tests0 aeffects of feedback in computerized adaptive and selfadapted tes aSan Francisco1 aRoos, L L1 aPlake, B S1 aWise, S L uhttp://www.iacat.org/content/effects-feedback-computerized-adaptive-and-self-adapted-tests00431nas a2200097 4500008004100000245008800041210006900129260001200198100001500210856010800225 1992 eng d00aEstimation of ability level by using only observable quantities in adaptive testing0 aEstimation of ability level by using only observable quantities  aChicago1 aKirisci, L uhttp://www.iacat.org/content/estimation-ability-level-using-only-observable-quantities-adaptive-testing00508nas a2200109 4500008004100000245005100041210005100092260014600143100001700289700001500306856007700321 1992 eng d00aEvaluation of alternative operational concepts0 aEvaluation of alternative operational concepts aProceedings of the 34th Annual Conference of the Military Testing Association. San Diego, CA: Navy Personnel Research and Development Center.1 aMcBride, J R1 aHogan, P F uhttp://www.iacat.org/content/evaluation-alternative-operational-concepts00572nas a2200121 4500008004100000245013200041210006900173260004700242100001200289700001700301700001100318856012100329 1992 eng d00aA general Bayesian model for testlets: theory and applications (Research Report 92-21; GRE Board Professional Report No 99-01P)0 ageneral Bayesian model for testlets theory and applications Rese aPrinceton NJ: Educational Testing Service.1 aWang, X1 aBradlow, E T1 aWainer uhttp://www.iacat.org/content/general-bayesian-model-testlets-theory-and-applications-research-report-92-21-gre-board00573nas a2200145 4500008004100000245009700041210006900138260002100207100001700228700001200245700001900257700001500276700001300291856012300304 1992 eng d00aHow review options and administration mode influence scores on computerized vocabulary tests0 aHow review options and administration mode influence scores on c aSan Francisco CA1 aVispoel, W P1 aWang, T1 aDe la Torre, R1 aBleiler, T1 aDings, J uhttp://www.iacat.org/content/how-review-options-and-administration-mode-influence-scores-computerized-vocabulary-tests00429nas a2200109 4500008004100000245007900041210006900120300001000189490000700199100001700206856009600223 1992 eng d00aImproving the measurement of tonal memory with computerized adaptive tests0 aImproving the measurement of tonal memory with computerized adap a73-890 v111 aVispoel, W P uhttp://www.iacat.org/content/improving-measurement-tonal-memory-computerized-adaptive-tests00433nas a2200109 4500008004100000245007200041210006900113260001800182100001200200700001700212856009400229 1992 eng d00aIncorporating post-administration item response revision into a CAT0 aIncorporating postadministration item response revision into a C aSan Francisco1 aWang, M1 aWingersky, M uhttp://www.iacat.org/content/incorporating-post-administration-item-response-revision-cat00391nas a2200109 4500008004100000245006200041210005800103300001200161490000700173100002000180856008100200 1992 eng d00aThe influence of dimensionality on CAT ability estimation0 ainfluence of dimensionality on CAT ability estimation a513-5280 v521 ade Ayala, R. J. uhttp://www.iacat.org/content/influence-dimensionality-cat-ability-estimation00481nas a2200121 4500008004100000245008900041210006900130300001000199490000700209100001500216700001600231856011200247 1992 eng d00aItem selection using an average growth approximation of target information functions0 aItem selection using an average growth approximation of target i a41-510 v161 aLuecht, RM1 aHirsch, T M uhttp://www.iacat.org/content/item-selection-using-average-growth-approximation-target-information-functions00510nas a2200109 4500008004100000245008000041210006900121260007600190100001800266700001200284856010400296 1992 eng d00aThe Language Training Division's computer adaptive reading proficiency test0 aLanguage Training Divisions computer adaptive reading proficienc aProvo, UT: Language Training Division, Office of Training and Education1 aJanczewski, D1 aLowe, P uhttp://www.iacat.org/content/language-training-divisions-computer-adaptive-reading-proficiency-test00577nas a2200109 4500008004400000245016300044210007200207490001400279100001300293700001600306856014500322 1992 Frendh 00aLe testing adaptatif avec interprétation critérielle, une expérience de praticabilité du TAM pour l’évaluation sommative des apprentissages au Québec.0 aLe testing adaptatif avec interprétation critérielle une expérie0 v15-1 et 21 aAuger, R1 aSeguin, S P uhttp://www.iacat.org/content/le-testing-adaptatif-avec-interpr%C3%A9tation-crit%C3%A9rielle-une-exp%C3%A9rience-de-praticabilit%C3%A9-du-tam00499nam a2200109 4500008004100000245008800041210006900129260004600198100001800244700002000262856010700282 1992 eng d00aManual for the General Scholastic Aptitude Test (Senior) Computerized adaptive test0 aManual for the General Scholastic Aptitude Test Senior Computeri aPretoria: Human Sciences Research Council1 aVon Tonder, M1 aClaasswn, N C W uhttp://www.iacat.org/content/manual-general-scholastic-aptitude-test-senior-computerized-adaptive-test00494nas a2200109 4500008004100000245007300041210006900114260007300183100001800256700001500274856009500289 1992 eng d00aA method for severely constrained item selection in adaptive testing0 amethod for severely constrained item selection in adaptive testi aEducational Testing Service Research Report (RR-92-37): Princeton NJ1 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/method-severely-constrained-item-selection-adaptive-testing-000297nas a2200085 4500008004100000245004200041210004200083100001500125856007100140 1992 eng d00aMultidimensional CAT simulation study0 aMultidimensional CAT simulation study1 aLuecht, RM uhttp://www.iacat.org/content/multidimensional-cat-simulation-study00404nas a2200109 4500008004500000245006400045210006000109300001200169490000700181100001800188856008800206 1992 Engldsh 00aThe Nominal Response Model in Computerized Adaptive Testing0 aNominal Response Model in Computerized Adaptive Testing a327-3430 v151 aDe Ayals, R J uhttp://www.iacat.org/content/nominal-response-model-computerized-adaptive-testing-000400nas a2200109 4500008004100000245006400041210006000105300001200165490000700177100002000184856008600204 1992 eng d00aThe nominal response model in computerized adaptive testing0 anominal response model in computerized adaptive testing a327-3430 v161 ade Ayala, R. J. uhttp://www.iacat.org/content/nominal-response-model-computerized-adaptive-testing00472nas a2200097 4500008004100000245011200041210006900153260002100222100001600243856011500259 1992 eng d00aPractical considerations for conducting studies of differential item functioning (DIF) in a CAT environment0 aPractical considerations for conducting studies of differential  aSan Francisco CA1 aMiller, T R uhttp://www.iacat.org/content/practical-considerations-conducting-studies-differential-item-functioning-dif-cat00453nas a2200109 4500008004100000245007800041210006900119260001900188100002100207700001500228856010000243 1992 eng d00aScaling of two-stage adaptive test configurations for achievement testing0 aScaling of twostage adaptive test configurations for achievement aNew Orleans LA1 aHendrickson, A B1 aKolen, M J uhttp://www.iacat.org/content/scaling-two-stage-adaptive-test-configurations-achievement-testing00521nas a2200097 4500008004100000245013200041210006900173260004600242100001100288856012400299 1992 eng d00aSome practical considerations when converting a linearly administered test to an adaptive format (Research Report 92-21 or 13?)0 aSome practical considerations when converting a linearly adminis aPrinceton NJ: Educational Testing Service1 aWainer uhttp://www.iacat.org/content/some-practical-considerations-when-converting-linearly-administered-test-adaptive-format-000457nas a2200121 4500008004100000245006700041210006600108260002100174100001300195700001700208700001400225856009600239 1992 eng d00aStudent attitudes toward computer-adaptive test administration0 aStudent attitudes toward computeradaptive test administration aSan Francisco CA1 aBaghi, H1 aFerrara, S F1 aGabrys, R uhttp://www.iacat.org/content/student-attitudes-toward-computer-adaptive-test-administration00499nas a2200121 4500008004100000245008200041210006900123300000900192490000700201653003400208100002400242856011100266 1992 eng d00aTest anxiety and test performance under computerized adaptive testing methods0 aTest anxiety and test performance under computerized adaptive te a25180 v5210acomputerized adaptive testing1 aPowell, Zen-Hsiu, E uhttp://www.iacat.org/content/test-anxiety-and-test-performance-under-computerized-adaptive-testing-methods00440nas a2200097 4500008004100000245008200041210006900123260002100192100001600213856011300229 1992 eng d00aTest anxiety and test performance under computerized adaptive testing methods0 aTest anxiety and test performance under computerized adaptive te aSan Francisco CA1 aPowell, Z E uhttp://www.iacat.org/content/test-anxiety-and-test-performance-under-computerized-adaptive-testing-methods-000439nas a2200097 4500008004100000245007900041210006900120260004500189100001500234856009200249 1991 eng d00aAn analysis of CAT-ASVAB scores in the Marine Corps JPM data (CRM- 91-161)0 aanalysis of CATASVAB scores in the Marine Corps JPM data CRM 911 aAlexandria VA: Center for Naval Analysis1 aDivgi, D R uhttp://www.iacat.org/content/analysis-cat-asvab-scores-marine-corps-jpm-data-crm-91-16100416nas a2200121 4500008004100000245005800041210005700099260001500156100001300171700001400184700001500198856008100213 1991 eng d00aApplications of computer-adaptive testing in Maryland0 aApplications of computeradaptive testing in Maryland aChicago IL1 aBaghi, H1 aGabrys, R1 aFerrara, S uhttp://www.iacat.org/content/applications-computer-adaptive-testing-maryland00547nas a2200121 4500008004100000245010100041210006900142260004600211100001800257700001500275700001600290856011900306 1991 eng d00aAutomatic item selection (AIS) methods in the ETS testing environment (Research Memorandum 91-5)0 aAutomatic item selection AIS methods in the ETS testing environm aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aSwanson, L1 aPearlman, M uhttp://www.iacat.org/content/automatic-item-selection-ais-methods-ets-testing-environment-research-memorandum-91-500515nas a2200145 4500008004100000245008200041210006900123300001200192490000600204100001100210700001300221700001400234700001600248856010500264 1991 eng d00aBuilding algebra testlets: A comparison of hierarchical and linear structures0 aBuilding algebra testlets A comparison of hierarchical and linea axxx-xxx0 v81 aWainer1 aLewis, C1 aKaplan, B1 aBraswell, J uhttp://www.iacat.org/content/building-algebra-testlets-comparison-hierarchical-and-linear-structures00535nas a2200133 4500008004100000245007400041210006900115260006600184100001500250700001400265700001600279700001300295856009300308 1991 eng d00aCollected works on the legal aspects of computerized adaptive testing0 aCollected works on the legal aspects of computerized adaptive te aChicago, IL: National Council of State Boards of Nursing, Inc1 aStenson, H1 aGraves, P1 aGardiner, J1 aDally, L uhttp://www.iacat.org/content/collected-works-legal-aspects-computerized-adaptive-testing01284nas a2200181 4500008004100000020002200041245008400063210006900147250001500216260000800231300001200239490000700251520069100258100001500949700002000964700001700984856010101001 1991 eng d a0022-3891 (Print)00aComparability of computerized adaptive and conventional testing with the MMPI-20 aComparability of computerized adaptive and conventional testing  a1991/01/01 cOct a278-2900 v573 aA computerized adaptive version and the standard version of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) were administered 1 week apart to a sample of 155 college students to assess the comparability of the two versions. The countdown method was used to adaptively administer Scales L, F, the I0 clinical scales, and the 15 new content scales. Profiles across administration modalities show a high degree of similarity, providing evidence for the comparability of computerized adaptive and conventional testing with the MMPI-2. Substantial item savings were found with the adaptive version. Future directions in the study of adaptive testing with the MMPI-2 are discussed.1 aRoper, B L1 aBen-Porath, Y S1 aButcher, J N uhttp://www.iacat.org/content/comparability-computerized-adaptive-and-conventional-testing-mmpi-200465nas a2200121 4500008004100000245007800041210006900119300001000188490000700198100001400205700002400219856010000243 1991 eng d00aComparability of decisions for computer adaptive and written examinations0 aComparability of decisions for computer adaptive and written exa a15-230 v201 aLunz, M E1 aBergstrom, Betty, A uhttp://www.iacat.org/content/comparability-decisions-computer-adaptive-and-written-examinations00584nas a2200121 4500008004100000245016000041210006900201300000900270490000700279653003400286100002000320856012200340 1991 eng d00aA comparison of paper-and-pencil, computer-administered, computerized feedback, and computerized adaptive testing methods for classroom achievement testing0 acomparison of paperandpencil computeradministered computerized f a17190 v5210acomputerized adaptive testing1 aKuan, Tsung Hao uhttp://www.iacat.org/content/comparison-paper-and-pencil-computer-administered-computerized-feedback-and-computerized00367nas a2200085 4500008004100000245006800041210006500109100001900174856008800193 1991 eng d00aA comparison of procedures for content-sensitive item selection0 acomparison of procedures for contentsensitive item selection1 aKingsbury, G G uhttp://www.iacat.org/content/comparison-procedures-content-sensitive-item-selection00496nas a2200121 4500008004100000245009900041210006900140300001200209490000600221100001900227700001200246856011600258 1991 eng d00aA comparison of procedures for content-sensitive item selection in computerized adaptive tests0 acomparison of procedures for contentsensitive item selection in  a241-2610 v41 aKingsbury, G G1 aZara, A uhttp://www.iacat.org/content/comparison-procedures-content-sensitive-item-selection-computerized-adaptive-tests00465nas a2200109 4500008004100000245006400041210006400105260005800169100002400227700001400251856009000265 1991 eng d00aComparisons of computer adaptive and pencil and paper tests0 aComparisons of computer adaptive and pencil and paper tests aChicago IL: American Society of Clinical Pathologists1 aBergstrom, Betty, A1 aLunz, M E uhttp://www.iacat.org/content/comparisons-computer-adaptive-and-pencil-and-paper-tests00599nas a2200121 4500008004100000245007100041210006800112260014900180100001800329700001400347700001900361856009700380 1991 eng d00aComputerized adaptive testing: Theory, applications, and standards0 aComputerized adaptive testing Theory applications and standards aR. K. Hambleton and J. N. Zaal (Eds.), Advances in educational and psychological testing: Theory and Applications (pp. 341-366). Boston: Kluwer.1 aHambleton, RK1 aZaal, J N1 aPieters, J P M uhttp://www.iacat.org/content/computerized-adaptive-testing-theory-applications-and-standards00479nas a2200109 4500008004100000245009400041210006900135260001500204100001900219700001400238856011700252 1991 eng d00aConfidence in pass/fail decisions for computer adaptive and paper and pencil examinations0 aConfidence in passfail decisions for computer adaptive and paper aChicago IL1 aBergstrom, B B1 aLunz, M E uhttp://www.iacat.org/content/confidence-passfail-decisions-computer-adaptive-and-paper-and-pencil-examinations-200501nas a2200109 4500008004100000245009900041210006900140260003300209100001500242700001800257856011600275 1991 eng d00aConstruction and validation of the SON-R 5-17, the Snijders-Oomen non-verbal intelligence test0 aConstruction and validation of the SONR 517 the SnijdersOomen no aGroningen: Wolters-Noordhoff1 aLaros, J A1 aTellegen, P J uhttp://www.iacat.org/content/construction-and-validation-son-r-5-17-snijders-oomen-non-verbal-intelligence-test00499nas a2200145 4500008004100000245007200041210006900113300001000182490000600192100001700198700001400215700001400229700001500243856009500258 1991 eng d00aCorrelates of examinee item choice behavior in self-adapted testing0 aCorrelates of examinee item choice behavior in selfadapted testi a25-280 v41 aJohnson, J L1 aRoos, L L1 aWise, S L1 aPlake, B S uhttp://www.iacat.org/content/correlates-examinee-item-choice-behavior-self-adapted-testing00445nas a2200109 4500008004100000245007700041210006900118260001500187100001900202700001700221856009700238 1991 eng d00aThe development and evaluation of a computerized adaptive testing system0 adevelopment and evaluation of a computerized adaptive testing sy aChicago IL1 aDe la Torre, R1 aVispoel, W P uhttp://www.iacat.org/content/development-and-evaluation-computerized-adaptive-testing-system00490nas a2200109 4500008004100000245010800041210006900149260001500218100001300233700001500246856011900261 1991 eng d00aDevelopment and evaluation of hierarchical testlets in two-stage tests using integer linear programming0 aDevelopment and evaluation of hierarchical testlets in twostage  aChicago IL1 aLam, T L1 aGoong, Y Y uhttp://www.iacat.org/content/development-and-evaluation-hierarchical-testlets-two-stage-tests-using-integer-linear00459nas a2200109 4500008004100000245008300041210006900124260001200193100001700205700002100222856010600243 1991 eng d00aAn empirical comparison of self-adapted and maximum information item selection0 aempirical comparison of selfadapted and maximum information item aChicago1 aRocklin, T R1 aO’Donnell, A M uhttp://www.iacat.org/content/empirical-comparison-self-adapted-and-maximum-information-item-selection00468nas a2200097 4500008004100000245010200041210006900143100001600212700001700228856012500245 1991 eng d00aIndividual differences in computer adaptive testing: Anxiety, computer literacy, and satisfaction0 aIndividual differences in computer adaptive testing Anxiety comp1 aGershon, RC1 aBergstrom, B uhttp://www.iacat.org/content/individual-differences-computer-adaptive-testing-anxiety-computer-literacy-and-satisfaction00439nas a2200121 4500008004100000245006100041210006000102300001200162490000700174653003400181100001500215856008700230 1991 eng d00aInter-subtest branching in computerized adaptive testing0 aIntersubtest branching in computerized adaptive testing a140-1410 v5210acomputerized adaptive testing1 aChang, S-H uhttp://www.iacat.org/content/inter-subtest-branching-computerized-adaptive-testing00738nas a2200169 4500008004100000020000900041245012400050210006900174260008700243653003400330653001500364653001800379100001600397700001900413700001700432856011900449 1991 eng d aR-1100aPatterns of alcohol and drug use among federal offenders as assessed by the Computerized Lifestyle Screening Instrument0 aPatterns of alcohol and drug use among federal offenders as asse aOttawa, ON. CanadabResearch and Statistics Branch, Correctional Service of Canada10acomputerized adaptive testing10adrug abuse10asubstance use1 aRobinson, D1 aPorporino, F J1 aMillson, W A uhttp://www.iacat.org/content/patterns-alcohol-and-drug-use-among-federal-offenders-assessed-computerized-lifestyle00538nas a2200097 4500008004100000245011700041210006900158260004300227100004800270856012200318 1991 eng d00aA psychometric comparison of computerized and paper-and-pencil versions of the national RN licensure examination0 apsychometric comparison of computerized and paperandpencil versi aChicago IL: Author, Unpublished report1 aNational-Council-of-State-Boards-of-Nursing uhttp://www.iacat.org/content/psychometric-comparison-computerized-and-paper-and-pencil-versions-national-rn-licensure00385nas a2200133 4500008004100000245004600041210003800087300001200125490000700137100001600144700001100160700001500171856006500186 1991 eng d00aOn the reliability of testlet-based tests0 areliability of testletbased tests a237-2470 v281 aSireci, S G1 aWainer1 aThissen, D uhttp://www.iacat.org/content/reliability-testlet-based-tests00469nas a2200109 4500008004100000245007800041210006900119260005300188100001700241700001300258856008800271 1991 eng d00aA simulation study of some simple approaches to the study of DIF for CATs0 asimulation study of some simple approaches to the study of DIF f aInternal memorandum, Educational Testing Service1 aHolland, P W1 aZwick, R uhttp://www.iacat.org/content/simulation-study-some-simple-approaches-study-dif-cats00522nas a2200121 4500008004100000245007700041210006900118260007500187100001100262700001400273700001300287856010000300 1991 eng d00aSome empirical guidelines for building testlets (Technical Report 91-56)0 aSome empirical guidelines for building testlets Technical Report aPrinceton NJ: Educational Testing Service, Program Statistics Research1 aWainer1 aKaplan, B1 aLewis, C uhttp://www.iacat.org/content/some-empirical-guidelines-building-testlets-technical-report-91-5601606nas a2200121 4500008004100000245010800041210006900149260003700218520108800255100001501343700001301358856011301371 1991 eng d00aThe use of the graded response model in computerized adaptive testing of the attitudes to science scale0 ause of the graded response model in computerized adaptive testin aChicago, IL USAcApril 3-7, 19913 aThe graded response model for two-stage testing was applied to an attitudes toward science scale using real-data simulation. The 48-item scale was administered to 920 students at a grade-8 equivalent in Singapore. A two-stage 16-item computerized adaptive test was developed. In two-stage testing an initial, or routing, test is followed by a second-stage testlet of greater or lesser difficulty based on performance. A conventional test of the same length as the adaptive two-stage test was selected from the 48-item pool. Responses to the conventional test, the routing test, and a testlet were simulated. The algorithm of E. Balas (1965) and the multidimensional knapsack problem of optimization theory were used in test development. The simulation showed the efficiency and accuracy of the two-stage test with the graded response model in estimating attitude trait levels, as evidenced by better results from the two-stage test than its conventional counterpart and the reduction to one-third of the length of the original measure. Six tables and three graphs are included. (SLD)1 aFoong, Y-Y1 aLam, T-L uhttp://www.iacat.org/content/use-graded-response-model-computerized-adaptive-testing-attitudes-science-scale00463nas a2200109 4500008004100000245009600041210006900137300001000206490000700216100001800223856011200241 1991 eng d00aThe use of unidimensional parameter estimates of multidimensional items in adaptive testing0 ause of unidimensional parameter estimates of multidimensional it a13-240 v151 aAckerman, T A uhttp://www.iacat.org/content/use-unidimensional-parameter-estimates-multidimensional-items-adaptive-testing00469nas a2200109 4500008004500000245009600045210006900141300001000210490000700220100001800227856011400245 1991 Engldsh 00aThe Use of Unidimensional Parameter Estimates of Multidimensional Items in Adaptive Testing0 aUse of Unidimensional Parameter Estimates of Multidimensional It a13-240 v151 aAckerman, T A uhttp://www.iacat.org/content/use-unidimensional-parameter-estimates-multidimensional-items-adaptive-testing-000505nas a2200097 4500008004100000245008400041210006900125260008800194100001700282856010800299 1991 eng d00aWhat lies ahead? Computer technology and its implications for personnel testing0 aWhat lies ahead Computer technology and its implications for per aNATO Workshop on Computer-based Assessment of Military Personnel, Brussels, Belgium1 aMcBride, J R uhttp://www.iacat.org/content/what-lies-ahead-computer-technology-and-its-implications-personnel-testing00461nas a2200109 4500008004100000245009200041210006900133300000800202490001100210100001900221856011100240 1990 eng d00aAdapting adaptive testing: Using the MicroCAT Testing System in a local school district0 aAdapting adaptive testing Using the MicroCAT Testing System in a a3-60 v29 (2)1 aKingsbury, G G uhttp://www.iacat.org/content/adapting-adaptive-testing-using-microcat-testing-system-local-school-district00555nas a2200133 4500008004100000245010600041210006900147260003100216100001100247700001300258700001100271700001600282856012300298 1990 eng d00aAn adaptive algebra test: A testlet-based, hierarchically structured test with validity-based scoring0 aadaptive algebra test A testletbased hierarchically structured t aETS Technical Report 90-921 aWainer1 aLewis, C1 aKaplan1 aBraswell, J uhttp://www.iacat.org/content/adaptive-algebra-test-testlet-based-hierarchically-structured-test-validity-based-scoring00507nas a2200133 4500008004100000245009100041210006900132300001200201490000700213100001300220700001600233700001600249856010800265 1990 eng d00aAdaptive designs for Likert-type data: An approach for implementing marketing research0 aAdaptive designs for Likerttype data An approach for implementin a304-3210 v271 aSingh, J1 aHowell, R D1 aRhoads, G K uhttp://www.iacat.org/content/adaptive-designs-likert-type-data-approach-implementing-marketing-research00372nas a2200109 4500008004100000245005400041210005400095300001100149490000700160100001500167856008000182 1990 eng d00aApplying computerized adaptive testing in schools0 aApplying computerized adaptive testing in schools a311-380 v231 aOlson, J B uhttp://www.iacat.org/content/applying-computerized-adaptive-testing-schools00454nas a2200109 4500008004100000245008100041210006900122260001400191100001900205700001600224856010400240 1990 eng d00aAssessing the utility of item response models: Computerized adaptive testing0 aAssessing the utility of item response models Computerized adapt aBoston MA1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/assessing-utility-item-response-models-computerized-adaptive-testing-000491nas a2200109 4500008004100000245009500041210006900136260002700205100001600232700001700248856011600265 1990 eng d00aA comparison of Rasch and three-parameter logistic models in computerized adaptive testing0 acomparison of Rasch and threeparameter logistic models in comput aUnpublished manuscript1 aParker, S B1 aMcBride, J R uhttp://www.iacat.org/content/comparison-rasch-and-three-parameter-logistic-models-computerized-adaptive-testing00462nas a2200109 4500008004100000245009800041210006900139300001200208490000600220100001500226856011100241 1990 eng d00aA comparison of three decision models for adapting the length of computer-based mastery tests0 acomparison of three decision models for adapting the length of c a479-5130 v61 aFrick, T W uhttp://www.iacat.org/content/comparison-three-decision-models-adapting-length-computer-based-mastery-tests00388nas a2200109 4500008004100000245005800041210005700099300001000156490001000166100001600176856008600192 1990 eng d00aComputer testing: Pragmatic issues and research needs0 aComputer testing Pragmatic issues and research needs a19-200 v9 (2)1 aRudner, L M uhttp://www.iacat.org/content/computer-testing-pragmatic-issues-and-research-needs00420nas a2200133 4500008004100000245005100041210005100092300001000143490000700153100001400160700001400174700002100188856007700209 1990 eng d00aComputerized adaptive measurement of attitudes0 aComputerized adaptive measurement of attitudes a20-300 v231 aKoch, W R1 aDodd, B G1 aFitzpatrick, S J uhttp://www.iacat.org/content/computerized-adaptive-measurement-attitudes00418nas a2200097 4500008004100000245007600041210006900117260001800186100001700204856009900221 1990 eng d00aComputerized adaptive music tests: A new solution to three old problems0 aComputerized adaptive music tests A new solution to three old pr aWashington DC1 aVispoel, W P uhttp://www.iacat.org/content/computerized-adaptive-music-tests-new-solution-three-old-problems00515nam a2200169 4500008003900000245005100039210004700090260002600137100001100163700001600174700001600190700001400206700001700220700001700237700001500254856007600269 1990 d00aComputerized adaptive testing: A primer (Eds.)0 aComputerized adaptive testing A primer Eds aHillsdale NJ: Erlbaum1 aWainer1 aDorans, N J1 aFlaugher, R1 aGreen, BF1 aMislevy, R J1 aSteinberg, L1 aThissen, D uhttp://www.iacat.org/content/computerized-adaptive-testing-primer-eds-200358nas a2200109 4500008004100000245005200041210004700093300001200140490000700152100001500159856007400174 1990 eng d00aThe construction of customized two-staged tests0 aconstruction of customized twostaged tests a241-2530 v271 aAdema, J J uhttp://www.iacat.org/content/construction-customized-two-staged-tests00595nas a2200109 4500008004100000245007600041210006900117260017000186100001700356700001500373856009700388 1990 eng d00aCreating adaptive tests of musical ability with limited-size item pools0 aCreating adaptive tests of musical ability with limitedsize item aD. Dalton (Ed.), ADCIS 32nd International Conference Proceedings (pp. 105-112). Columbus OH: Association for the Development of Computer-Based Instructional Systems.1 aVispoel, W T1 aTwing, J S uhttp://www.iacat.org/content/creating-adaptive-tests-musical-ability-limited-size-item-pools00368nas a2200085 4500008004100000245006800041210006800109100001200177856009300189 1990 eng d00aDichotomous search strategies for computerized adaptive testing0 aDichotomous search strategies for computerized adaptive testing1 aXiao, B uhttp://www.iacat.org/content/dichotomous-search-strategies-computerized-adaptive-testing01702nas a2200121 4500008004100000245013100041210006900172300001200241490000700253520118500260100001401445856012101459 1990 eng d00aThe effect of item selection procedure and stepsize on computerized adaptive attitude measurement using the rating scale model0 aeffect of item selection procedure and stepsize on computerized  a355-3860 v143 aReal and simulated datasets were used to investigate the effects of the systematic variation of two major variables on the operating characteristics of computerized adaptive testing (CAT) applied to instruments consisting of poly- chotomously scored rating scale items. The two variables studied were the item selection procedure and the stepsize method used until maximum likelihood trait estimates could be calculated. The findings suggested that (1) item pools that consist of as few as 25 items may be adequate for CAT; (2) the variable stepsize method of preliminary trait estimation produced fewer cases of nonconvergence than the use of a fixed stepsize procedure; and (3) the scale value item selection procedure used in conjunction with a minimum standard error stopping rule outperformed the information item selection technique used in conjunction with a minimum information stopping rule in terms of the frequencies of nonconvergent cases, the number of items administered, and the correlations of CAT 0 estimates with full scale estimates and known 0 values. The implications of these findings for implementing CAT with rating scale items are discussed. Index terms: 1 aDodd, B G uhttp://www.iacat.org/content/effect-item-selection-procedure-and-stepsize-computerized-adaptive-attitude-measurement00511nas a2200109 4500008004500000245013100045210006900176300001200245490000700257100001400264856012300278 1990 Engldsh 00aThe Effect of Item Selection Procedure and Stepsize on Computerized Adaptive Attitude Measurement Using the Rating Scale Model0 aEffect of Item Selection Procedure and Stepsize on Computerized  a355-3660 v141 aDodd, B G uhttp://www.iacat.org/content/effect-item-selection-procedure-and-stepsize-computerized-adaptive-attitude-measurement-000470nas a2200109 4500008004100000245010100041210006900142300001200211490000700223100001700230856011300247 1990 eng d00aThe effects of variable entry on bias and information of the Bayesian adaptive testing procedure0 aeffects of variable entry on bias and information of the Bayesia a785-8020 v501 aHankins, J A uhttp://www.iacat.org/content/effects-variable-entry-bias-and-information-bayesian-adaptive-testing-procedure00412nas a2200121 4500008003900000245005500039210005100094260001900145100002000164700001500184700001700199856007400216 1990 d00aAn empirical study of the computer adaptive MMPI-20 aempirical study of the computer adaptive MMPI2 aMinneapolis MN1 aBen-Porath, Y S1 aRoper, B L1 aButcher, J N uhttp://www.iacat.org/content/empirical-study-computer-adaptive-mmpi-200483nas a2200157 4500008004100000245002200041210002200063260009900085100001100184700001600195700001400211700001700225700001700242700001500259856005100274 1990 eng d00aFuture challenges0 aFuture challenges aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 233-272). Hillsdale NJ: Erlbaum.1 aWainer1 aDorans, N J1 aGreen, BF1 aMislevy, R J1 aSteinberg, L1 aThissen, D uhttp://www.iacat.org/content/future-challenges00619nas a2200169 4500008004100000245009000041210006900131300001200200490000700212653001500219653001500234653003700249653002300286653001800309100001600327856010600343 1990 eng d00aFuture directions for the National Council: the Computerized Adaptive Testing Project0 aFuture directions for the National Council the Computerized Adap a1, 3, 50 v1110a*Computers10a*Licensure10aEducational Measurement/*methods10aSocieties, Nursing10aUnited States1 aBouchard, J uhttp://www.iacat.org/content/future-directions-national-council-computerized-adaptive-testing-project00487nas a2200097 4500008004100000245009000041210006900131260006500200100001600265856010800281 1990 eng d00aFuture directions for the National Council: The Computerized Adaptive Testing Project0 aFuture directions for the National Council The Computerized Adap aIssues, 11, 1-5(National Council of State Boards of Nursing)1 aBouchard, J uhttp://www.iacat.org/content/future-directions-national-council-computerized-adaptive-testing-project-000462nas a2200109 4500008004100000245005400041210005400095260009400149100001500243700001600258856007800274 1990 eng d00aGenerative adaptive testing with digit span items0 aGenerative adaptive testing with digit span items aSan Diego, CA: Testing Systems Department, Navy Personnel Research and Development Center1 aWolfe, J H1 aLarson, G E uhttp://www.iacat.org/content/generative-adaptive-testing-digit-span-items00443nas a2200121 4500008004100000245006600041210006500107260001400172100001500186700002000201700001700221856008300238 1990 eng d00aIllustration of computerized adaptive testing with the MMPI-20 aIllustration of computerized adaptive testing with the MMPI2 aBoston MA1 aRoper, B L1 aBen-Porath, Y S1 aButcher, J N uhttp://www.iacat.org/content/illustration-computerized-adaptive-testing-mmpi-200346nas a2200097 4500008004100000245002800041210002800069260008600097100001100183856005400194 1990 eng d00aImportant issues in CAT0 aImportant issues in CAT aH. Wainer et al., Computerized adaptive testing: A primer. Hillsdale NJ: Erlbaum.1 aWainer uhttp://www.iacat.org/content/important-issues-cat00367nas a2200097 4500008004100000245002900041210002900070260010100099100001100200856005800211 1990 eng d00aIntroduction and history0 aIntroduction and history aIn H. Wainer (Ed.), Computerized adaptive testing: A Primer (pp. 1 - 21). Hillsdale NJ: Erlbaum.1 aWainer uhttp://www.iacat.org/content/introduction-and-history00515nas a2200109 4500008004100000245007100041210006900112260009800181100001100279700001700290856009800307 1990 eng d00aItem response theory, item calibration, and proficiency estimation0 aItem response theory item calibration and proficiency estimation aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 65-102). Hillsdale NJ: Erlbaum.1 aWainer1 aMislevy, R J uhttp://www.iacat.org/content/item-response-theory-item-calibration-and-proficiency-estimation00452nas a2200121 4500008004100000245006800041210006700109260001700176100001700193700001500210700001500225856009000240 1990 eng d00aMusicCAT: An adaptive testing program to assess musical ability0 aMusicCAT An adaptive testing program to assess musical ability aSan Diego CA1 aVispoel, W P1 aCoffman, D1 aScriven, D uhttp://www.iacat.org/content/musiccat-adaptive-testing-program-assess-musical-ability00657nas a2200181 4500008004100000245008900041210006900130300000600199490000700205653001500212653001500227653003700242653002400279653002300303653001800326100001400344856011700358 1990 eng d00aNational Council Computerized Adaptive Testing Project Review--committee perspective0 aNational Council Computerized Adaptive Testing Project Reviewcom a30 v1110a*Computers10a*Licensure10aEducational Measurement/*methods10aFeasibility Studies10aSocieties, Nursing10aUnited States1 aHaynes, B uhttp://www.iacat.org/content/national-council-computerized-adaptive-testing-project-review-committee-perspective00494nas a2200097 4500008004100000245004200041210004200083260018500125100001500310856007100325 1990 eng d00aReliability and measurement precision0 aReliability and measurement precision aH. Wainer, N. J. Dorans, R. Flaugher, B. F. Green, R. J. Mislevy, L. Steinberg, and D. Thissen (Eds.), Computerized adaptive testing: A primer (pp. 161-186). Hillsdale NJ: Erlbaum.1 aThissen, D uhttp://www.iacat.org/content/reliability-and-measurement-precision00501nas a2200097 4500008004100000245008100041210006900122260009800191100001200289856010200301 1990 eng d00aA research proposal for field testing CAT for nursing licensure examinations0 aresearch proposal for field testing CAT for nursing licensure ex aDelegate Assembly Book of Reports 1989. Chicago: National Council of State Boards of Nursing.1 aZara, A uhttp://www.iacat.org/content/research-proposal-field-testing-cat-nursing-licensure-examinations-000382nas a2200109 4500008003900000245006100039210006100100300001000161490000700171100001200178856008200190 1990 d00aSequential item response models with an ordered response0 aSequential item response models with an ordered response a39-550 v431 aTutz, G uhttp://www.iacat.org/content/sequential-item-response-models-ordered-response01508nas a2200157 4500008004100000245008900041210006900130300001200199490000700211520093700218653003401155100002001189700001401209700001401223856011301237 1990 eng d00aA simulation and comparison of flexilevel and Bayesian computerized adaptive testing0 asimulation and comparison of flexilevel and Bayesian computerize a227-2390 v273 aComputerized adaptive testing (CAT) is a testing procedure that adapts an examination to an examinee's ability by administering only items of appropriate difficulty for the examinee. In this study, the authors compared Lord's flexilevel testing procedure (flexilevel CAT) with an item response theory-based CAT using Bayesian estimation of ability (Bayesian CAT). Three flexilevel CATs, which differed in test length (36, 18, and 11 items), and three Bayesian CATs were simulated; the Bayesian CATs differed from one another in the standard error of estimate (SEE) used for terminating the test (0.25, 0.10, and 0.05). Results showed that the flexilevel 36- and 18-item CATs produced ability estimates that may be considered as accurate as those of the Bayesian CAT with SEE = 0.10 and comparable to the Bayesian CAT with SEE = 0.05. The authors discuss the implications for classroom testing and for item response theory-based CAT.10acomputerized adaptive testing1 ade Ayala, R. J.1 aDodd, B G1 aKoch, W R uhttp://www.iacat.org/content/simulation-and-comparison-flexilevel-and-bayesian-computerized-adaptive-testing00377nas a2200109 4500008004100000245005500041210005400096300001000150490000600160100001800166856008300184 1990 eng d00aSoftware review: MicroCAT Testing System Version 30 aSoftware review MicroCAT Testing System Version 3 a82-880 v71 aPatience, W M uhttp://www.iacat.org/content/software-review-microcat-testing-system-version-300470nas a2200109 4500008004100000245008900041210006900130260001500199100002400214700001400238856010800252 1990 eng d00aThe stability of Rasch pencil and paper item calibrations on computer adaptive tests0 astability of Rasch pencil and paper item calibrations on compute aChicago IL1 aBergstrom, Betty, A1 aLunz, M E uhttp://www.iacat.org/content/stability-rasch-pencil-and-paper-item-calibrations-computer-adaptive-tests00378nas a2200109 4500008004100000245002300041210002300064260009900087100001100186700001700197856005400214 1990 eng d00aTesting algorithms0 aTesting algorithms aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 103-135). Hillsdale NJ: Erlbaum.1 aWainer1 aMislevy, R J uhttp://www.iacat.org/content/testing-algorithms-000380nas a2200109 4500008004100000245002300041210002300064260009900087100001500186700001700201856005200218 1990 eng d00aTesting algorithms0 aTesting algorithms aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 103-135). Hillsdale NJ: Erlbaum.1 aThissen, D1 aMislevy, R J uhttp://www.iacat.org/content/testing-algorithms00436nas a2200121 4500008004100000245005600041210005400097260002800151100001400179700002400193700001600217856008100233 1990 eng d00aTest-retest consistency of computer adaptive tests.0 aTestretest consistency of computer adaptive tests aBoston, MA USAc04/19901 aLunz, M E1 aBergstrom, Betty, A1 aGershon, RC uhttp://www.iacat.org/content/test-retest-consistency-computer-adaptive-tests00346nas a2200121 4500008004100000245004000041210004000081300000900121490000700130100001100137700001300148856006300161 1990 eng d00aToward a psychometrics for testlets0 aToward a psychometrics for testlets a1-140 v271 aWainer1 aLewis, C uhttp://www.iacat.org/content/toward-psychometrics-testlets00455nas a2200121 4500008004500000245007300045210006900118300001200187490000700199100001300206700001500219856009900234 1990 Engldsh 00aUsing Bayesian Decision Theory to Design a Computerized Mastery Test0 aUsing Bayesian Decision Theory to Design a Computerized Mastery  a367-3860 v141 aLewis, C1 aSheehan, K uhttp://www.iacat.org/content/using-bayesian-decision-theory-design-computerized-mastery-test-100446nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001000202700001500212856009700227 1990 eng d00aUsing Bayesian decision theory to design a computerized mastery test0 aUsing Bayesian decision theory to design a computerized mastery  a367-3860 v141 aLewis1 aSheehan, K uhttp://www.iacat.org/content/using-bayesian-decision-theory-design-computerized-mastery-test00552nas a2200109 4500008004100000245011200041210006900153260006900222100001400291700001600305856012100321 1990 eng d00aUtility of predicting starting abilities in sequential computer-based adaptive tests (Research Report 90-1)0 aUtility of predicting starting abilities in sequential computerb aBaltimore MD: Johns Hopkins University, Department of Psychology1 aGreen, BF1 aThomas, T J uhttp://www.iacat.org/content/utility-predicting-starting-abilities-sequential-computer-based-adaptive-tests-research00373nas a2200121 4500008004100000245001300041210001300054260009900067100001700166700001500183700001100198856004200209 1990 eng d00aValidity0 aValidity aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 187-231). Hillsdale NJ: Erlbaum.1 aSteinberg, L1 aThissen, D1 aWainer uhttp://www.iacat.org/content/validity00544nas a2200097 4500008004100000245013000041210006900171260006800240100001600308856012200324 1990 eng d00aValidity study in multidimensional latent space and efficient computerized adaptive testing (Final Report R01-1069-11-004-91)0 aValidity study in multidimensional latent space and efficient co aKnoxville TN: University of Tennessee, Department of Psychology1 aSamejima, F uhttp://www.iacat.org/content/validity-study-multidimensional-latent-space-and-efficient-computerized-adaptive-testing00389nas a2200085 4500008004100000245007800041210006900119100001500188856010000203 1990 eng d00aWhat can we do with computerized adaptive testing and what we cannot do? 0 aWhat can we do with computerized adaptive testing and what we ca1 aLaurier, M uhttp://www.iacat.org/content/what-can-we-do-computerized-adaptive-testing-and-what-we-cannot-do00547nas a2200145 4500008004500000245009400045210006900139300001200208490000700220100001500227700001500242700001700257700001400274856011300288 1989 Engldsh 00aAdaptive and Conventional Versions of the DAT: The First Complete Test Battery Comparison0 aAdaptive and Conventional Versions of the DAT The First Complete a363-3710 v131 aHenly, S J1 aKlebe, K J1 aMcBride, J R1 aCudeck, R uhttp://www.iacat.org/content/adaptive-and-conventional-versions-dat-first-complete-test-battery-comparison-000541nas a2200145 4500008004100000245009400041210006900135300001200204490000700216100001500223700001500238700001700253700001400270856011100284 1989 eng d00aAdaptive and conventional versions of the DAT: The first complete test battery comparison0 aAdaptive and conventional versions of the DAT The first complete a363-3710 v131 aHenly, S J1 aKlebe, K J1 aMcBride, J R1 aCudeck, R uhttp://www.iacat.org/content/adaptive-and-conventional-versions-dat-first-complete-test-battery-comparison00455nas a2200121 4500008004100000245008100041210006900122300001200191490000700203100000900210700001400219856010000233 1989 eng d00aAdaptive estimation when the unidimensionality assumption of IRT is violated0 aAdaptive estimation when the unidimensionality assumption of IRT a373-3890 v131 aFolk1 aGreen, BF uhttp://www.iacat.org/content/adaptive-estimation-when-unidimensionality-assumption-irt-violated00466nas a2200121 4500008004500000245008100045210006900126300001200195490000700207100001400214700001400228856010200242 1989 Engldsh 00aAdaptive Estimation When the Unidimensionality Assumption of IRT is Violated0 aAdaptive Estimation When the Unidimensionality Assumption of IRT a373-3900 v131 aFolk, V G1 aGreen, BF uhttp://www.iacat.org/content/adaptive-estimation-when-unidimensionality-assumption-irt-violated-000427nas a2200133 4500008004100000020001400041245005100055210005000106300001000156490000600166653003400172100001700206856007000223 1989 eng d a1745-399200aAdaptive testing: The evolution of a good idea0 aAdaptive testing The evolution of a good idea a11-150 v810acomputerized adaptive testing1 aReckase, M D uhttp://www.iacat.org/content/adaptive-testing-evolution-good-idea00505nas a2200121 4500008004100000245009800041210006900139300000900208490000700217653003400224100001400258856011100272 1989 eng d00aApplication of computerized adaptive testing to the University Entrance Exam of Taiwan, R.O.C0 aApplication of computerized adaptive testing to the University E a36620 v4910acomputerized adaptive testing1 aHung, P-H uhttp://www.iacat.org/content/application-computerized-adaptive-testing-university-entrance-exam-taiwan-roc01763nas a2200133 4500008004100000245005400041210005100095260005500146300000800201520129200209653003401501100001701535856007701552 1989 eng d00aAn applied study on computerized adaptive testing0 aapplied study on computerized adaptive testing aGroningen, The NetherlandsbUniversity of Groingen a1853 a(from the cover) The rapid development and falling prices of powerful personal computers, in combination with new test theories, will have a large impact on psychological testing. One of the new possibilities is computerized adaptive testing. During the test administration each item is chosen to be appropriate for the person being tested. The test becomes tailor-made, resolving some of the problems with classical paper-and-pencil tests. In this way individual differences can be measured with higher efficiency and reliability. Scores on other meaningful variables, such as response time, can be obtained easily using computers. /// In this book a study on computerized adaptive testing is described. The study took place at Dutch Railways in an applied setting and served practical goals. Topics discussed include the construction of computerized tests, the use of response time, the choice of algorithms and the implications of using a latent trait model. After running a number of simulations and calibrating the item banks, an experiment was carried out. In the experiment a pretest was administered to a sample of over 300 applicants, followed by an adaptive test. In addition, a survey concerning the attitudes of testees towards computerized testing formed part of the design.10acomputerized adaptive testing1 aSchoonman, W uhttp://www.iacat.org/content/applied-study-computerized-adaptive-testing00393nam a2200097 4500008004100000245005400041210005100095260005300146100001700199856007900216 1989 eng d00aAn applied study on computerized adaptive testing0 aapplied study on computerized adaptive testing aAmsterdam, The Netherlands: Swets and Zeitlinger1 aSchoonman, W uhttp://www.iacat.org/content/applied-study-computerized-adaptive-testing-000520nas a2200109 4500008004100000245013200041210006900173260001800242100001900260700001600279856011500295 1989 eng d00aAssessing the impact of using item parameter estimates obtained from paper-and-pencil testing for computerized adaptive testing0 aAssessing the impact of using item parameter estimates obtained  aSan Francisco1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/assessing-impact-using-item-parameter-estimates-obtained-paper-and-pencil-testing00466nas a2200109 4500008004100000245009100041210006900132300001100201490000900212100001500221856012000236 1989 eng d00aBayesian adaptation during computer-based tests and computer-guided practice exercises0 aBayesian adaptation during computerbased tests and computerguide a89-1140 v5(1)1 aFrick, T W uhttp://www.iacat.org/content/bayesian-adaptation-during-computer-based-tests-and-computer-guided-practice-exercises00334nam a2200097 4500008004100000245004100041210003900082260003100121100001600152856006800168 1989 eng d00aCAT administrator [Computer program]0 aCAT administrator Computer program aChicago: Micro Connections1 aGershon, RC uhttp://www.iacat.org/content/cat-administrator-computer-program00386nas a2200097 4500008004100000245006100041210006100102260002100163100001700184856008700201 1989 eng d00aCommercial applications of computerized adaptive testing0 aCommercial applications of computerized adaptive testing aSan Antonio, TX1 aMcBride, J R uhttp://www.iacat.org/content/commercial-applications-computerized-adaptive-testing00512nas a2200097 4500008004100000245009700041210006900138260008000207100001500287856011200302 1989 eng d00aA comparison of an expert systems approach to computerized adaptive testing and an IRT model0 acomparison of an expert systems approach to computerized adaptiv aUnpublished manuscript (submitted to American Educational Research Journal)1 aFrick, T W uhttp://www.iacat.org/content/comparison-expert-systems-approach-computerized-adaptive-testing-and-irt-model00502nas a2200109 4500008004100000245011900041210006900160300001200229490000700241100002000248856012400268 1989 eng d00aA comparison of the nominal response model and the three-parameter logistic model in computerized adaptive testing0 acomparison of the nominal response model and the threeparameter  a789-8050 v491 ade Ayala, R. J. uhttp://www.iacat.org/content/comparison-nominal-response-model-and-three-parameter-logistic-model-computerized-adaptive00421nas a2200109 4500008004100000245006900041210006700110260001800177100001000195700001300205856009300218 1989 eng d00aA comparison of three adaptive testing strategies using MicroCAT0 acomparison of three adaptive testing strategies using MicroCAT aSan Francisco1 aHo, R1 aHsu, T C uhttp://www.iacat.org/content/comparison-three-adaptive-testing-strategies-using-microcat01130nas a2200157 4500008004100000245010500041210006900146300001200215490000600227520055900233100001500792700001600807700001500823700001000838856012400848 1989 eng d00aComparisons of paper-administered, computer-administered and computerized adaptive achievement tests0 aComparisons of paperadministered computeradministered and comput a311-3260 v53 aThis research study was designed to compare student achievement scores from three different testing methods: paper-administered testing, computer-administered testing, and computerized adaptive testing. The three testing formats were developed from the California Assessment Program (CAP) item banks for grades three and six. The paper-administered and the computer-administered tests were identical in item content, format, and sequence. The computerized adaptive test was a tailored or adaptive sequence of the items in the computer-administered test. 1 aOlson, J B1 aMaynes, D D1 aSlawson, D1 aHo, K uhttp://www.iacat.org/content/comparisons-paper-administered-computer-administered-and-computerized-adaptive-achievement00365nas a2200097 4500008004100000245005500041210005300096260001900149100001700168856008200185 1989 eng d00aA computerized adaptive mathematics screening test0 acomputerized adaptive mathematics screening test aBurlingame, CA1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-mathematics-screening-test00399nam a2200097 4500008004100000245004900041210004900090260006800139100001600207856007800223 1989 eng d00aComputerized adaptive personality assessment0 aComputerized adaptive personality assessment aUnpublished master’s thesis, Harvard University, Cambridge MA1 aWaller, N G uhttp://www.iacat.org/content/computerized-adaptive-personality-assessment00396nas a2200121 4500008004100000245003200041210003200073260007000105100001300175700001600188700000900204856006100213 1989 eng d00aComputerized adaptive tests0 aComputerized adaptive tests aERIC Clearinghouse on Tests, Measurement, and Evaluation, no. 1071 aGrist, S1 aRudner, L M1 aWise uhttp://www.iacat.org/content/computerized-adaptive-tests00452nas a2200097 4500008004100000245007900041210006900120260004600189100001900235856010000254 1989 eng d00aA consideration for variable length adaptive tests (Research Report 89-40)0 aconsideration for variable length adaptive tests Research Report aPrinceton NJ: Educational Testing Service1 aWingersky, M S uhttp://www.iacat.org/content/consideration-variable-length-adaptive-tests-research-report-89-4000650nas a2200097 4500008004100000245013800041210006900179260016300248100001800411856012300429 1989 eng d00aDie Optimierung der Mebgenauikeit beim branched adaptiven Testen [Optimization of measurement precision for branched-adaptive testing0 aDie Optimierung der Mebgenauikeit beim branched adaptiven Testen aK. D. Kubinger (Ed.), Moderne Testtheorie Ein Abrib samt neusten Beitrgen [Modern test theory Overview and new issues] (pp. 187-218). Weinhem, Germany: Beltz.1 aKubinger, K D uhttp://www.iacat.org/content/die-optimierung-der-mebgenauikeit-beim-branched-adaptiven-testen-optimization-measurement00395nas a2200109 4500008004500000245006000045210006000105300001200165490000700177100001500184856008600199 1989 Engldsh 00aEstimating Reliabilities of Computerized Adaptive Tests0 aEstimating Reliabilities of Computerized Adaptive Tests a145-1490 v131 aDivgi, D R uhttp://www.iacat.org/content/estimating-reliabilities-computerized-adaptive-tests00623nam a2200097 4500008004100000245016500041210007200206260009800278100001300376856013600389 1989 eng d00aÉtude de praticabilité du testing adaptatif de maîtrise des apprentissages scolaires au Québec : une expérimentation en éducation économique secondaire 50 aÉtude de praticabilité du testing adaptatif de maîtrise des appr aThèse de doctorat non publiée. Montréal : Université du Québec à Montréal. [In French]1 aAuger, R uhttp://www.iacat.org/content/%C3%A9tude-de-praticabilit%C3%A9-du-testing-adaptatif-de-ma%C3%AEtrise-des-apprentissages-scolaires-au00464nas a2200121 4500008004100000245007400041210006900115490001900184100001500203700001400218700001400232856009600246 1989 eng d00aEXSPRT: An expert systems approach to computer-based adaptive testing0 aEXSPRT An expert systems approach to computerbased adaptive test0 vSan Francisco.1 aFrick, T W1 aPlew, G T1 aLuk, H -K uhttp://www.iacat.org/content/exsprt-expert-systems-approach-computer-based-adaptive-testing00403nas a2200097 4500008004100000245007100041210006900112260001600181100001200197856009600209 1989 eng d00aGolden section search strategies for computerized adaptive testing0 aGolden section search strategies for computerized adaptive testi aBerkeley CA1 aXiao, B uhttp://www.iacat.org/content/golden-section-search-strategies-computerized-adaptive-testing00407nas a2200097 4500008004100000245007000041210006900111260002100180100001500201856009300216 1989 eng d00aIndividual differences in item selection in self adaptive testing0 aIndividual differences in item selection in self adaptive testin aSan Francisco CA1 aRocklin, T uhttp://www.iacat.org/content/individual-differences-item-selection-self-adaptive-testing00593nas a2200097 4500008004100000245018700041210006900228260005500297100001700352856012600369 1989 eng d00aThe interpretation and application of multidimensional item response theory models; and computerized testing in the instructional environment: Final Report (Research Report ONR 89-2)0 ainterpretation and application of multidimensional item response aIowa City IA: The American College Testing Program1 aReckase, M D uhttp://www.iacat.org/content/interpretation-and-application-multidimensional-item-response-theory-models-and-computerized00471nas a2200109 4500008004100000245009300041210006900134260002100203100001400224700001400238856010900252 1989 eng d00aInvestigating the validity of a computerized adaptive test for different examinee groups0 aInvestigating the validity of a computerized adaptive test for d aSan Francisco CA1 aBuhr, D C1 aLegg, S M uhttp://www.iacat.org/content/investigating-validity-computerized-adaptive-test-different-examinee-groups00493nas a2200121 4500008004100000245009800041210006900139300001200208490000600220100001400226700001400240856011700254 1989 eng d00aAn investigation of procedures for computerized adaptive testing using partial credit scoring0 ainvestigation of procedures for computerized adaptive testing us a335-3570 v21 aKoch, W R1 aDodd, B G uhttp://www.iacat.org/content/investigation-procedures-computerized-adaptive-testing-using-partial-credit-scoring00589nas a2200109 4500008004100000245012200041210006900163260009400232100001600326700001400342856012300356 1989 eng d00aItem-presentation controls for computerized adaptive testing: Content-balancing versus min-CAT (Research Report 89-1)0 aItempresentation controls for computerized adaptive testing Cont aBaltimore MD: Johns Hopkins University, Department of Psychology, Psychometric Laboratory1 aThomas, T J1 aGreen, BF uhttp://www.iacat.org/content/item-presentation-controls-computerized-adaptive-testing-content-balancing-versus-min-cat00527nas a2200133 4500008004500000245009500045210006900140300001200209490000700221100001400228700001400242700001800256856011900274 1989 Engldsh 00aOperational Characteristics of Adaptive Testing Procedures Using the Graded Response Model0 aOperational Characteristics of Adaptive Testing Procedures Using a129-1430 v131 aDodd, B G1 aKoch, W R1 aDe Ayala, R J uhttp://www.iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-graded-response-model-000523nas a2200133 4500008004100000245009500041210006900136300001200205490000700217100001400224700001400238700002000252856011700272 1989 eng d00aOperational characteristics of adaptive testing procedures using the graded response model0 aOperational characteristics of adaptive testing procedures using a129-1430 v131 aDodd, B G1 aKoch, W R1 ade Ayala, R. J. uhttp://www.iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-graded-response-model00434nas a2200121 4500008004100000245006700041210006700108300001200175490000600187100001900193700001200212856008800224 1989 eng d00aProcedures for selecting items for computerized adaptive tests0 aProcedures for selecting items for computerized adaptive tests a359-3750 v21 aKingsbury, G G1 aZara, A uhttp://www.iacat.org/content/procedures-selecting-items-computerized-adaptive-tests00510nas a2200133 4500008004100000245009200041210006900133300001200202490000700214100001400221700001500235700001200250856011400262 1989 eng d00aProviding item feedback in computer-based tests: Effects of initial success and failure0 aProviding item feedback in computerbased tests Effects of initia a479-4860 v491 aWise, S L1 aPlake, B S1 aet. al. uhttp://www.iacat.org/content/providing-item-feedback-computer-based-tests-effects-initial-success-and-failure01449nas a2200157 4500008004100000245007900041210006900120300001000189490000600199520090200205653003401107100002001141700001701161700001701178856009601195 1989 eng d00aA real-data simulation of computerized adaptive administration of the MMPI0 arealdata simulation of computerized adaptive administration of t a18-220 v13 aA real-data simulation of computerized adaptive administration of the MMPI was conducted with data obtained from two personnel-selection samples and two clinical samples. A modification of the countdown method was tested to determine the usefulness, in terms of item administration savings, of several different test administration procedures. Substantial item administration savings were achieved for all four samples, though the clinical samples required administration of more items to achieve accurate classification and/or full-scale scores than did the personnel-selection samples. The use of normative item endorsement frequencies was found to be as effective as sample-specific frequencies for the determination of item administration order. The role of computerized adaptive testing in the future of personality assessment is discussed., (C) 1989 by the American Psychological Association10acomputerized adaptive testing1 aBen-Porath, Y S1 aSlutske, W S1 aButcher, J N uhttp://www.iacat.org/content/real-data-simulation-computerized-adaptive-administration-mmpi00504nas a2200097 4500008004100000245008100041210006900122260010300191100001200294856010000306 1989 eng d00aA research proposal for field testing CAT for nursing licensure examinations0 aresearch proposal for field testing CAT for nursing licensure ex aDelegate Assembly Book of Reports 1989. Chicago: National Council of State Boards of Nursing, Inc.1 aZara, A uhttp://www.iacat.org/content/research-proposal-field-testing-cat-nursing-licensure-examinations00408nas a2200121 4500008004100000245005300041210005300094300001200147490001000159100002300169700001600192856007800208 1989 eng d00aSome procedures for computerized ability testing0 aSome procedures for computerized ability testing a175-1870 v13(2)1 avan der Linden, WJ1 aZwarts, M A uhttp://www.iacat.org/content/some-procedures-computerized-ability-testing00495nas a2200121 4500008004100000245009400041210006900135300001200204490000700216100001300223700002500236856011200261 1989 eng d00aTailored interviewing: An application of item response theory for personality measurement0 aTailored interviewing An application of item response theory for a502-5190 v531 aKamakura1 aBalasubramanian, S K uhttp://www.iacat.org/content/tailored-interviewing-application-item-response-theory-personality-measurement00357nas a2200109 4500008004100000245004800041210004700089300001000136490001000146100001500156856007600171 1989 eng d00aTesting software review: MicroCAT Version 30 aTesting software review MicroCAT Version 3 a33-380 v8 (3)1 aStone, C A uhttp://www.iacat.org/content/testing-software-review-microcat-version-300482nas a2200133 4500008004100000245007600041210006900117300001200186490000700198100001500205700001700220700001600237856009500253 1989 eng d00aTrace lines for testlets: A use of multiple-categorical-response models0 aTrace lines for testlets A use of multiplecategoricalresponse mo a247-2600 v261 aThissen, D1 aSteinberg, L1 aMooney, J A uhttp://www.iacat.org/content/trace-lines-testlets-use-multiple-categorical-response-models00491nam a2200097 4500008004100000245009300041210006900134260006200203100001700265856011100282 1988 eng d00aApplication of appropriateness measurement to a problem in computerized adaptive testing0 aApplication of appropriateness measurement to a problem in compu aUnpublished doctoral dissertation, University of Illinois1 aCandell, G L uhttp://www.iacat.org/content/application-appropriateness-measurement-problem-computerized-adaptive-testing00486nas a2200121 4500008004100000245009400041210006900135300001000204490000700214100001700221700001400238856011200252 1988 eng d00aAssessment of academic skills of learning disabled students with classroom microcomputers0 aAssessment of academic skills of learning disabled students with a81-880 v171 aWatkins, M W1 aKush, J C uhttp://www.iacat.org/content/assessment-academic-skills-learning-disabled-students-classroom-microcomputers00470nas a2200109 4500008004100000245010000041210006900141300001200210490000600222100001400228856011800242 1988 eng d00aThe College Board computerized placement tests: An application of computerized adaptive testing0 aCollege Board computerized placement tests An application of com a271-2820 v21 aWard, W C uhttp://www.iacat.org/content/college-board-computerized-placement-tests-application-computerized-adaptive-testing00509nas a2200109 4500008004100000245011200041210006900153260001900222100001900241700001600260856012300276 1988 eng d00aA comparison of achievement level estimates from computerized adaptive testing and paper-and-pencil testing0 acomparison of achievement level estimates from computerized adap aNew Orleans LA1 aKingsbury, G G1 aHouser, R L uhttp://www.iacat.org/content/comparison-achievement-level-estimates-computerized-adaptive-testing-and-paper-and-pencil00524nas a2200133 4500008004100000245009300041210006900134260001500203100002000218700001600238700001700254700001700271856010200288 1988 eng d00aA comparison of two methods for the adaptive administration of the MMPI-2 content scales0 acomparison of two methods for the adaptive administration of the aAtlanta GA1 aBen-Porath, Y S1 aWaller, N G1 aSlutske, W S1 aButcher, J N uhttp://www.iacat.org/content/comparison-two-methods-adaptive-administration-mmpi-2-content-scales00524nas a2200121 4500008004100000245010800041210006900149260001600218100001400234700001400248700002000262856012000282 1988 eng d00aComputerized adaptive attitude measurement: A comparison of the graded response and rating scale models0 aComputerized adaptive attitude measurement A comparison of the g aNew Orleans1 aDodd, B G1 aKoch, W R1 ade Ayala, R. J. uhttp://www.iacat.org/content/computerized-adaptive-attitude-measurement-comparison-graded-response-and-rating-scale00533nas a2200121 4500008004100000245010800041210006900149300000900218490000700227653003400234100002000268856012300288 1988 eng d00aComputerized adaptive testing: A comparison of the nominal response model and the three parameter model0 aComputerized adaptive testing A comparison of the nominal respon a31480 v4810acomputerized adaptive testing1 ade Ayala, R. J. uhttp://www.iacat.org/content/computerized-adaptive-testing-comparison-nominal-response-model-and-three-parameter-model00479nas a2200121 4500008004100000245008700041210006900128300001000197490001100207100001900218700001200237856010800249 1988 eng d00aComputerized adaptive testing: A four-year-old pilot study shows that CAT can work0 aComputerized adaptive testing A fouryearold pilot study shows th a73-760 v16 (4)1 aKingsbury, G G1 aet. al. uhttp://www.iacat.org/content/computerized-adaptive-testing-four-year-old-pilot-study-shows-cat-can-work00431nas a2200097 4500008004100000245008000041210006900121260002800190100001700218856009800235 1988 eng d00aComputerized adaptive testing: a good idea waiting for the right technology0 aComputerized adaptive testing a good idea waiting for the right  aNew Orleans, April 19881 aReckase, M D uhttp://www.iacat.org/content/computerized-adaptive-testing-good-idea-waiting-right-technology00442nas a2200097 4500008004100000245008900041210006900130100001800199700001300217856011400230 1988 eng d00aComputerized adaptive testing program at Miami-Dade Community College, South Campous0 aComputerized adaptive testing program at MiamiDade Community Col1 aSchinoff, R B1 aStead, L uhttp://www.iacat.org/content/computerized-adaptive-testing-program-miami-dade-community-college-south-campous00494nas a2200097 4500008004100000245009800041210006900139260002800208100005100236856010900287 1988 eng d00aComputerized adaptive testing: The state of the art in assessment at three community colleges0 aComputerized adaptive testing The state of the art in assessment aLaguna Hills CA: Author1 aLeague-for-Innovation-in-the-Community-College uhttp://www.iacat.org/content/computerized-adaptive-testing-state-art-assessment-three-community-colleges00501nam a2200097 4500008004100000245009800041210006900139260006800208100001600276856011100292 1988 eng d00aComputerized adaptive testing: The state of the art in assessment at three community colleges0 aComputerized adaptive testing The state of the art in assessment aLaguna Hills CA: League for Innovation in the Community College1 aDoucette, D uhttp://www.iacat.org/content/computerized-adaptive-testing-state-art-assessment-three-community-colleges-000402nas a2200097 4500008004100000245007100041210006900112260001500181100001700196856009100213 1988 eng d00aA computerized adaptive version of the Differential Aptitude Tests0 acomputerized adaptive version of the Differential Aptitude Tests aAtlanta GA1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-version-differential-aptitude-tests00337nas a2200121 4500008004100000245003300041210003300074300001200107490000600119100001300125700001500138856006200153 1988 eng d00aComputerized mastery testing0 aComputerized mastery testing a283-2860 v21 aLewis, C1 aSheehan, K uhttp://www.iacat.org/content/computerized-mastery-testing00405nas a2200097 4500008004100000245004700041210004600088260008600134100001400220856007300234 1988 eng d00aConstruct validity of computer-based tests0 aConstruct validity of computerbased tests aH. Wainer and H. Braun (Eds.), Test validity (pp. 77-103). Hillsdale NJ: Erlbaum.1 aGreen, BF uhttp://www.iacat.org/content/construct-validity-computer-based-tests00411nas a2200109 4500008004100000245007100041210006500112300001200177490000600189100001400195856009200209 1988 eng d00aCritical problems in computer-based psychological measurement, , ,0 aCritical problems in computerbased psychological measurement a223-2310 v11 aGreen, BF uhttp://www.iacat.org/content/critical-problems-computer-based-psychological-measurement00540nas a2200109 4500008004100000245011600041210006900157260005300226100001400279700001700293856012000310 1988 eng d00aThe development and evaluation of a microcomputerized adaptive placement testing system for college mathematics0 adevelopment and evaluation of a microcomputerized adaptive place a1986 (San Francisco CA) and 1987 (Washington DC)1 aHsu, T -C1 aShermis, M D uhttp://www.iacat.org/content/development-and-evaluation-microcomputerized-adaptive-placement-testing-system-college00557nas a2200109 4500008004100000245013000041210006900171260005400240100001400294700001600308856012300324 1988 eng d00aThe equivalence of scores from automated and conventional educational and psychological tests (College Board Report No. 88-8)0 aequivalence of scores from automated and conventional educationa aNew York: The College Entrance Examination Board.1 aMazzeo, J1 aHarvey, A L uhttp://www.iacat.org/content/equivalence-scores-automated-and-conventional-educational-and-psychological-tests-college00491nas a2200097 4500008004100000245012800041210006900169100001500238700001600253856012400269 1988 eng d00aFitting the two-parameter model to personality data: The parameterization of the Multidimensional Personality Questionnaire0 aFitting the twoparameter model to personality data The parameter1 aReise, S P1 aWaller, N G uhttp://www.iacat.org/content/fitting-two-parameter-model-personality-data-parameterization-multidimensional-personality00525nas a2200121 4500008003900000245008900039210006900128260004700197100001900244700001600263700001500279856010900294 1988 d00aThe four generations of computerized educational measurement (Research Report 98-35)0 afour generations of computerized educational measurement Researc aPrinceton NJ: Educational Testing Service.1 aBunderson, C V1 aInouye, D K1 aOlsen, J B uhttp://www.iacat.org/content/four-generations-computerized-educational-measurement-research-report-98-3500496nas a2200109 4500008004100000245012500041210006900166300001000235490000600245100001200251856012300263 1988 eng d00aIntroduction to item response theory and computerized adaptive testing as applied in licensure and certification testing0 aIntroduction to item response theory and computerized adaptive t a11-170 v61 aZara, A uhttp://www.iacat.org/content/introduction-item-response-theory-and-computerized-adaptive-testing-applied-licensure-and00456nas a2200133 4500008004100000245006600041210006600107300001200173490000700185100000900192700001400201700002200215856008500237 1988 eng d00aItem pool maintenance in the presence of item parameter drift0 aItem pool maintenance in the presence of item parameter drift a275-2850 v251 aBock1 aMuraki, E1 aPfeiffenberger, W uhttp://www.iacat.org/content/item-pool-maintenance-presence-item-parameter-drift00386nas a2200109 4500008004100000245005500041210005300096260001900149100001500168700001400183856007900197 1988 eng d00aA predictive analysis approach to adaptive testing0 apredictive analysis approach to adaptive testing aNew Orleans LA1 aKirisci, L1 aHsu, T -C uhttp://www.iacat.org/content/predictive-analysis-approach-adaptive-testing00489nas a2200097 4500008004100000245007700041210006900118260009100187100001600278856009700294 1988 eng d00aA procedure for scoring incomplete adaptive tests in high stakes testing0 aprocedure for scoring incomplete adaptive tests in high stakes t aUnpublished manuscript. San Diego, CA: Navy Personnel Research and Development Center1 aSegall, D O uhttp://www.iacat.org/content/procedure-scoring-incomplete-adaptive-tests-high-stakes-testing01299nas a2200109 4500008004100000245007900041210006900120260003600189520085200225100002001077856009201097 1988 eng d00aThe Rasch model and missing data, with an emphasis on tailoring test items0 aRasch model and missing data with an emphasis on tailoring test  aNew Orleans, LA. USAcApril 5-93 aMany applications of educational testing have a missing data aspect (MDA). This MDA is perhaps most pronounced in item banking, where each examinee responds to a different subtest of items from a large item pool and where both person and item parameter estimates are needed. The Rasch model is emphasized, and its non-parametric counterpart (the Mokken scale) is considered. The possibility of tailoring test items in combination with their estimation is discussed; however, most methods for the estimation of item parameters are inadequate under tailoring. Without special measures, only marginal maximum likelihood produces adequate item parameter estimates under item tailoring. Fischer's approximate minimum-chi-square method for estimation of item parameters for the Rasch model is discussed, which efficiently produces item parameters. (TJH)1 aGruijter, D N M uhttp://www.iacat.org/content/rasch-model-and-missing-data-emphasis-tailoring-test-items00336nas a2200109 4500008004100000245004400041210003900085300001000124490000700134100001600141856006900157 1988 eng d00aThe Rasch model and multi-stage testing0 aRasch model and multistage testing a45-520 v131 aGlas, C A W uhttp://www.iacat.org/content/rasch-model-and-multi-stage-testing00480nas a2200097 4500008004100000245007000041210006200111260010100173100001800274856009000292 1988 eng d00aOn a Rasch-model-based test for non-computerized adaptive testing0 aRaschmodelbased test for noncomputerized adaptive testing aLangeheine, R. and Rost, J. (Ed.), Latent trait and latent class models. New York: Plenum Press.1 aKubinger, K D uhttp://www.iacat.org/content/rasch-model-based-test-non-computerized-adaptive-testing00437nas a2200121 4500008004100000245005900041210005600100260002200156100001700178700002000195700001700215856008300232 1988 eng d00aA real-data simulation of adaptive MMPI administration0 arealdata simulation of adaptive MMPI administration aSt. Petersburg FL1 aSlutske, W S1 aBen-Porath, Y S1 aButcher, J N uhttp://www.iacat.org/content/real-data-simulation-adaptive-mmpi-administration00622nas a2200145 4500008004100000245011100041210006900152260005400221100001400275700001700289700001400306700001600320700001700336856012300353 1988 eng d00aRefinement of the Computerized Adaptive Screening Test (CAST) (Final Report, Contract No MDA203 06-C-0373)0 aRefinement of the Computerized Adaptive Screening Test CAST Fina aWashington, DC: American Institutes for Research.1 aWise, L L1 aMcHenry, J J1 aChia, W J1 aSzenas, P L1 aMcBride, J R uhttp://www.iacat.org/content/refinement-computerized-adaptive-screening-test-cast-final-report-contract-no-mda203-06-c00428nas a2200097 4500008004100000245007000041210006400111260004600175100001800221856009100239 1988 eng d00aScale drift in on-line calibration (Research Report RR-88-28-ONR)0 aScale drift in online calibration Research Report RR8828ONR aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/scale-drift-line-calibration-research-report-rr-88-28-onr00427nas a2200097 4500008004100000245006900041210006400110260004900174100001800223856008800241 1988 eng d00aScale drift in on-line calibration (Tech Rep. No. ERIC ED389710)0 aScale drift in online calibration Tech Rep No ERIC ED389710 aEducational Testing Service, Princeton, N.J.1 aStocking, M L uhttp://www.iacat.org/content/scale-drift-line-calibration-tech-rep-no-eric-ed38971000399nas a2200097 4500008004100000245006800041210006500109260001900174100001700193856009100210 1988 eng d00aSimple and effective algorithms [for] computer-adaptive testing0 aSimple and effective algorithms for computeradaptive testing aNew Orleans LA1 aLinacre, J M uhttp://www.iacat.org/content/simple-and-effective-algorithms-computer-adaptive-testing00480nas a2200097 4500008004100000245009200041210006900133260004600202100001800248856011600266 1988 eng d00aSome considerations in maintaining adaptive test item pools (Research Report 88-33-ONR)0 aSome considerations in maintaining adaptive test item pools Rese aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/some-considerations-maintaining-adaptive-test-item-pools-research-report-88-33-onr00485nas a2200097 4500008004100000245009400041210006900135260004900204100001800253856011600271 1988 eng d00aSome considerations in maintaining adaptive test item pools (Tech Rep. No. ERIC ED391814)0 aSome considerations in maintaining adaptive test item pools Tech aEducational Testing Service, Princeton, N.J.1 aStocking, M L uhttp://www.iacat.org/content/some-considerations-maintaining-adaptive-test-item-pools-tech-rep-no-eric-ed39181400398nam a2200097 4500008004100000245006000041210005900101260002500160100003500185856008000220 1988 eng d00aUsers manual for the MicroCAT Testing System, Version 30 aUsers manual for the MicroCAT Testing System Version 3 aSt. Paul MN: Author.1 aAssessment-Systems-Corporation uhttp://www.iacat.org/content/users-manual-microcat-testing-system-version-300561nam a2200097 4500008004100000245011600041210006900157260009800226100001700324856012200341 1987 eng d00aAn adaptive test of musical memory: An application of item response theory to the assessment of musical ability0 aadaptive test of musical memory An application of item response  aDoctoral dissertation, University of Illinois. Dissertation Abstracts International, 49, 79A.1 aVispoel, W P uhttp://www.iacat.org/content/adaptive-test-musical-memory-application-item-response-theory-assessment-musical-ability00302nas a2200121 4500008004100000245002100041210002100062300001200083490000700095100001400102700001400116856005000130 1987 eng d00aAdaptive testing0 aAdaptive testing a249-2620 v361 aWeiss, DJ1 aVale, C D uhttp://www.iacat.org/content/adaptive-testing00457nas a2200097 4500008003900000245006400039210006200103260009200165100001500257856008700272 1987 d00aAdaptive testing, information, and the partial credit model0 aAdaptive testing information and the partial credit model aMelbourne, Australia: University of Melbourne, Center for the Study of Higher Education1 aAdams, R J uhttp://www.iacat.org/content/adaptive-testing-information-and-partial-credit-model00486nas a2200121 4500008004100000245009700041210006900138300001200207490000700219100001100226700001500237856011200252 1987 eng d00aCATS, testlets, and test construction: A rationale for putting test developers back into CAT0 aCATS testlets and test construction A rationale for putting test a185-2020 v321 aWainer1 aKiely, G L uhttp://www.iacat.org/content/cats-testlets-and-test-construction-rationale-putting-test-developers-back-cat00468nas a2200097 4500008004100000245008500041210006900126260005500195100001700250856010300267 1987 eng d00aA computer program for adaptive testing by microcomputer (MESA Memorandum No 40)0 acomputer program for adaptive testing by microcomputer MESA Memo aChicago: University of Chicago. (ERIC ED 280 895.)1 aLinacre, J M uhttp://www.iacat.org/content/computer-program-adaptive-testing-microcomputer-mesa-memorandum-no-4000469nas a2200097 4500008004100000245006900041210006800110260008200178100001600260856009500276 1987 eng d00aComputerized adaptive language testing: A Spanish placement exam0 aComputerized adaptive language testing A Spanish placement exam aIn Language Testing Research Selected Papers from the Colloquium, Monterey CA1 aLarson, J W uhttp://www.iacat.org/content/computerized-adaptive-language-testing-spanish-placement-exam00515nas a2200109 4500008004100000245011700041210006900158260001800227100002000245700001400265856012600279 1987 eng d00aComputerized adaptive testing: A comparison of the nominal response model and the three-parameter logistic model0 aComputerized adaptive testing A comparison of the nominal respon aWashington DC1 ade Ayala, R. J.1 aKoch, W R uhttp://www.iacat.org/content/computerized-adaptive-testing-comparison-nominal-response-model-and-three-parameter-logistic00580nas a2200109 4500008004100000245009200041210006900133260012300202100001400325700001400339856011700353 1987 eng d00aComputerized adaptive testing for measuring abilities and other psychological variables0 aComputerized adaptive testing for measuring abilities and other  aJ. N. Butcher (Ed.), Computerized personality measurement: A practitioners guide (pp. 325-343). New York: Basic Books.1 aWeiss, DJ1 aVale, C D uhttp://www.iacat.org/content/computerized-adaptive-testing-measuring-abilities-and-other-psychological-variables00487nas a2200097 4500008004100000245011900041210006900160260002200229100001700251856012100268 1987 eng d00aComputerized adaptive testing made practical: The Computerized Adaptive Edition of the Differential Aptitude Tests0 aComputerized adaptive testing made practical The Computerized Ad aSan Francisco, CA1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-made-practical-computerized-adaptive-edition-differential00371nas a2200097 4500008004100000245006200041210006200103260001200165100001400177856008200191 1987 eng d00aComputerized adaptive testing with the rating scale model0 aComputerized adaptive testing with the rating scale model aChicago1 aDodd, B G uhttp://www.iacat.org/content/computerized-adaptive-testing-rating-scale-model00443nas a2200133 4500008004100000245006200041210006100103300001000164490000600174100001000180700001500190700001400205856009000219 1987 eng d00aComputerized psychological testing: Overview and critique0 aComputerized psychological testing Overview and critique a42-510 v11 aBurke1 aNormand, J1 aRaju, N M uhttp://www.iacat.org/content/computerized-psychological-testing-overview-and-critique00620nas a2200133 4500008004100000245011200041210006900153260003800222653003400260653003800294100001500332700001700347856012200364 1987 eng d00aThe effect of item parameter estimation error on decisions made using the sequential probability ratio test0 aeffect of item parameter estimation error on decisions made usin aIowa City, IA. USAbDTIC Document10acomputerized adaptive testing10aSequential probability ratio test1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/effect-item-parameter-estimation-error-decisions-made-using-sequential-probability-ratio00570nas a2200109 4500008004100000245015100041210006900192260004300261100001500304700001700319856012400336 1987 eng d00aThe effect of item parameter estimation error on the decisions made using the sequential probability ratio test (ACT Research Report Series 87-17)0 aeffect of item parameter estimation error on the decisions made  aIowa City IA: American College Testing1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/effect-item-parameter-estimation-error-decisions-made-using-sequential-probability-ratio-000497nam a2200097 4500008004100000245010100041210006900142260005600211100001700267856011500284 1987 eng d00aThe effects of variable entry on bias and information of the Bayesian adaptive testing procedure0 aeffects of variable entry on bias and information of the Bayesia aDissertation Abstracts International, 47 (8A), 30131 aHankins, J A uhttp://www.iacat.org/content/effects-variable-entry-bias-and-information-bayesian-adaptive-testing-procedure-000473nas a2200121 4500008004100000245008200041210006900123260001300192100001700205700001500222700001200237856010200249 1987 eng d00aEquating the computerized adaptive edition of the Differential Aptitude Tests0 aEquating the computerized adaptive edition of the Differential A aNew York1 aMcBride, J R1 aCorpe, V A1 aWing, H uhttp://www.iacat.org/content/equating-computerized-adaptive-edition-differential-aptitude-tests-000512nas a2200097 4500008004100000245012400041210006900165260004500234100001700279856011800296 1987 eng d00aEquivalent-groups versus single-group equating designs for the Accelerated CAT-ASVAB Project (Research Memorandum 87-6)0 aEquivalentgroups versus singlegroup equating designs for the Acc aAlexandria VA: Center for Naval Analyses1 aStoloff, P H uhttp://www.iacat.org/content/equivalent-groups-versus-single-group-equating-designs-accelerated-cat-asvab-project00513nas a2200109 4500008004100000245008700041210006900128260007500197100001400272700001400286856010300300 1987 eng d00aFinal report: Feasibility study of a computerized test administration of the CLAST0 aFinal report Feasibility study of a computerized test administra aUniversity of Florida: Institute for Student Assessment and Evaluation1 aLegg, S M1 aBuhr, D C uhttp://www.iacat.org/content/final-report-feasibility-study-computerized-test-administration-clast00529nas a2200109 4500008004100000245011300041210006900154260003800223100001800261700001400279856012600293 1987 eng d00aFull-information item factor analysis from the ASVAB CAT item pool (Methodology Research Center Report 87-1)0 aFullinformation item factor analysis from the ASVAB CAT item poo aChicago IL: University of Chicago1 aZimowski, M F1 aBock, R D uhttp://www.iacat.org/content/full-information-item-factor-analysis-asvab-cat-item-pool-methodology-research-center-report00540nas a2200121 4500008004100000245011700041210006900158260002700227100001200254700001300266700001400279856012500293 1987 eng d00aFunctional and design specifications for the National Council of State Boards of Nursing adaptive testing system0 aFunctional and design specifications for the National Council of aUnpublished manuscript1 aZara, A1 aBosma, J1 aKaplan, R uhttp://www.iacat.org/content/functional-and-design-specifications-national-council-state-boards-nursing-adaptive-testing00507nas a2200097 4500008004100000245007400041210006900115260011200184100001700296856009600313 1987 eng d00aImproving the measurement of musical ability through adaptive testing0 aImproving the measurement of musical ability through adaptive te aG. Hayes (Ed.), Proceedings of the 29th International ADCIS Conference (pp. 221-228). Bellingham WA: ADCIS.1 aVispoel, W P uhttp://www.iacat.org/content/improving-measurement-musical-ability-through-adaptive-testing00443nas a2200121 4500008003900000245007300039210006900112300001200181490000700193100001100200700001500211856009500226 1987 d00aItem clusters and computerized adaptive testing: A case for testlets0 aItem clusters and computerized adaptive testing A case for testl a185-2010 v241 aWainer1 aKiely, G L uhttp://www.iacat.org/content/item-clusters-and-computerized-adaptive-testing-case-testlets00520nas a2200109 4500008004100000245012700041210006900168260002100237100001600258700001400274856012200288 1987 eng d00aMultidimensional adaptive testing: A procedure for sequential estimation of the posterior centroid and dispersion of theta0 aMultidimensional adaptive testing A procedure for sequential est aMontreal, Canada1 aBloxom, B M1 aVale, C D uhttp://www.iacat.org/content/multidimensional-adaptive-testing-procedure-sequential-estimation-posterior-centroid-and00509nas a2200097 4500008004100000245011600041210006900157260004500226100001500271856012500286 1987 eng d00aProperties of some Bayesian scoring procedures for computerized adaptive tests (Research Memorandum CRM 87-161)0 aProperties of some Bayesian scoring procedures for computerized  aAlexandria VA: Center for Naval Analyses1 aDivgi, D R uhttp://www.iacat.org/content/properties-some-bayesian-scoring-procedures-computerized-adaptive-tests-research-memorandum00493nas a2200121 4500008004100000245009300041210006900134300001200203490000700215100001200222700002100234856011600255 1987 eng d00aSelf-adapted testing: A performance improving variation of computerized adaptive testing0 aSelfadapted testing A performance improving variation of compute a315-3190 v791 aRocklin1 aO’Donnell, A M uhttp://www.iacat.org/content/self-adapted-testing-performance-improving-variation-computerized-adaptive-testing00425nas a2200109 4500008004100000245007100041210006900112300001200181490000700193100001800200856009700218 1987 eng d00aTwo simulated feasibility studies in computerized adaptive testing0 aTwo simulated feasibility studies in computerized adaptive testi a263-2770 v361 aStocking, M L uhttp://www.iacat.org/content/two-simulated-feasibility-studies-computerized-adaptive-testing01146nas a2200133 4500008004100000020001000041245010100051210006900152260004000221300000700261520060900268100001800877856011700895 1987 eng d a87-1300aThe use of unidimensional item parameter estimates of multidimensional items in adaptive testing0 ause of unidimensional item parameter estimates of multidimension aIowa City, IAbACTcSeptember, 1987 a333 aInvestigated the effect of using multidimensional (MDN) items in a computer adaptive test setting that assumes a unidimensional item response theory model in 2 experiments, using generated and real data in which difficulty was known to be confounded with dimensionality. Results from simulations suggest that univariate calibration of MDN data filtered out multidimensionality. The closer an item's MDN composite aligned itself with the calibrated univariate ability scale's orientation, the larger was the estimated discrimination parameter. (PsycINFO Database Record (c) 2003 APA, all rights reserved).1 aAckerman, T A uhttp://www.iacat.org/content/use-unidimensional-item-parameter-estimates-multidimensional-items-adaptive-testing00431nas a2200109 4500008004100000245007500041210006900116300000900185490000900194100001800203856010000221 1987 eng d00aWilcox' closed sequential testing procedure in stratified item domains0 aWilcox closed sequential testing procedure in stratified item do a3-120 v1(1)1 aGruijter, D N uhttp://www.iacat.org/content/wilcox-closed-sequential-testing-procedure-stratified-item-domains01524nas a2200157 4500008004100000020001400041245008900055210006900144300001000213490000700223520095700230653003401187100001801221700002001239856010701259 1986 eng d a0013-164400aAn application of computer adaptive testing with communication handicapped examinees0 aapplication of computer adaptive testing with communication hand a23-350 v463 aThis study was conducted to evaluate a computerized adaptive testing procedure for the measurement of mathematical skills of entry level deaf college students. The theoretical basis of the study was the Rasch model for person measurement. Sixty persons were tested using an Apple II Plus microcomputer. Ability estimates provided by the computerized procedure were compared for stability with those obtained six to eight weeks earlier from conventional (written) testing of the same subject matter. Students' attitudes toward their testing experiences also were measured. Substantial increases in measurement efficiency (by reducing test length) were realized through the adaptive testing procedure. Because the item pool used was not specifically designed for adaptive testing purposes, the psychometric quality of measurements resulting from the different testing methods was approximately equal. Attitudes toward computerized testing were favorable.10acomputerized adaptive testing1 aGarrison, W M1 aBaumgarten, B S uhttp://www.iacat.org/content/application-computer-adaptive-testing-communication-handicapped-examinees00565nas a2200109 4500008004100000245012200041210006900163260007500232100001100307700001500318856012200333 1986 eng d00aCATs, testlets, and test construction: A rationale for putting test developers back into CAT (Technical Report 86-71)0 aCATs testlets and test construction A rationale for putting test aPrinceton NJ: Educational Testing Service, Program Statistics Research1 aWainer1 aKiely, G L uhttp://www.iacat.org/content/cats-testlets-and-test-construction-rationale-putting-test-developers-back-cat-technical00432nas a2200097 4500008004100000245005700041210005500098260007900153100001800232856008400250 1986 eng d00aA cognitive error diagnostic adaptive testing system0 acognitive error diagnostic adaptive testing system athe 28th ADCIS International Conference Proceedings. Washington DC: ADCIS.1 aTatsuoka, K K uhttp://www.iacat.org/content/cognitive-error-diagnostic-adaptive-testing-system00567nas a2200121 4500008004100000245011900041210006900160260004800229100001400277700001500291700001600306856012300322 1986 eng d00aCollege Board computerized placement tests: Validation of an adaptive test of basic skills (Research Report 86-29)0 aCollege Board computerized placement tests Validation of an adap aPrinceton NJ: Educational Testing Service.1 aWard, W C1 aKline, R G1 aFlaugher, J uhttp://www.iacat.org/content/college-board-computerized-placement-tests-validation-adaptive-test-basic-skills-research00566nas a2200133 4500008004100000245012100041210006900162260002100231100001500252700001600267700001500283700001000298856012400308 1986 eng d00aComparison and equating of paper-administered, computer-administered, and computerized adaptive tests of achievement0 aComparison and equating of paperadministered computeradministere aSan Francisco CA1 aOlsen, J B1 aMaynes, D D1 aSlawson, D1 aHo, K uhttp://www.iacat.org/content/comparison-and-equating-paper-administered-computer-administered-and-computerized-adaptive00386nas a2200097 4500008004100000245006300041210006000104260002100164100001700185856008600202 1986 eng d00aA computer-adaptive placement test for college mathematics0 acomputeradaptive placement test for college mathematics aSan Francisco CA1 aShermis, M D uhttp://www.iacat.org/content/computer-adaptive-placement-test-college-mathematics00404nas a2200109 4500008004100000245005900041210005800100260002100158100001700179700001300196856008500209 1986 eng d00aComputerized adaptive achievement testing: A prototype0 aComputerized adaptive achievement testing A prototype aSan Francisco CA1 aMcBride, J R1 aMoe, K C uhttp://www.iacat.org/content/computerized-adaptive-achievement-testing-prototype00405nas a2200097 4500008004100000245007100041210006900112260001600181100001700197856009300214 1986 eng d00aA computerized adaptive edition of the Differential Aptitude Tests0 acomputerized adaptive edition of the Differential Aptitude Tests aBoulder, CO1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-edition-differential-aptitude-tests-000405nas a2200097 4500008004100000245007100041210006900112260001800181100001700199856009100216 1986 eng d00aA computerized adaptive edition of the Differential Aptitude Tests0 acomputerized adaptive edition of the Differential Aptitude Tests aWashington DC1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-edition-differential-aptitude-tests00518nas a2200097 4500008004100000245005100041210005000092260018200142100001900324856007700343 1986 eng d00aComputerized adaptive testing: A pilot project0 aComputerized adaptive testing A pilot project aW. C. Ryan (ed.), Proceedings: NECC 86, National Educational Computing Conference (pp.172-176). Eugene OR: University of Oregon, International Council on Computers in Education.1 aKingsbury, G G uhttp://www.iacat.org/content/computerized-adaptive-testing-pilot-project00319nas a2200109 4500008004100000245003600041210003600077300001000113490000600123100001500129856006500144 1986 eng d00aComputerized testing technology0 aComputerized testing technology a71-780 v41 aWolfe, J H uhttp://www.iacat.org/content/computerized-testing-technology00533nas a2200097 4500008004100000245014000041210006900181260004500250100001500295856012500310 1986 eng d00aDetermining the sensitivity of CAT-ASVAB scores to changes in item response curves with the medium of administration (Report No.86-189)0 aDetermining the sensitivity of CATASVAB scores to changes in ite aAlexandria VA: Center for Naval Analyses1 aDivgi, D R uhttp://www.iacat.org/content/determining-sensitivity-cat-asvab-scores-changes-item-response-curves-medium-administration00433nas a2200109 4500008004100000245008100041210006900122300001200191490000700203100001300210856010000223 1986 eng d00aThe effects of computer experience on computerized adaptive test performance0 aeffects of computer experience on computerized adaptive test per a727-7330 v461 aLee, J A uhttp://www.iacat.org/content/effects-computer-experience-computerized-adaptive-test-performance00443nas a2200121 4500008004100000245007300041210006900114300001000183490000700193100001100200700001400211856009600225 1986 eng d00aEquivalence of conventional and computer presentation of speed tests0 aEquivalence of conventional and computer presentation of speed t a23-340 v101 aGreaud1 aGreen, BF uhttp://www.iacat.org/content/equivalence-conventional-and-computer-presentation-speed-tests00431nas a2200097 4500008004100000245007000041210006700111260004700178100001500225856009300240 1986 eng d00aFinal report: Adaptive testing of spatial abilities (ONR 150 531)0 aFinal report Adaptive testing of spatial abilities ONR 150 531 aPrinceton, NJ: Educational Testing Service1 aBejar, I I uhttp://www.iacat.org/content/final-report-adaptive-testing-spatial-abilities-onr-150-53100550nas a2200097 4500008004100000245010100041210006900142260010900211100001700320856011500337 1986 eng d00aFinal report: The use of tailored testing with instructional programs (Research Report ONR 86-1)0 aFinal report The use of tailored testing with instructional prog aIowa City IA: The American College Testing Program, Assessment Programs Area, Test Development Division.1 aReckase, M D uhttp://www.iacat.org/content/final-report-use-tailored-testing-instructional-programs-research-report-onr-86-100522nas a2200121 4500008004100000245006500041210006100106260009600167100001900263700001600282700001500298856008700313 1986 eng d00aThe four generations of computerized educational measurement0 afour generations of computerized educational measurement aIn R. L. Linn (Ed.), Educational Measurement (3rd ed and pp. 367-407). New York: Macmillan.1 aBunderson, C V1 aInouye, D K1 aOlsen, J B uhttp://www.iacat.org/content/four-generations-computerized-educational-measurement00483nas a2200097 4500008004100000245011800041210006900159260002000228100001500248856012200263 1986 eng d00aMeasuring up in an individualized way with CAT-ASVAB: Considerations in the development of adaptive testing pools0 aMeasuring up in an individualized way with CATASVAB Consideratio aSan Franciso CA1 aSchartz, M uhttp://www.iacat.org/content/measuring-individualized-way-cat-asvab-considerations-development-adaptive-testing-pools00482nas a2200109 4500008004100000245009200041210006900133260002100202100001400223700001700237856011800254 1986 eng d00aOperational characteristics of adaptive testing procedures using partial credit scoring0 aOperational characteristics of adaptive testing procedures using aSan Francisco CA1 aKoch, W R1 aG., Dodd., B uhttp://www.iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-partial-credit-scoring00456nas a2200109 4500008004100000245008500041210006900126300001200195490000700207100002400214856010800238 1986 eng d00aSome applications of optimization algorithms in test design and adaptive testing0 aSome applications of optimization algorithms in test design and  a381-3890 v101 aTheunissen, T J J M uhttp://www.iacat.org/content/some-applications-optimization-algorithms-test-design-and-adaptive-testing00462nas a2200109 4500008004500000245008500045210006900130300001200199490000700211100002400218856011000242 1986 Engldsh 00aSome Applications of Optimization Algorithms in Test Design and Adaptive Testing0 aSome Applications of Optimization Algorithms in Test Design and  a381-3890 v101 aTheunissen, T J J M uhttp://www.iacat.org/content/some-applications-optimization-algorithms-test-design-and-adaptive-testing-000397nas a2200109 4500008004100000245006200041210006100103300001000164490000700174100001800181856008800199 1986 eng d00aUsing microcomputer-based assessment in career counseling0 aUsing microcomputerbased assessment in career counseling a50-560 v231 aThompson, D L uhttp://www.iacat.org/content/using-microcomputer-based-assessment-career-counseling00649nas a2200121 4500008004100000245022600041210006900267300000900336490000700345653003400352100001900386856012200405 1985 eng d00aAdaptive self-referenced testing as a procedure for the measurement of individual change due to instruction: A comparison of the reliabilities of change estimates obtained from conventional and adaptive testing procedures0 aAdaptive selfreferenced testing as a procedure for the measureme a30570 v4510acomputerized adaptive testing1 aKingsbury, G G uhttp://www.iacat.org/content/adaptive-self-referenced-testing-procedure-measurement-individual-change-due-instruction00309nas a2200109 4500008004100000245003300041210003300074300001200107490000700119100001400126856005900140 1985 eng d00aAdaptive testing by computer0 aAdaptive testing by computer a774-7890 v531 aWeiss, DJ uhttp://www.iacat.org/content/adaptive-testing-computer00446nas a2200121 4500008004100000245007200041210006900113300000800182490000600190100002000196700001400216856009400230 1985 eng d00aALPHATAB: A lookup table for Bayesian computerized adaptive testing0 aALPHATAB A lookup table for Bayesian computerized adaptive testi a3260 v91 ade Ayala, R. J.1 aKoch, W R uhttp://www.iacat.org/content/alphatab-lookup-table-bayesian-computerized-adaptive-testing00623nas a2200133 4500008004100000245012600041210006900167260006700236100001900303700001400322700001600336700001500352856012200367 1985 eng d00aArmed Services Vocational Aptitude Battery: Development of an adaptive item pool (AFHLR-TR-85-19; Technical Rep No 85-19)0 aArmed Services Vocational Aptitude Battery Development of an ada aBrooks Air Force Base TX: Air Force Human Resources Laboratory1 aPrestwood, J S1 aVale, C D1 aMassey, R H1 aWelsh, J R uhttp://www.iacat.org/content/armed-services-vocational-aptitude-battery-development-adaptive-item-pool-afhlr-tr-85-1900361nas a2200109 4500008004100000245004700041210004700088260001200135100001400147700001400161856007600175 1985 eng d00aComputerized adaptive attitude measurement0 aComputerized adaptive attitude measurement aChicago1 aKoch, W R1 aDodd, B G uhttp://www.iacat.org/content/computerized-adaptive-attitude-measurement00316nas a2200109 4500008004100000245003400041210003400075300001000109490000700119100001700126856006300143 1985 eng d00aComputerized adaptive testing0 aComputerized adaptive testing a25-280 v431 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing00379nas a2200097 4500008004100000245006200041210006100103260001600164100001700180856008400197 1985 eng d00aComputerized adaptive testing: An overview and an example0 aComputerized adaptive testing An overview and an example aBoulder, CO1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-overview-and-example00479nas a2200121 4500008004100000245008600041210006900127300001000196490000700206100001700213700001600230856011100246 1985 Eng d00aControlling item exposure conditional on ability in computerized adaptive testing0 aControlling item exposure conditional on ability in computerized a57-750 v231 aSympson, J B1 aHetter, R D uhttp://www.iacat.org/content/controlling-item-exposure-conditional-ability-computerized-adaptive-testing-000572nas a2200109 4500008004100000245006900041210006800110260015600178100001700334700001600351856009500367 1985 eng d00aControlling item-exposure rates in computerized adaptive testing0 aControlling itemexposure rates in computerized adaptive testing aProceedings of the 27th annual meeting of the Military Testing Association (pp. 973-977). San Diego CA: Navy Personnel Research and Development Center.1 aSympson, J B1 aHetter, R D uhttp://www.iacat.org/content/controlling-item-exposure-rates-computerized-adaptive-testing01634nas a2200145 4500008004100000245008600041210006900127300001200196490000700208520111300215100001701328700001601345700001501361856011201376 1985 eng d00aCurrent developments and future directions in computerized personality assessment0 aCurrent developments and future directions in computerized perso a803-8150 v533 aAlthough computer applications in personality assessment have burgeoned rapidly in recent years, the majority of these uses capitalize on the computer's speed, accuracy, and memory capacity rather than its potential for the development of new, flexible assessment strategies. A review of current examples of computer usage in personality assessment reveals wide acceptance of automated clerical tasks such as test scoring and even test administration. The computer is also assuming tasks previously reserved for expert clinicians, such as writing narrative interpretive reports from test results. All of these functions represent automation of established assessment devices and interpretive strategies. The possibility also exists of harnessing some of the computer's unique adaptive capabilities to alter standard devices and even develop new ones. Three proposed strategies for developing computerized adaptive personality tests are described, with the conclusion that the computer's potential in this area justifies a call for further research efforts., (C) 1985 by the American Psychological Association1 aButcher, J N1 aKeller, L S1 aBacon, S F uhttp://www.iacat.org/content/current-developments-and-future-directions-computerized-personality-assessment00509nas a2200097 4500008004100000245011700041210006900158260004800227100001400275856012200289 1985 eng d00aDevelopment of a microcomputer-based adaptive testing system: Phase II Implementation (Research Report ONR 85-5)0 aDevelopment of a microcomputerbased adaptive testing system Phas aSt. Paul MN: Assessment Systems Corporation1 aVale, C D uhttp://www.iacat.org/content/development-microcomputer-based-adaptive-testing-system-phase-ii-implementation-research00489nas a2200109 4500008004100000245008600041210006900127260005100196300000800247100001700255856010700272 1985 eng d00aEquivalence of scores from computerized adaptive and paper-and-pencil ASVAB tests0 aEquivalence of scores from computerized adaptive and paperandpen aAlexandria, VA. USAbCenter for Naval Analysis a1001 aStoloff, P H uhttp://www.iacat.org/content/equivalence-scores-computerized-adaptive-and-paper-and-pencil-asvab-tests00502nas a2200097 4500008004100000245007900041210006900120260009700189100001400286856010400300 1985 eng d00aFinal report: Computerized adaptive measurement of achievement and ability0 aFinal report Computerized adaptive measurement of achievement an aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://www.iacat.org/content/final-report-computerized-adaptive-measurement-achievement-and-ability00521nas a2200121 4500008004100000245011900041210006900160300001200229490000700241100001500248700001600263856012000279 1985 eng d00aImplications for altering the context in which test items appear: A historical perspective on an immediate concern0 aImplications for altering the context in which test items appear a387-4130 v551 aLeary, L F1 aDorans, N J uhttp://www.iacat.org/content/implications-altering-context-which-test-items-appear-historical-perspective-immediate00380nas a2200097 4500008004100000245001700041210001700058260014700075100001400222856004600236 1985 eng d00aIntroduction0 aIntroduction aIn D. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 1-8). New York: Academic Press.1 aWeiss, DJ uhttp://www.iacat.org/content/introduction00405nas a2200121 4500008003900000245005800039210005800097300001000155490000700165100001500172700001300187856008300200 1985 d00aLatent structure and item sampling models for testing0 aLatent structure and item sampling models for testing a19-480 v361 aTraub, R E1 aLam, Y R uhttp://www.iacat.org/content/latent-structure-and-item-sampling-models-testing00387nas a2200097 4500008004100000245006200041210006200103260002900165100001000194856008500204 1985 eng d00aMethods of selecting successive items in adaptive testing0 aMethods of selecting successive items in adaptive testing aUniversity of Pittsburgh1 aYu, L uhttp://www.iacat.org/content/methods-selecting-successive-items-adaptive-testing00440nas a2200109 4500008004100000245008400041210006900125300000900194490000700203100001800210856010200228 1985 eng d00aMonitoring item calibrations from data yielded by an adaptive testing procedure0 aMonitoring item calibrations from data yielded by an adaptive te a9-120 v101 aGarrison, W M uhttp://www.iacat.org/content/monitoring-item-calibrations-data-yielded-adaptive-testing-procedure00491nam a2200097 4500008004100000245006900041210006900110260010900179100001400288856009100302 1985 eng d00aProceedings of the 1982 Computerized Adaptive Testing Conference0 aProceedings of the 1982 Computerized Adaptive Testing Conference aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://www.iacat.org/content/proceedings-1982-computerized-adaptive-testing-conference00484nas a2200109 4500008004100000245005900041210005900100260010100159100001600260700001700276856008100293 1985 eng d00aReducing the predictability of adaptive item sequences0 aReducing the predictability of adaptive item sequences aProceedings of the 27th Annual Conference of the Military Testing Association, San Diego, 43-48.1 aWetzel, C D1 aMcBride, J R uhttp://www.iacat.org/content/reducing-predictability-adaptive-item-sequences00380nam a2200097 4500008004100000245005600041210005500097260003000152100001600182856008400198 1985 eng d00aSequential analysis: Tests and confidence intervals0 aSequential analysis Tests and confidence intervals aNew York: Springer-Verlag1 aSiegmund, D uhttp://www.iacat.org/content/sequential-analysis-tests-and-confidence-intervals01654nas a2200121 4500008004100000245007900041210006900120300001200189490000700201520121400208100001401422856009601436 1985 eng d00aA structural comparison of conventional and adaptive versions of the ASVAB0 astructural comparison of conventional and adaptive versions of t a305-3220 v203 aExamined several structural models of similarity between the Armed Services Vocational Aptitude Battery (ASVAB) and a battery of computerized adaptive tests designed to measure the same aptitudes. 12 plausible models were fitted to sample data in a double cross-validation design. 1,411 US Navy recruits completed 10 ASVAB subtests. A computerized adaptive test version of the ASVAB subtests was developed on item pools of approximately 200 items each. The items were pretested using applicants from military entrance processing stations across the US, resulting in a total calibration sample size of approximately 60,000 for the computerized adaptive tests. Three of the 12 models provided reasonable summaries of the data. One model with a multiplicative structure (M. W. Browne; see record 1984-24964-001) performed quite well. This model provides an estimate of the disattenuated method correlation between conventional testing and adaptive testing. In the present data, this correlation was estimated to be 0.97 and 0.98 in the 2 halves of the data. Results support computerized adaptive tests as replacements for conventional tests. (33 ref) (PsycINFO Database Record (c) 2004 APA, all rights reserved).1 aCudeck, R uhttp://www.iacat.org/content/structural-comparison-conventional-and-adaptive-versions-asvab00535nas a2200109 4500008004100000245007200041210006900113260011600182300001200298100001800310856009700328 1985 eng d00aUnidimensional and multidimensional models for item response theory0 aUnidimensional and multidimensional models for item response the aMinneapolis, MN. USAbUniversity of Minnesota, Department of Psychology, Psychometrics Methods Programc06/1982 a127-1481 aMcDonald, R P uhttp://www.iacat.org/content/unidimensional-and-multidimensional-models-item-response-theory00383nas a2200097 4500008004100000245006400041210006300105100001700168700001600185856008400201 1985 eng d00aValidity of adaptive testing: A summary of research results0 aValidity of adaptive testing A summary of research results1 aSympson, J B1 aMoreno, K E uhttp://www.iacat.org/content/validity-adaptive-testing-summary-research-results00510nas a2200109 4500008004100000245011600041210006900157100001600226700001600242700002100258856012100279 1985 eng d00aA validity study of the computerized adaptive testing version of the Armed Services Vocational Aptitude Battery0 avalidity study of the computerized adaptive testing version of t1 aMoreno, K E1 aSegall, D O1 aKieckhaefer, W F uhttp://www.iacat.org/content/validity-study-computerized-adaptive-testing-version-armed-services-vocational-aptitude00642nam a2200097 4500008004100000245022200041210006900263260007500332100001900407856011800426 1984 eng d00aAdaptive self-referenced testing as a procedure for the measurement of individual change in instruction: A comparison of the reliabilities of change estimates obtained from conventional and adaptive testing procedures0 aAdaptive selfreferenced testing as a procedure for the measureme aUnpublished doctoral dissertation, Univerity of Minnesota, Minneapolis1 aKingsbury, G G uhttp://www.iacat.org/content/adaptive-self-referenced-testing-procedure-measurement-individual-change-instruction00422nas a2200097 4500008004100000245005500041210005100096260007800147100001700225856008200242 1984 eng d00aAdaptive testing (Final Report Contract OPM-29-80)0 aAdaptive testing Final Report Contract OPM2980 aUrbana-Champaign IL: University of Illinois, Aviation Research Laboratory1 aTrollip, S R uhttp://www.iacat.org/content/adaptive-testing-final-report-contract-opm-29-8000406nas a2200109 4500008003900000245004400039210004400083260006900127100001600196700001400212856007000226 1984 d00aAnalysis of experimental CAT ASVAB data0 aAnalysis of experimental CAT ASVAB data aBaltimore MD: Johns Hopkins University, Department of Psychology1 aAllred, L A1 aGreen, BF uhttp://www.iacat.org/content/analysis-experimental-cat-asvab-data00455nas a2200109 4500008004100000245006300041210006300104260006900167100001100236700001400247856008400261 1984 eng d00aAnalysis of speeded test data from experimental CAT system0 aAnalysis of speeded test data from experimental CAT system aBaltimore MD: Johns Hopkins University, Department of Psychology1 aGreaud1 aGreen, BF uhttp://www.iacat.org/content/analysis-speeded-test-data-experimental-cat-system00549nas a2200121 4500008004100000245008200041210006900123260008300192100001800275700001800293700001500311856010100326 1984 eng d00aApplication of adaptive testing to a fraction test (Research Report 84-3-NIE)0 aApplication of adaptive testing to a fraction test Research Repo aUrbana IL: Univerity of Illinois, Computer-Based Education Research Laboratory1 aTatsuoka, K K1 aTatsuoka, M M1 aBaillie, R uhttp://www.iacat.org/content/application-adaptive-testing-fraction-test-research-report-84-3-nie00400nas a2200121 4500008004100000245005400041210005400095300001200149490000600161100001400167700001700181856008000198 1984 eng d00aBias and information of Bayesian adaptive testing0 aBias and information of Bayesian adaptive testing a273-2850 v81 aWeiss, DJ1 aMcBride, J R uhttp://www.iacat.org/content/bias-and-information-bayesian-adaptive-testing00406nas a2200121 4500008004500000245005400045210005400099300001200153490000600165100001400171700001700185856008200202 1984 Engldsh 00aBias and Information of Bayesian Adaptive Testing0 aBias and Information of Bayesian Adaptive Testing a273-2850 v81 aWeiss, DJ1 aMcBride, J R uhttp://www.iacat.org/content/bias-and-information-bayesian-adaptive-testing-000486nam a2200097 4500008004100000245009300041210006900134260006300203100001400266856010800280 1984 eng d00aA comparison of the maximum likelihood strategy and stradaptive test on a micro-computer0 acomparison of the maximum likelihood strategy and stradaptive te aUnpublished M.S. thesis, University of Wisconsin, Madison.1 aBill, B C uhttp://www.iacat.org/content/comparison-maximum-likelihood-strategy-and-stradaptive-test-micro-computer00397nas a2200109 4500008004100000245006500041210006500106300000600171490000600177100001700183856008700200 1984 eng d00aComputerized adaptive testing in the Maryland Public Schools0 aComputerized adaptive testing in the Maryland Public Schools a10 v11 aStevenson, J uhttp://www.iacat.org/content/computerized-adaptive-testing-maryland-public-schools00352nas a2200121 4500008003900000245003600039210003600075300001200111490000700123100001800130700001700148856006500165 1984 d00aComputerized diagnostic testing0 aComputerized diagnostic testing a391-3970 v211 aMCArthur, D L1 aChoppin, B H uhttp://www.iacat.org/content/computerized-diagnostic-testing00427nas a2200097 4500008004100000245008500041210006900126260002000195100001700215856009700232 1984 eng d00aThe design of a computerized adaptive testing system for administering the ASVAB0 adesign of a computerized adaptive testing system for administeri aNew Orleans, LA1 aMcBride, J R uhttp://www.iacat.org/content/design-computerized-adaptive-testing-system-administering-asvab00396nas a2200097 4500008004100000245005900041210005800100260004100158100001400199856008500213 1984 eng d00aEfficiency and precision in two-stage adaptive testing0 aEfficiency and precision in twostage adaptive testing aWest Palm Beach Florida: Eastern ERA1 aLoyd, B H uhttp://www.iacat.org/content/efficiency-and-precision-two-stage-adaptive-testing00529nas a2200133 4500008004100000245006100041210006100102260009000163100001700253700001400270700001700284700001400301856008000315 1984 eng d00aEvaluation of computerized adaptive testing of the ASVAB0 aEvaluation of computerized adaptive testing of the ASVAB aSan Diego, CA: Navy Personnel Research and Development Center, unpublished manuscript1 aHardwicke, S1 aVicino, F1 aMcBride, J R1 aNemeth, C uhttp://www.iacat.org/content/evaluation-computerized-adaptive-testing-asvab00446nas a2200109 4500008004100000245007800041210006900119260001900188100001600207700001900223856009400242 1984 eng d00aAn evaluation of the utility of large scale computerized adaptive testing0 aevaluation of the utility of large scale computerized adaptive t aNew Orleans LA1 aVicino, F L1 aHardwicke, S B uhttp://www.iacat.org/content/evaluation-utility-large-scale-computerized-adaptive-testing00441nas a2200109 4500008004100000245007800041210006900119260001200188100001600200700001900216856009600235 1984 eng d00aAn evaluation of the utility of large scale computerized adaptive testing0 aevaluation of the utility of large scale computerized adaptive t aChicago1 aVicino, F L1 aHardwicke, S B uhttp://www.iacat.org/content/evaluation-utility-large-scale-computerized-adaptive-testing-000542nas a2200133 4500008004100000245010100041210006900142100001400211700001400225700001900239700001300258700001700271856012000288 1984 eng d00aEvaluation plan for the computerized adaptive vocational aptitude battery (Research Report 82-1)0 aEvaluation plan for the computerized adaptive vocational aptitud1 aGreen, BF1 aBock, R D1 aHumphreys, L G1 aLinn, RL1 aReckase, M D uhttp://www.iacat.org/content/evaluation-plan-computerized-adaptive-vocational-aptitude-battery-research-report-82-100318nas a2200121 4500008004100000245002700041210002700068300001200095490000600107100001500113700001500128856005300143 1984 eng d00aIssues in item banking0 aIssues in item banking a315-3300 v11 aMillman, J1 aArter, J A uhttp://www.iacat.org/content/issues-item-banking00487nas a2200121 4500008004500000245008700045210006900132300001200201490000600213100001800219700001600237856011200253 1984 Engldsh 00aItem Location Effects and Their Implications for IRT Equating and Adaptive Testing0 aItem Location Effects and Their Implications for IRT Equating an a147-1540 v81 aKingston, N M1 aDorans, N J uhttp://www.iacat.org/content/item-location-effects-and-their-implications-irt-equating-and-adaptive-testing00540nas a2200133 4500008004100000245007700041210006900118260006500187100001200252700001400264700001500278700001500293856009800308 1984 eng d00aMicrocomputer network for computerized adaptive testing (CAT) (TR-84-33)0 aMicrocomputer network for computerized adaptive testing CAT TR84 aSan Diego CA: Navy Personnel Research and Development Center1 aQuan, B1 aPark, T A1 aSandahl, G1 aWolfe, J H uhttp://www.iacat.org/content/microcomputer-network-computerized-adaptive-testing-cat-tr-84-3300556nas a2200157 4500008004100000245009200041210006900133300001200202490000700214100001400221700000900235700001300244700001300257700001700270856011100287 1984 eng d00aA plan for scaling the computerized adaptive Armed Services Vocational Aptitude Battery0 aplan for scaling the computerized adaptive Armed Services Vocati a347-3600 v211 aGreen, BF1 aBock1 aLinn, RL1 aLord, FM1 aReckase, M D uhttp://www.iacat.org/content/plan-scaling-computerized-adaptive-armed-services-vocational-aptitude-battery00500nas a2200121 4500008004100000245009200041210006900133260001900202100001700221700001400238700001300252856011300265 1984 eng d00aPredictive validity of computerized adaptive testing in a military training environment0 aPredictive validity of computerized adaptive testing in a milita aNew Orleans LA1 aSympson, J B1 aWeiss, DJ1 aRee, M J uhttp://www.iacat.org/content/predictive-validity-computerized-adaptive-testing-military-training-environment00603nas a2200145 4500008004500000245013900045210006900184300001200253490000600265100001600271700001600287700001700303700001400320856012300334 1984 Engldsh 00aRelationship Between Corresponding Armed Services Vocational Aptitude Battery (ASVAB) and Computerized Adaptive Testing (CAT) Subtests0 aRelationship Between Corresponding Armed Services Vocational Apt a155-1630 v81 aMoreno, K E1 aWetzel, C D1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/relationship-between-corresponding-armed-services-vocational-aptitude-battery-asvab-and-101570nas a2200169 4500008004100000245013900041210006900180300001200249490000600261520091500267653003401182100001601216700001601232700001701248700001401265856012101279 1984 eng d00aRelationship between corresponding Armed Services Vocational Aptitude Battery (ASVAB) and computerized adaptive testing (CAT) subtests0 aRelationship between corresponding Armed Services Vocational Apt a155-1630 v83 aInvestigated the relationships between selected subtests from the Armed Services Vocational Aptitude Battery (ASVAB) and corresponding subtests administered as computerized adaptive tests (CATs), using 270 17-26 yr old Marine recruits as Ss. Ss were administered the ASVAB before enlisting and approximately 2 wks after entering active duty, and the CAT tests were administered to Ss approximately 24 hrs after arriving at the recruit depot. Results indicate that 3 adaptive subtests correlated as well with ASVAB as did the 2nd administration of the ASVAB, although CAT subtests contained only half the number of items. Factor analysis showed CAT subtests to load on the same factors as the corresponding ASVAB subtests, indicating that the same abilities were being measured. It is concluded that CAT can achieve the same measurement precision as a conventional test, with half the number of items. (16 ref) 10acomputerized adaptive testing1 aMoreno, K E1 aWetzel, C D1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/relationship-between-corresponding-armed-services-vocational-aptitude-battery-asvab-and00436nas a2200109 4500008004100000245007700041210006900118260001900187100001500206700001700221856008800238 1984 eng d00aThe selection of items for decision making with a computer adaptive test0 aselection of items for decision making with a computer adaptive  aNew Orleans LA1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/selection-items-decision-making-computer-adaptive-test00655nas a2200205 4500008004100000020001400041245006700055210006700122300001200189490000700201653003400208653001700242653002100259100001400280700001400294700001900308700001300327700001700340856009200357 1984 eng d a1745-398400aTechnical guidelines for assessing computerized adaptive tests0 aTechnical guidelines for assessing computerized adaptive tests a347-3600 v2110acomputerized adaptive testing10aMode effects10apaper-and-pencil1 aGreen, BF1 aBock, R D1 aHumphreys, L G1 aLinn, RL1 aReckase, M D uhttp://www.iacat.org/content/technical-guidelines-assessing-computerized-adaptive-tests00460nas a2200097 4500008004100000245008200041210006900123260004600192100001800238856010600256 1984 eng d00aTwo simulated feasibility studies in computerized adaptive testing (RR-84-15)0 aTwo simulated feasibility studies in computerized adaptive testi aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/two-simulated-feasibility-studies-computerized-adaptive-testing-rr-84-1500366nam a2200097 4500008004100000245004900041210004900090260002400139100003500163856007000198 1984 eng d00aUsers manual for the MicroCAT Testing System0 aUsers manual for the MicroCAT Testing System aSt. Paul MN: Author1 aAssessment-Systems-Corporation uhttp://www.iacat.org/content/users-manual-microcat-testing-system00345nas a2200109 4500008004100000245004500041210004500086300001000131490000900141100001400150856007100164 1984 eng d00aUsing microcomputers to administer tests0 aUsing microcomputers to administer tests a16-200 v3(2)1 aWard, W C uhttp://www.iacat.org/content/using-microcomputers-administer-tests00419nas a2200109 4500008004100000245007300041210006900114300001000183490000900193100001500202856009200217 1984 eng d00aUsing microcomputers to administer tests: An alternate point of view0 aUsing microcomputers to administer tests An alternate point of v a20-210 v3(2)1 aMillman, J uhttp://www.iacat.org/content/using-microcomputers-administer-tests-alternate-point-view00445nas a2200097 4500008004100000245003300041210003300074260016500107100001400272856006100286 1983 eng d00aAdaptive testing by computer0 aAdaptive testing by computer aR. 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Army recruiting.0 aapplication of computerized adaptive testing in U S Army recruit a87-890 v101 aSands, W A1 aGade, P A uhttp://www.iacat.org/content/application-computerized-adaptive-testing-u-s-army-recruiting00538nas a2200109 4500008004100000245007700041210006900118260010900187100001400296700001700310856010100327 1983 eng d00aBias and information of Bayesian adaptive testing (Research Report 83-2)0 aBias and information of Bayesian adaptive testing Research Repor aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ1 aMcBride, J R uhttp://www.iacat.org/content/bias-and-information-bayesian-adaptive-testing-research-report-83-200613nas a2200109 4500008004100000245009800041210006900139260013900208100002000347700001400367856012200381 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure0 acomparison of IRTbased adaptive mastery testing and a sequential aD. J. Weiss (Ed.), New horizons in testing: Latent trait theory and computerized adaptive testing (pp. 1-8). New York: Academic Press.1 aKingsbury, G.G.1 aWeiss, DJ uhttp://www.iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure-100535nas a2200121 4500008004100000245009900041210006900140260003900209300001200248100001900260700001400279856012000293 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure.0 acomparison of IRTbased adaptive mastery testing and a sequential aNew York, NY. USAbAcademic Press. a258-2831 aKingsbury, G G1 aWeiss, DJ uhttp://www.iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure00621nas a2200109 4500008004100000245009800041210006900139260014800208100001900356700001400375856012200389 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure0 acomparison of IRTbased adaptive mastery testing and a sequential aD. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 257-283). 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J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 83-108). New York: Academic Press.1 aTrabin, T E1 aWeiss, DJ uhttp://www.iacat.org/content/person-response-curve-fit-individuals-item-response-theory-models00479nas a2200109 4500008004100000245008400041210006900125260004100194100001700235700001500252856010200267 1983 eng d00aPredictive utility evaluation of adaptive testing: Results of the Navy research0 aPredictive utility evaluation of adaptive testing Results of the aFalls Church VA: The Rehab Group Inc1 aHardwicke, S1 aWhite, K E uhttp://www.iacat.org/content/predictive-utility-evaluation-adaptive-testing-results-navy-research00573nas a2200157 4500008004100000245006000041210005700101260003800158300001200196653000900208653004900217653004100266653000900307100001700316856008200333 1983 eng d00aA procedure for decision making using tailored testing.0 aprocedure for decision making using tailored testing aNew York, NY. USAbAcademic Press a237-25410aCCAT10aCLASSIFICATION Computerized Adaptive Testing10asequential probability ratio testing10aSPRT1 aReckase, M D uhttp://www.iacat.org/content/procedure-decision-making-using-tailored-testing00393nas a2200097 4500008004100000245003400041210003000075260012000105100001400225856005600239 1983 eng d00aThe promise of tailored tests0 apromise of tailored tests aH. Wainer and S. Messick (Eds.). Principals of modern psychological measurement (pp. 69-80). Hillsdale NJ: Erlbaum.1 aGreen, BF uhttp://www.iacat.org/content/promise-tailored-tests00645nas a2200133 4500008004100000245015000041210006900191260006500260100001600325700001600341700001700357700001400374856012300388 1983 eng d00aRelationship between corresponding Armed Services Vocational Aptitude Battery (ASVAB) and computerized adaptive testing (CAT) subtests (TR 83-27)0 aRelationship between corresponding Armed Services Vocational Apt aSan Diego CA: Navy Personnel Research and Development Center1 aMoreno, K E1 aWetzel, D C1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/relationship-between-corresponding-armed-services-vocational-aptitude-battery-asvab-and-000576nas a2200109 4500008004100000245007700041210006900118260014800187100001700335700001600352856009800368 1983 eng d00aReliability and validity of adaptive ability tests in a military setting0 aReliability and validity of adaptive ability tests in a military aD. J. 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New York: Academic Press.1 aMcBride, J R1 aMartin, J T uhttp://www.iacat.org/content/reliability-and-validity-adaptive-ability-tests-military-setting00620nas a2200121 4500008004100000245011100041210006900152260010500221100001700326700001600343700001400359856012500373 1983 eng d00aReliability and validity of adaptive ability tests in a military recruit population (Research Report 83-1)0 aReliability and validity of adaptive ability tests in a military aMinneapolis: Department of Psychology, Psychometric Methods Program, Computerized Testing Laboratory1 aMcBride, J R1 aMartin, J T1 aWeiss, DJ uhttp://www.iacat.org/content/reliability-and-validity-adaptive-ability-tests-military-recruit-population-research-report00668nas a2200121 4500008004100000245012300041210006900164260014000233100001600373700001700389700001400406856012600420 1983 eng d00aReliability and validity of adaptive vs. conventional tests in a military recruit population (Research Rep. No. 83-1).0 aReliability and validity of adaptive vs conventional tests in a  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aMartin, J T1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/reliability-and-validity-adaptive-vs-conventional-tests-military-recruit-population-research00369nas a2200121 4500008004100000245003400041210003400075260003800109300001000147100001300157700001400170856006300184 1983 eng d00aSmall N justifies Rasch model0 aSmall N justifies Rasch model aNew York, NY. USAbAcademic Press a51-611 aLord, FM1 aBock, R D uhttp://www.iacat.org/content/small-n-justifies-rasch-model00442nam a2200109 4500008004100000245006600041210006200107260004200169100001800211700001500229856008800244 1983 eng d00aThe stochastic modeling of elementary psychological processes0 astochastic modeling of elementary psychological processes aCambridge: Cambridge University Press1 aTownsend, J T1 aAshby, G F uhttp://www.iacat.org/content/stochastic-modeling-elementary-psychological-processes00510nas a2200097 4500008004100000245007700041210006900118260010900187100001400296856010200310 1983 eng d00aThe stratified adaptive computerized ability test (Research Report 73-3)0 astratified adaptive computerized ability test Research Report 73 aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://www.iacat.org/content/stratified-adaptive-computerized-ability-test-research-report-73-3-000587nas a2200109 4500008004100000245015200041210006900193260006500262100001400327700001600341856012000357 1983 eng d00aTailored testing, its theory and practice. 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Washington, DC: Office of the Assistant Secretary of Defense (Manpower, Reserve Affairs and Logistics), Accession Policy Directorate.1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-system-development-and-project-management00593nas a2200109 4500008004100000245006500041210006100106260019200167100001700359700001700376856009000393 1982 eng d00aThe computerized adaptive testing system development project0 acomputerized adaptive testing system development project aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference (pp. 342-349). 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J. Weiss (Ed.), Proceedings of the 1979 Item Response Theory and Computerized Adaptive Testing Conference (pp. 360-371). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laborat1 aVale, C D uhttp://www.iacat.org/content/design-microcomputer-based-adaptive-testing-system00446nas a2200097 4500008004100000245009100041210006900132260001900201100001700220856011100237 1982 eng d00aDevelopment of a computerized adaptive testing system for enlisted personnel selection0 aDevelopment of a computerized adaptive testing system for enlist aWashington, DC1 aMcBride, J R uhttp://www.iacat.org/content/development-computerized-adaptive-testing-system-enlisted-personnel-selection00527nas a2200097 4500008004100000245004800041210004700089260020000136100001700336856007600353 1982 eng d00aDiscussion: Adaptive and sequential testing0 aDiscussion Adaptive and sequential testing aD. J. Weiss (Ed.). Proceedings of the 1982 Computerized Adaptive Testing Conference (pp. 290-294). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aReckase, M D uhttp://www.iacat.org/content/discussion-adaptive-and-sequential-testing00422nas a2200109 4500008004500000245007100045210006900116300001200185490000600197100001400203856009500217 1982 Engldsh 00aImproving Measurement Quality and Efficiency with Adaptive Testing0 aImproving Measurement Quality and Efficiency with Adaptive Testi a473-4920 v61 aWeiss, DJ uhttp://www.iacat.org/content/improving-measurement-quality-and-efficiency-adaptive-testing00679nas a2200109 4500008004100000245010300041210006900144260020000213100001700413700001300430856012600443 1982 eng d00aItem Calibrations for Computerized Adaptive Testing (CAT) Experimental Item Pools Adaptive Testing0 aItem Calibrations for Computerized Adaptive Testing CAT Experime aD. J. Weiss (Ed.). 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J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program. {PDF file, 1.1 aWeiss, DJ1 aSuhadolnik, D uhttp://www.iacat.org/content/robustness-adaptive-testing-multidimensionality00323nas a2200109 4500008004100000245003700041210003700078300001200115490000600127100001800133856006200151 1982 eng d00aSequential testing for selection0 aSequential testing for selection a337-3510 v61 aWeitzman, R A uhttp://www.iacat.org/content/sequential-testing-selection00329nas a2200109 4500008004500000245003700045210003700082300001200119490000600131100001800137856006400155 1982 Engldsh 00aSequential Testing for Selection0 aSequential Testing for Selection a337-3510 v61 aWeitzman, R A uhttp://www.iacat.org/content/sequential-testing-selection-000622nas a2200097 4500008004100000245008500041210006900126260020700195100001800402856010400420 1982 eng d00aUse of Sequential Testing to Prescreen Prospective Entrants to Military Service.0 aUse of Sequential Testing to Prescreen Prospective Entrants to M aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWeitzman, R A uhttp://www.iacat.org/content/use-sequential-testing-prescreen-prospective-entrants-military-service00645nam a2200097 4500008004100000245014800041210006900189260015400258100001500412856012000427 1981 eng d00aAbility measurement, test bias reduction, and psychological reactions to testing as a function of computer adaptive testing versus conventional0 aAbility measurement test bias reduction and psychological reacti aUnpublished doctoral dissertation, Virginia Polytechnic Institute and State University. Dissertational Abstracts International, 1982, 42,(10-B), 42331 aOrban, J A uhttp://www.iacat.org/content/ability-measurement-test-bias-reduction-and-psychological-reactions-testing-function-000468nas a2200121 4500008004100000245004000041210004000081260011500121100001600236700001400252700001300266856006700279 1981 eng d00aAdaptive testing without a computer0 aAdaptive testing without a computer aCatalog of Selected Documents in Psychology, Nov 1981, 11, 74-75 (Ms. No. 2350). AFHRL Technical Report 80-66.1 aFriedman, D1 aSteinberg1 aRee, M J uhttp://www.iacat.org/content/adaptive-testing-without-computer00552nas a2200109 4500008004100000245008300041210006900124260011600193100001300309700001700322856010300339 1981 eng d00aA comparison of a Bayesian and a maximum likelihood tailored testing procedure0 acomparison of a Bayesian and a maximum likelihood tailored testi aColumbia MObUniversity of Missouri, Department of Educational Psychology, Tailored Testing Research Laboratory1 aMcKinley1 aReckase, M D uhttp://www.iacat.org/content/comparison-bayesian-and-maximum-likelihood-tailored-testing-procedure00483nas a2200109 4500008004100000245009800041210006900139260001900208100001500227700001700242856011400259 1981 eng d00aA comparison of a maximum likelihood and a Bayesian estimation procedure for tailored testing0 acomparison of a maximum likelihood and a Bayesian estimation pro aLos Angeles CA1 aRosso, M A1 aReckase, M D uhttp://www.iacat.org/content/comparison-maximum-likelihood-and-bayesian-estimation-procedure-tailored-testing00487nas a2200121 4500008004100000245006900041210006600110260005000176100002000226700001500246700001500261856008900276 1981 eng d00aA comparison of two methods of interactive testing Final report.0 acomparison of two methods of interactive testing Final report aNational Institute of Education Grant 79-10451 aNicewander, W A1 aChang, H S1 aDoody, E N uhttp://www.iacat.org/content/comparison-two-methods-interactive-testing-final-report00435nas a2200109 4500008004100000245007900041210006900120300001200189490000700201100001400208856010300222 1981 eng d00aDesign and implementation of a microcomputer-based adaptive testing system0 aDesign and implementation of a microcomputerbased adaptive testi a399-4060 v131 aVale, C D uhttp://www.iacat.org/content/design-and-implementation-microcomputer-based-adaptive-testing-system00515nam a2200097 4500008004100000245011700041210006900158260005100227100001800278856012100296 1981 eng d00aEffect of error in item parameter estimates on adaptive testing (Doctoral dissertation, University of Minnesota)0 aEffect of error in item parameter estimates on adaptive testing  aDissertation Abstracts International, 42, 06-B1 aCrichton, L I uhttp://www.iacat.org/content/effect-error-item-parameter-estimates-adaptive-testing-doctoral-dissertation-university00446nas a2200109 4500008004500000245008700045210006900132300001000201490000600211100001300217856010600230 1981 Engldsh 00aThe Effects of Item Calibration Sample Size and Item Pool Size on Adaptive Testing0 aEffects of Item Calibration Sample Size and Item Pool Size on Ad a11-190 v51 aRee, M J uhttp://www.iacat.org/content/effects-item-calibration-sample-size-and-item-pool-size-adaptive-testing00647nas a2200109 4500008004100000245013300041210006900174260013900243100001800382700001400400856012300414 1981 eng d00aFactors influencing the psychometric characteristics of an adaptive testing strategy for test batteries (Research Rep. No. 81-4)0 aFactors influencing the psychometric characteristics of an adapt aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aMaurelli, V A1 aWeiss, DJ uhttp://www.iacat.org/content/factors-influencing-psychometric-characteristics-adaptive-testing-strategy-test-batteries00445nas a2200097 4500008004100000245005600041210005500097260009700152100001400249856008400263 1981 eng d00aFinal report: Computerized adaptive ability testing0 aFinal report Computerized adaptive ability testing aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://www.iacat.org/content/final-report-computerized-adaptive-ability-testing00463nas a2200097 4500008004100000245007100041210006900112260007200181100001700253856009500270 1981 eng d00aFinal report: Procedures for criterion referenced tailored testing0 aFinal report Procedures for criterion referenced tailored testin aColumbia: University of Missouri, Educational Psychology Department1 aReckase, M D uhttp://www.iacat.org/content/final-report-procedures-criterion-referenced-tailored-testing00417nas a2200109 4500008004100000245007100041210006900112300001200181490000700193100001500200856009200215 1981 eng d00aOptimal item difficulty for the three-parameter normal ogive model0 aOptimal item difficulty for the threeparameter normal ogive mode a461-4640 v461 aWolfe, J H uhttp://www.iacat.org/content/optimal-item-difficulty-three-parameter-normal-ogive-model00568nas a2200097 4500008004100000245016100041210006900202260006500271100001400336856012000350 1981 eng d00aTailored testing, its theory and practice. Part II: Ability and item parameter estimation, multiple ability application, and allied procedures (NPRDC TR-81)0 aTailored testing its theory and practice Part II Ability and ite aSan Diego CA: Navy Personnel Research and Development Center1 aUrry, V W uhttp://www.iacat.org/content/tailored-testing-its-theory-and-practice-part-ii-ability-and-item-parameter-estimation00569nas a2200097 4500008004100000245014500041210006900186260007800255100001700333856012100350 1981 eng d00aThe use of the sequential probability ratio test in making grade classifications in conjunction with tailored testing (Research Report 81-4)0 ause of the sequential probability ratio test in making grade cla aColumbia MO: University of Missouri, Department of Educational Psychology1 aReckase, M D uhttp://www.iacat.org/content/use-sequential-probability-ratio-test-making-grade-classifications-conjunction-tailored00601nas a2200109 4500008004100000245010900041210006900150260011400219100001900333700001400352856012500366 1981 eng d00aA validity comparison of adaptive and conventional strategies for mastery testing (Research Report 81-3)0 avalidity comparison of adaptive and conventional strategies for  aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://www.iacat.org/content/validity-comparison-adaptive-and-conventional-strategies-mastery-testing-research-report-8100593nas a2200097 4500008004100000245005800041210005800099260023900157100001700396856008200413 1980 eng d00aAdaptive verbal ability testing in a military setting0 aAdaptive verbal ability testing in a military setting aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 4-15). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-verbal-ability-testing-military-setting00630nas a2200109 4500008004100000245014500041210006900186260011400255100001900369700001400388856011800402 1980 eng d00aAn alternate-forms reliability and concurrent validity comparison of Bayesian adaptive and conventional ability tests (Research Report 80-5)0 aalternateforms reliability and concurrent validity comparison of aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://www.iacat.org/content/alternate-forms-reliability-and-concurrent-validity-comparison-bayesian-adaptive-and00538nas a2200109 4500008004100000245011800041210006900159260005000228490001000278100001400288856012600302 1980 eng d00aA comparative evaluation of two Bayesian adaptive ability estimation procedures with a conventional test strategy0 acomparative evaluation of two Bayesian adaptive ability estimati aWashington DCbCatholic University of America0 vPh.D.1 aGorman, S uhttp://www.iacat.org/content/comparative-evaluation-two-bayesian-adaptive-ability-estimation-procedures-conventional-test00488nam a2200097 4500008004100000245008400041210006900125260007400194100001400268856010800282 1980 eng d00aA comparative evaluation of two Bayesian adaptive ability estimation procedures0 acomparative evaluation of two Bayesian adaptive ability estimati aUnpublished doctoral dissertation, the Catholic University of America1 aGorman, S uhttp://www.iacat.org/content/comparative-evaluation-two-bayesian-adaptive-ability-estimation-procedures00608nas a2200109 4500008004100000245012300041210006900164260011400233100001900347700001400366856011800380 1980 eng d00aA comparison of adaptive, sequential, and conventional testing strategies for mastery decisions (Research Report 80-4)0 acomparison of adaptive sequential and conventional testing strat aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://www.iacat.org/content/comparison-adaptive-sequential-and-conventional-testing-strategies-mastery-decisions00706nas a2200109 4500008004100000245009600041210006900137260024100206100001900447700001400466856011600480 1980 eng d00aA comparison of ICC-based adaptive mastery testing and the Waldian probability ratio method0 acomparison of ICCbased adaptive mastery testing and the Waldian  aD. J. Weiss (Ed.). Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 120-139). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://www.iacat.org/content/comparison-icc-based-adaptive-mastery-testing-and-waldian-probability-ratio-method00653nas a2200097 4500008004100000245010500041210006900146260021000215100001400425856011600439 1980 eng d00aA comparison of the accuracy of Bayesian adaptive and static tests using a correction for regression0 acomparison of the accuracy of Bayesian adaptive and static tests aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 35-50). Minneapolis MN: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory.1 aGorman, S uhttp://www.iacat.org/content/comparison-accuracy-bayesian-adaptive-and-static-tests-using-correction-regression00436nas a2200109 4500008004100000245008200041210006900123300001200192490000700204100001400211856010100225 1980 eng d00aComputer applications in audiology and rehabilitation of the hearing impaired0 aComputer applications in audiology and rehabilitation of the hea a471-4810 v131 aLevitt, H uhttp://www.iacat.org/content/computer-applications-audiology-and-rehabilitation-hearing-impaired00373nas a2200121 4500008004100000245004500041210004500086300001200131490000700143100001300150700001700163856007100180 1980 eng d00aComputer applications to ability testing0 aComputer applications to ability testing a193-2030 v131 aMcKinley1 aReckase, M D uhttp://www.iacat.org/content/computer-applications-ability-testing00620nas a2200097 4500008004100000245011300041210006900154260015700223100001700380856012500397 1980 eng d00aComputerized instructional adaptive testing model: Formulation and validation (AFHRL-TR-79-33, Final Report)0 aComputerized instructional adaptive testing model Formulation an aBrooks Air Force Base TX: Air Force Human Resources Laboratory", Also Catalog of Selected Documents in Psychology, February 1981, 11, 20 (Ms. No, 2217) 1 aKalisch, S J uhttp://www.iacat.org/content/computerized-instructional-adaptive-testing-model-formulation-and-validation-afhrl-tr-79-3300632nas a2200097 4500008004100000245006600041210006400107260026000171100001700431856008600448 1980 eng d00aComputerized testing in the German Federal Armed Forces (FAF)0 aComputerized testing in the German Federal Armed Forces FAF aD. J. Weiss (Ed.), Proceedings of the 1979 Item Response Theory and Computerized Adaptive Testing Conference (pp. 68-77). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laborator1 aWildgrube, W uhttp://www.iacat.org/content/computerized-testing-german-federal-armed-forces-faf00585nas a2200109 4500008004100000245008500041210006900126260013900195100001800334700001400352856010900366 1980 eng d00aCriterion-related validity of adaptive testing strategies (Research Report 80-3)0 aCriterionrelated validity of adaptive testing strategies Researc aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aThompson, J G1 aWeiss, DJ uhttp://www.iacat.org/content/criterion-related-validity-adaptive-testing-strategies-research-report-80-300572nam a2200097 4500008004100000245011100041210006900152260012300221100001400344856011600358 1980 eng d00aDevelopment and evaluation of an adaptive testing strategy for use in multidimensional interest assessment0 aDevelopment and evaluation of an adaptive testing strategy for u aUnpublished doctoral dissertation, University of Minnesota. Dissertational Abstract International, 42(11-B), 4248-42491 aVale, C D uhttp://www.iacat.org/content/development-and-evaluation-adaptive-testing-strategy-use-multidimensional-interest00500nas a2200097 4500008004100000245002600041210002500067260024000092100001600332856005400348 1980 eng d00aDiscussion: Session 10 aDiscussion Session 1 aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 51-55). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aWaters, B K uhttp://www.iacat.org/content/discussion-session-100520nas a2200097 4500008004100000245002600041210002500067260026000092100001600352856005400368 1980 eng d00aDiscussion: Session 30 aDiscussion Session 3 aD. J. Weiss (Ed.), Proceedings of the 1979 Item Response Theory and Computerized Adaptive Testing Conference (pp. 140-143). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laborat1 aNovick, M R uhttp://www.iacat.org/content/discussion-session-300616nas a2200133 4500008004100000245009600041210006900137260009700206100001400303700001600317700001800333700001400351856011700365 1980 eng d00aEffects of computerized adaptive testing on Black and White students (Research Report 79-2)0 aEffects of computerized adaptive testing on Black and White stud aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aPine, S M1 aChurch, A T1 aGialluca, K A1 aWeiss, DJ uhttp://www.iacat.org/content/effects-computerized-adaptive-testing-black-and-white-students-research-report-79-200516nas a2200109 4500008004100000245012400041210006900165260001700234100001800251700001700269856012000286 1980 eng d00aEffects of program parameters and item pool characteristics on the bias of a three-parameter tailored testing procedure0 aEffects of program parameters and item pool characteristics on t aBoston MA, U1 aPatience, W M1 aReckase, M D uhttp://www.iacat.org/content/effects-program-parameters-and-item-pool-characteristics-bias-three-parameter-tailored00436nas a2200109 4500008004100000245006300041210006000104260004600164100002000210700001500230856008100245 1980 eng d00aAn empirical study of a broad range test of verbal ability0 aempirical study of a broad range test of verbal ability aPrinceton NJ: Educational Testing Service1 aKreitzberg, C B1 aJones, D J uhttp://www.iacat.org/content/empirical-study-broad-range-test-verbal-ability00417nas a2200097 4500008004100000245008300041210006900124260001100193100001700204856009800221 1980 eng d00aEstimating the reliability of adaptive tests from a single test administration0 aEstimating the reliability of adaptive tests from a single test  aBoston1 aSympson, J B uhttp://www.iacat.org/content/estimating-reliability-adaptive-tests-single-test-administration00477nas a2200097 4500008004100000245006300041210006200104260010800166100001400274856009100288 1980 eng d00aFinal report: Computerized adaptive performance evaluation0 aFinal report Computerized adaptive performance evaluation aMinneapolis: Univerity of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://www.iacat.org/content/final-report-computerized-adaptive-performance-evaluation00433nas a2200097 4500008004100000245007600041210006900117260002800186100002100214856010000235 1980 eng d00aFinal Report: Computerized adaptive testing, assessment of requirements0 aFinal Report Computerized adaptive testing assessment of require aFalls Church VA: Author1 aRehab-Group-Inc. uhttp://www.iacat.org/content/final-report-computerized-adaptive-testing-assessment-requirements00477nas a2200133 4500008004500000245007200045210006900117300001200186490000600198100001400204700001900218700001300237856009300250 1980 Engldsh 00aImplied Orders Tailored Testing: Simulation with the Stanford-Binet0 aImplied Orders Tailored Testing Simulation with the StanfordBine a157-1630 v41 aCudeck, R1 aMcCormick, D J1 aCliff, N uhttp://www.iacat.org/content/implied-orders-tailored-testing-simulation-stanford-binet-000471nas a2200133 4500008004100000245007200041210006900113300001200182490000600194100001400200700001700214700001500231856009100246 1980 eng d00aImplied orders tailored testing: Simulation with the Stanford-Binet0 aImplied orders tailored testing Simulation with the StanfordBine a157-1630 v41 aCudeck, R1 aMcCormick, D1 aCliff, N A uhttp://www.iacat.org/content/implied-orders-tailored-testing-simulation-stanford-binet00506nas a2200109 4500008004100000245005900041210005900100260013300159100001700292700001300309856007400322 1980 eng d00aIndividualized testing on the basis of the Rasch model0 aIndividualized testing on the basis of the Rasch model aIn J. Th. Van der Kamp, W. F. Langerak, and D. N. M. de Gruijter (Eds.). Psychometrics for educational debates. New York: Wiley.1 aFischer, G H1 aPendl, P uhttp://www.iacat.org/content/individualized-testing-basis-rasch-model00651nas a2200097 4500008004100000245008200041210006900123260024200192100001700434856010200451 1980 eng d00aA model for computerized adaptive testing related to instructional situations0 amodel for computerized adaptive testing related to instructional aD. J. Weiss (Ed.). Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 101-119). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aKalisch, S J uhttp://www.iacat.org/content/model-computerized-adaptive-testing-related-instructional-situations00483nas a2200121 4500008004100000245007800041210006900119300002500188490001600213100001300229700001700242856010200259 1980 eng d00aOperational characteristics of a one-parameter tailored testing procedure0 aOperational characteristics of a oneparameter tailored testing p a10, 66 (Ms No. 2104)0 vAugust 19801 aPatience1 aReckase, M D uhttp://www.iacat.org/content/operational-characteristics-one-parameter-tailored-testing-procedure00725nas a2200109 4500008004100000245011500041210006900156260023700225100001700462700001400479856012200493 1980 eng d00aParallel forms reliability and measurement accuracy comparison of adaptive and conventional testing strategies0 aParallel forms reliability and measurement accuracy comparison o aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 16-34). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aJohnson, M J1 aWeiss, DJ uhttp://www.iacat.org/content/parallel-forms-reliability-and-measurement-accuracy-comparison-adaptive-and-conventional00491nam a2200097 4500008004100000245006900041210006900110260010900179100001400288856009100302 1980 eng d00aProceedings of the 1979 Computerized Adaptive Testing Conference0 aProceedings of the 1979 Computerized Adaptive Testing Conference aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://www.iacat.org/content/proceedings-1979-computerized-adaptive-testing-conference00369nas a2200133 4500008003900000245003800039210003600077300001200113490000700125100001400132700001300146700001400159856006200173 1980 d00aA simple form of tailored testing0 asimple form of tailored testing a301-3030 v501 aNisbet, J1 aAdams, M1 aArthur, J uhttp://www.iacat.org/content/simple-form-tailored-testing00594nas a2200097 4500008004100000245005900041210005900100260024100159100001700400856007900417 1980 eng d00aSome decision procedures for use with tailored testing0 aSome decision procedures for use with tailored testing aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 79-100). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aReckase, M D uhttp://www.iacat.org/content/some-decision-procedures-use-tailored-testing00589nas a2200097 4500008004100000245005400041210005400095260025000149100001300399856007900412 1980 eng d00aSome how and which for practical tailored testing0 aSome how and which for practical tailored testing aL. J. T. van der Kamp, W. F. Langerak and D.N.M. de Gruijter (Eds): Psychometrics for educational debates (pp. 189-206). New York: John Wiley and Sons. Computer-Assisted Instruction, Testing, and Guidance (pp. 139-183). New York: Harper and Row.1 aLord, FM uhttp://www.iacat.org/content/some-how-and-which-practical-tailored-testing00591nas a2200109 4500008004100000245010700041210006900148260010300217100001800320700001700338856012600355 1980 eng d00aA successful application of latent trait theory to tailored achievement testing (Research Report 80-1)0 asuccessful application of latent trait theory to tailored achiev aUniversity of Missouri, Department of Educational Psychology, Tailored Testing Research Laboratory1 aMcKinley, R L1 aReckase, M D uhttp://www.iacat.org/content/successful-application-latent-trait-theory-tailored-achievement-testing-research-report-80-100595nas a2200109 4500008004100000245006600041210006400107260019800171100001600369700001600385856008400401 1980 eng d00aA validity study of an adaptive test of reading comprehension0 avalidity study of an adaptive test of reading comprehension aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 57-67). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aHornke, L F1 aSauter, M B uhttp://www.iacat.org/content/validity-study-adaptive-test-reading-comprehension00476nas a2200097 4500008004100000245007300041210006900114260008800183100001700271856009000288 1979 eng d00aAdaptive mental testing: The state of the art (Technical Report 423)0 aAdaptive mental testing The state of the art Technical Report 42 aAlexandria VA: U.S. Army Research Institute for the Behavioral and Social Sciences.1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-mental-testing-state-art-technical-report-423-000526nas a2200109 4500008004100000245007800041210006900119260009700188100001900285700001400304856009800318 1979 eng d00aAn adaptive testing strategy for mastery decisions (Research Report 79-5)0 aadaptive testing strategy for mastery decisions Research Report  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aKingsbury, G G1 aWeiss, DJ uhttp://www.iacat.org/content/adaptive-testing-strategy-mastery-decisions-research-report-79-500551nas a2200097 4500008004100000245006400041210006300105260018000168100001700348856008800365 1979 eng d00aAdaptive tests' usefulness for military personnel screening0 aAdaptive tests usefulness for military personnel screening aIn M. Wiskoff, Chair, Military Applications of Computerized Adaptive Testing. Symposium presented at the Annual Convention of the American Psychological Association, New York.1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-tests-usefulness-military-personnel-screening00502nas a2200097 4500008004100000245011200041210006900153260004600222100001400268856012200282 1979 eng d00aBayesian sequential design and analysis of dichotomous experiments with special reference to mental testing0 aBayesian sequential design and analysis of dichotomous experimen aPrinceton NJ: Educational Testing Service1 aOwen, R J uhttp://www.iacat.org/content/bayesian-sequential-design-and-analysis-dichotomous-experiments-special-reference-mental00506nas a2200121 4500008004100000245010500041210006900146300000900215490000700224100001600231700001500247856012200262 1979 eng d00aA comparison of a standard and a computerized adaptive paradigm in Bekesy fixed-frequency audiometry0 acomparison of a standard and a computerized adaptive paradigm in a1-220 v191 aHarris, J D1 aSmith, P F uhttp://www.iacat.org/content/comparison-standard-and-computerized-adaptive-paradigm-bekesy-fixed-frequency-audiometry00495nas a2200097 4500008004100000245008300041210006900124260008900193100001700282856009800299 1979 eng d00aComputerized adaptive testing: The state of the art (ARI Technical Report 423)0 aComputerized adaptive testing The state of the art ARI Technical aAlexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-state-art-ari-technical-report-42300449nas a2200097 4500008004100000245009200041210006900133260001900202100001700221856011300238 1979 eng d00aCriterion-related validity of conventional and adaptive tests in a military environment0 aCriterionrelated validity of conventional and adaptive tests in  aMinneapolis MN1 aSympson, J B uhttp://www.iacat.org/content/criterion-related-validity-conventional-and-adaptive-tests-military-environment00605nas a2200109 4500008004100000245014400041210006900185260008500254100001600339700001700355856012300372 1979 eng d00aThe danger of relying solely on diagnostic adaptive testing when prior and subsequent instructional methods are different (CERL Report E-5)0 adanger of relying solely on diagnostic adaptive testing when pri aUrbana IL: Univeristy of Illinois, Computer-Based Education Research Laboratory.1 aTatsuoka, K1 aBirenbaum, M uhttp://www.iacat.org/content/danger-relying-solely-diagnostic-adaptive-testing-when-prior-and-subsequent-instructional00597nas a2200109 4500008003900000245013000039210006900169260009700238100001800335700001400353856012000367 1979 d00aEfficiency of an adaptive inter-subtest branching strategy in the measurement of classroom achievement (Research Report 79-6)0 aEfficiency of an adaptive intersubtest branching strategy in the aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aGialluca, K A1 aWeiss, DJ uhttp://www.iacat.org/content/efficiency-adaptive-inter-subtest-branching-strategy-measurement-classroom-achievement00463nas a2200097 4500008004100000245005100041210004800092260013400140100001700274856007400291 1979 eng d00aAn evaluation of computerized adaptive testing0 aevaluation of computerized adaptive testing aIn Proceedings of the 21st Military Testing Association Conference. SanDiego, CA: Navy Personnel Research and Development Center.1 aMcBride, J R uhttp://www.iacat.org/content/evaluation-computerized-adaptive-testing00466nas a2200121 4500008004100000245008600041210006900127300001200196490000600208100001500214700001700229856009800246 1979 eng d00aEvaluation of implied orders as a basis for tailored testing with simulation data0 aEvaluation of implied orders as a basis for tailored testing wit a495-5140 v31 aCliff, N A1 aMcCormick, D uhttp://www.iacat.org/content/evaluation-implied-orders-basis-tailored-testing-simulation-data00498nas a2200133 4500008004500000245008600045210006900131300001200200490000600212100001300218700001400231700001900245856010000264 1979 Engldsh 00aEvaluation of Implied Orders as a Basis for Tailored Testing with Simulation Data0 aEvaluation of Implied Orders as a Basis for Tailored Testing wit a495-5140 v31 aCliff, N1 aCudeck, R1 aMcCormick, D J uhttp://www.iacat.org/content/evaluation-implied-orders-basis-tailored-testing-simulation-data-000368nas a2200109 4500008004100000245005200041210005200093300001200145490000700157100001600164856007800180 1979 eng d00aFour realizations of pyramidal adaptive testing0 aFour realizations of pyramidal adaptive testing a164-1690 v161 aHornke, L F uhttp://www.iacat.org/content/four-realizations-pyramidal-adaptive-testing00479nas a2200133 4500008004100000245007700041210006900118300001000187490000600197100001400203700001900217700001500236856009400251 1979 eng d00aMonte carlo evaluation of implied orders as a basis for tailored testing0 aMonte carlo evaluation of implied orders as a basis for tailored a65-740 v31 aCudeck, R1 aMcCormick, D J1 aCliff, N A uhttp://www.iacat.org/content/monte-carlo-evaluation-implied-orders-basis-tailored-testing00481nas a2200133 4500008004500000245007700045210006900122300001000191490000600201100001400207700001700221700001300238856009600251 1979 Engldsh 00aMonte Carlo Evaluation of Implied Orders As a Basis for Tailored Testing0 aMonte Carlo Evaluation of Implied Orders As a Basis for Tailored a65-740 v31 aCudeck, R1 aMcCormick, D1 aCliff, N uhttp://www.iacat.org/content/monte-carlo-evaluation-implied-orders-basis-tailored-testing-000533nas a2200109 4500008004100000245013600041210006900177260001800246100001800264700001700282856012400299 1979 eng d00aOperational characteristics of a Rasch model tailored testing procedure when program parameters and item pool attributes are varied0 aOperational characteristics of a Rasch model tailored testing pr aSan Francisco1 aPatience, W M1 aReckase, M D uhttp://www.iacat.org/content/operational-characteristics-rasch-model-tailored-testing-procedure-when-program-parameters00626nas a2200109 4500008004100000245009400041210006900135260016900204100001400373700001700387856011200404 1979 eng d00aProblems in application of latent-trait models to tailored testing (Research Report 79-1)0 aProblems in application of latenttrait models to tailored testin aColumbia MO: University of Missouri, Department of Psychology", (also presented at National Council on Measurement in Education, 1979: ERIC No. ED 177 196) note = "1 aKoch, W J1 aReckase, M D uhttp://www.iacat.org/content/problems-application-latent-trait-models-tailored-testing-research-report-79-100403nam a2200097 4500008004100000245005600041210005200097260006300149100001500212856007800227 1979 eng d00aThe Rasch model in computerized personality testing0 aRasch model in computerized personality testing aPh.D. dissertation, University of Missouri, Columbia, 19791 aKunce, C S uhttp://www.iacat.org/content/rasch-model-computerized-personality-testing00399nas a2200097 4500008004100000245007100041210006900112260001300181100001700194856009000211 1979 eng d00aStudent reaction to computerized adaptive testing in the classroom0 aStudent reaction to computerized adaptive testing in the classro aNew York1 aJohnson, M J uhttp://www.iacat.org/content/student-reaction-computerized-adaptive-testing-classroom00372nas a2200097 4500008004100000245005900041210005400100260002200154100001700176856008100193 1978 eng d00aAn adaptive test designed for paper-and-pencil testing0 aadaptive test designed for paperandpencil testing aSan Francisco, CA1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-test-designed-paper-and-pencil-testing00522nas a2200097 4500008004100000245007200041210006900113260013000182100001700312856009500329 1978 eng d00aApplications of latent trait theory to criterion-referenced testing0 aApplications of latent trait theory to criterionreferenced testi aD.J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis, MN: University of Minnesota.1 aMcBride, J R uhttp://www.iacat.org/content/applications-latent-trait-theory-criterion-referenced-testing00609nas a2200109 4500008004100000245007300041210006900114260018600183100001700369700001500386856009800401 1978 eng d00aApplications of sequential testing procedures to performance testing0 aApplications of sequential testing procedures to performance tes aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aEpstein, K I1 aKnerr, C S uhttp://www.iacat.org/content/applications-sequential-testing-procedures-performance-testing-000512nas a2200133 4500008004100000245009100041210006900132300001200201490000700213100001600220700001600236700001600252856011000268 1978 eng d00aCombining auditory and visual stimuli in the adaptive testing of speech discrimination0 aCombining auditory and visual stimuli in the adaptive testing of a115-1220 v431 aSteele, J A1 aBinnie, C A1 aCooper, W A uhttp://www.iacat.org/content/combining-auditory-and-visual-stimuli-adaptive-testing-speech-discrimination00510nam a2200097 4500008004100000245009200041210006900133260008100202100001800283856011100301 1978 eng d00aA comparison of Bayesian and maximum likelihood scoring in a simulated stradaptive test0 acomparison of Bayesian and maximum likelihood scoring in a simul aUnpublished Masters thesis, St. Mary’s University of Texas, San Antonio TX1 aMaurelli, V A uhttp://www.iacat.org/content/comparison-bayesian-and-maximum-likelihood-scoring-simulated-stradaptive-test00568nas a2200109 4500008004100000245010400041210006900145260009700214100001400311700001400325856011900339 1978 eng d00aA comparison of the fairness of adaptive and conventional testing strategies (Research Report 78-1)0 acomparison of the fairness of adaptive and conventional testing  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aPine, S M1 aWeiss, DJ uhttp://www.iacat.org/content/comparison-fairness-adaptive-and-conventional-testing-strategies-research-report-78-100485nas a2200133 4500008004100000245007400041210006900115300001200184490000700196100001700203700001400220700001500234856010200249 1978 eng d00aComputer-assisted tailored testing: Examinee reactions and evaluation0 aComputerassisted tailored testing Examinee reactions and evaluat a265-2730 v381 aSchmidt, F L1 aUrry, V W1 aGugel, J F uhttp://www.iacat.org/content/computer-assisted-tailored-testing-examinee-reactions-and-evaluation00453nas a2200133 4500008004100000245006100041210006000102300001200162490000600174100002000180700001300200700001500213856009100228 1978 eng d00aComputerized adaptive testing: Principles and directions0 aComputerized adaptive testing Principles and directions a319-3290 v21 aKreitzberg, C B1 aStocking1 aSwanson, L uhttp://www.iacat.org/content/computerized-adaptive-testing-principles-and-directions-000403nas a2200109 4500008004100000245006100041210006000102300001200162490001000174100002000184856008900204 1978 eng d00aComputerized adaptive testing: Principles and directions0 aComputerized adaptive testing Principles and directions a319-3290 v2 (4)1 aKreitzberg, C B uhttp://www.iacat.org/content/computerized-adaptive-testing-principles-and-directions00575nas a2200109 4500008003900000245008200039210006900121260014200190100001500332700001400347856010400361 1978 d00aA construct validation of adaptive achievement testing (Research Report 78-4)0 aconstruct validation of adaptive achievement testing Research Re aMinneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aBejar, I I1 aWeiss, DJ uhttp://www.iacat.org/content/construct-validation-adaptive-achievement-testing-research-report-78-400591nas a2200121 4500008004100000245010900041210006900150260008100219100001500300700001400315700001700329856012300346 1978 eng d00aEvaluations of implied orders as a basis for tailored testing using simulations (Technical Report No. 4)0 aEvaluations of implied orders as a basis for tailored testing us aLos Angeles CA: University of Southern California, Department of Psychology.1 aCliff, N A1 aCudeck, R1 aMcCormick, D uhttp://www.iacat.org/content/evaluations-implied-orders-basis-tailored-testing-using-simulations-technical-report-no-400432nas a2200097 4500008004100000245008500041210006900126260002100195100001700216856010100233 1978 eng d00aA generalization of sequential analysis to decision making with tailored testing0 ageneralization of sequential analysis to decision making with ta aOklahoma City OK1 aReckase, M D uhttp://www.iacat.org/content/generalization-sequential-analysis-decision-making-tailored-testing00528nas a2200121 4500008004100000245007600041210006900117260008100186100001500267700001400282700001700296856009300313 1978 eng d00aImplied orders as a basis for tailored testing (Technical Report No. 6)0 aImplied orders as a basis for tailored testing Technical Report  aLos Angeles CA: University of Southern California, Department of Psychology.1 aCliff, N A1 aCudeck, R1 aMcCormick, D uhttp://www.iacat.org/content/implied-orders-basis-tailored-testing-technical-report-no-600554nas a2200109 4500008004100000245011600041210006900157260006600226100001400292700001700306856012100323 1978 eng d00aA live tailored testing comparison study of the one- and three-parameter logistic models (Research Report 78-1)0 alive tailored testing comparison study of the one and threeparam aColumbia MO: University of Missouri, Department of Psychology1 aKoch, W J1 aReckase, M D uhttp://www.iacat.org/content/live-tailored-testing-comparison-study-one-and-three-parameter-logistic-models-research00466nas a2200109 4500008004100000245005200041210005000093260011600143300001000259100001700269856007000286 1978 eng d00aA model for testing with multidimensional items0 amodel for testing with multidimensional items aMinneapolis, MN. USAbUniversity of Minnesota, Department of Psychology, Psychometrics Methods Programc06/1978 a82-981 aSympson, J B uhttp://www.iacat.org/content/model-testing-multidimensional-items00635nas a2200097 4500008004100000245007400041210006900115260024200184100001300426856009800439 1978 eng d00aPanel discussion: Future directions for computerized adaptive testing0 aPanel discussion Future directions for computerized adaptive tes aD. J. Weiss (Ed.), Proceedings of the 1977 Item Response Theory and Computerized adaptive conference. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aLord, FM uhttp://www.iacat.org/content/panel-discussion-future-directions-computerized-adaptive-testing00364nas a2200121 4500008004100000245004300041210004300084300001200127490000700139100001400146700001500160856006700175 1978 eng d00aPredictive ability of a branching test0 aPredictive ability of a branching test a415-4190 v381 aBrooks, S1 aHartz, M A uhttp://www.iacat.org/content/predictive-ability-branching-test00491nam a2200097 4500008004100000245006900041210006900110260010900179100001400288856009100302 1978 eng d00aProceedings of the 1977 Computerized Adaptive Testing Conference0 aProceedings of the 1977 Computerized Adaptive Testing Conference aMinneapolis: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://www.iacat.org/content/proceedings-1977-computerized-adaptive-testing-conference00472nas a2200121 4500008004100000245008900041210006900130300001200199490000600211100001400217700001400231856010500245 1978 eng d00aThe stratified adaptive ability test as a tool for personnel selection and placement0 astratified adaptive ability test as a tool for personnel selecti a135-1510 v81 aVale, C D1 aWeiss, DJ uhttp://www.iacat.org/content/stratified-adaptive-ability-test-tool-personnel-selection-and-placement00403nas a2200133 4500008003900000245004900039210004700088300001200135490000700147100001300154700001500167700001400182856007300196 1978 d00aA stratified adaptive test of verbal ability0 astratified adaptive test of verbal ability a229-2380 v261 aShiba, S1 aNoguchi, H1 aHaebra, T uhttp://www.iacat.org/content/stratified-adaptive-test-verbal-ability00567nas a2200109 4500008003900000245005900039210005800098260018500156100001700341700001600358856008300374 1977 d00aAdaptive Branching in a Multi-Content Achievement Test0 aAdaptive Branching in a MultiContent Achievement Test aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aPennell, R J1 aHarris, D A uhttp://www.iacat.org/content/adaptive-branching-multi-content-achievement-test00407nas a2200097 4500008004100000245004500041210004200086260009600128100001700224856006800241 1977 eng d00aAn adaptive test of arithmetic reasoning0 aadaptive test of arithmetic reasoning athe Proceedings of the Nineteenth Military Testing Association conference, San Antonio, TX.1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-test-arithmetic-reasoning00527nas a2200097 4500008004100000245005500041210005500096260018700151100001400338856007700352 1977 eng d00aAdaptive testing and the problem of classification0 aAdaptive testing and the problem of classification aD. Weiss (Ed.), Applications of computerized adaptive testing (Research Report 77-1). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aVale, C D uhttp://www.iacat.org/content/adaptive-testing-and-problem-classification00631nas a2200109 4500008003900000245008400039210006900123260018500192100001800377700001600395856011000411 1977 d00aAdaptive Testing Applied to Hierarchically Structured Objectives-Based Programs0 aAdaptive Testing Applied to Hierarchically Structured Objectives aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aHambleton, RK1 aEignor, D R uhttp://www.iacat.org/content/adaptive-testing-applied-hierarchically-structured-objectives-based-programs00538nas a2200109 4500008003900000245008700039210006900126260009700195100001500292700001400307856010700321 1977 d00aAn adaptive testing strategy for achievement test batteries (Research Rep No 77-6)0 aadaptive testing strategy for achievement test batteries Researc aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aBrown, J M1 aWeiss, DJ uhttp://www.iacat.org/content/adaptive-testing-strategy-achievement-test-batteries-research-rep-no-77-600457nas a2200133 4500008004100000245006300041210006300104300001200167490000600179100001700185700001700202700001800219856008600237 1977 eng d00aApplication of tailored testing to achievement measurement0 aApplication of tailored testing to achievement measurement a158-1610 v91 aEnglish, R A1 aReckase, M D1 aPatience, W M uhttp://www.iacat.org/content/application-tailored-testing-achievement-measurement00533nam a2200097 4500008004100000245013000041210006900171260005700240100001700297856012100314 1977 eng d00aAn application of the Rasch one-parameter logistic model to individual intelligence testing in a tailored testing environment0 aapplication of the Rasch oneparameter logistic model to individu aDissertation Abstracts International, 37 (9-A), 57661 aIreland, C M uhttp://www.iacat.org/content/application-rasch-one-parameter-logistic-model-individual-intelligence-testing-tailored00593nas a2200097 4500008004100000245007800041210006900119260019100188100001500379856010100394 1977 eng d00aApplications of adaptive testing in measuring achievement and performance0 aApplications of adaptive testing in measuring achievement and pe aD. J. Weiss (Ed.), Applications of computerized adaptive testing (Research Report 77-1). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program. 1 aBejar, I I uhttp://www.iacat.org/content/applications-adaptive-testing-measuring-achievement-and-performance00534nas a2200097 4500008004100000245007300041210006900114260014200183100001400325856009700339 1977 eng d00aApplications of computerized adaptive testing (Research Report 77-1)0 aApplications of computerized adaptive testing Research Report 77 aMinneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aWeiss, DJ uhttp://www.iacat.org/content/applications-computerized-adaptive-testing-research-report-77-100471nas a2200109 4500008004100000245007300041210006900114260005000183100001700233700001500250856009600265 1977 eng d00aApplications of sequential testing procedures to performance testing0 aApplications of sequential testing procedures to performance tes aMinneapolis, MN. USAbUniversity of Minnesota1 aEpstein, K I1 aKnerr, C S uhttp://www.iacat.org/content/applications-sequential-testing-procedures-performance-testing00433nas a2200109 4500008004100000245007700041210006900118300001200187490000600199100001700205856010100222 1977 En d00aBayesian Tailored Testing and the Influence of Item Bank Characteristics0 aBayesian Tailored Testing and the Influence of Item Bank Charact a111-1200 v11 aJensema, C J uhttp://www.iacat.org/content/bayesian-tailored-testing-and-influence-item-bank-characteristics-100431nas a2200109 4500008004100000245007700041210006900118300001200187490000600199100001700205856009900222 1977 eng d00aBayesian tailored testing and the influence of item bank characteristics0 aBayesian tailored testing and the influence of item bank charact a111-1200 v11 aJensema, C J uhttp://www.iacat.org/content/bayesian-tailored-testing-and-influence-item-bank-characteristics00478nas a2200097 4500008004100000245004100041210003900082260017700121100001700298856006500315 1977 eng d00aA brief overview of adaptive testing0 abrief overview of adaptive testing aD. J. Weiss (Ed.), Applications of computerized testing (Research Report 77-1). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aMcBride, J R uhttp://www.iacat.org/content/brief-overview-adaptive-testing00356nas a2200109 4500008004100000245005100041210004700092300001100139490000600150100001400156856007600170 1977 En d00aA Broad-Range Tailored Test of Verbal Ability 0 aBroadRange Tailored Test of Verbal Ability a95-1000 v11 aLord, F M uhttp://www.iacat.org/content/broad-range-tailored-test-verbal-ability-100352nas a2200109 4500008004100000245005000041210004700091300001100138490000600149100001300155856007400168 1977 eng d00aA broad-range tailored test of verbal ability0 abroadrange tailored test of verbal ability a95-1000 v11 aLord, FM uhttp://www.iacat.org/content/broad-range-tailored-test-verbal-ability00560nas a2200121 4500008004100000245009900041210006900140260007200209100001500281700001400296700001900310856010900329 1977 eng d00aCalibration of an item pool for the adaptive measurement of achievement (Research Report 77-5)0 aCalibration of an item pool for the adaptive measurement of achi aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBejar, I I1 aWeiss, DJ1 aKingsbury, G G uhttp://www.iacat.org/content/calibration-item-pool-adaptive-measurement-achievement-research-report-77-500560nas a2200097 4500008004100000245006600041210006400107260018600171100001500357856009000372 1977 eng d00aA comparison of conventional and adaptive achievement testing0 acomparison of conventional and adaptive achievement testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aBejar, I I uhttp://www.iacat.org/content/comparison-conventional-and-adaptive-achievement-testing00525nam a2200097 4500008004100000245011600041210006900157260006500226100001400291856012200305 1977 eng d00aA comparison of the classification of students by two methods of administration of a mathematics placement test0 acomparison of the classification of students by two methods of a aUnpublished doctoral dissertation, Syracuse University, 19771 aBrooks, S uhttp://www.iacat.org/content/comparison-classification-students-two-methods-administration-mathematics-placement-test00589nam a2200121 4500008004100000024005800041050003600099245007700135210006900212260007300281100001900354856009400373 1977 eng d aDissertation abstracts International, 1978, 38, 4993B aUniversity Microfims No.78-450300aA computer adaptive approach to the measurement of personality variables0 acomputer adaptive approach to the measurement of personality var aUnpublished doctoral dissertation, University of Maryland, Baltimore1 aSapinkopf, R C uhttp://www.iacat.org/content/computer-adaptive-approach-measurement-personality-variables01595nas a2200133 4500008004100000245010600041210006900147300001200216490000700228520106500235100001701300700001801317856012601335 1977 eng d00aA computer simulation study of tailored testing strategies for objective-based instructional programs0 acomputer simulation study of tailored testing strategies for obj a139-1580 v373 aOne possible way of reducing the amount of time spent testing in . objective-based instructional programs would involve the implementation of a tailored testing strategy. Our purpose was to provide some additional data on the effectiveness of various tailored testing strategies for different testing situations. The three factors of a tailored testing strategy under study with various hypothetical distributions of abilities across two learning hierarchies were test length, mastery cutting score, and starting point. Overall, our simulation results indicate that it is possible to obtain a reduction of more than 50% in testing time without any loss in decision-making accuracy, when compared to a conventional testing procedure, by implementing a tailored testing strategy. In addition, our study of starting points revealed that it was generally best to begin testing in the middle of the learning hierarchy. Finally we observed a 40% reduction in errors of classification as the number of items for testing each objective was increased from one to five.1 aSpineti, J P1 aHambleton, RK uhttp://www.iacat.org/content/computer-simulation-study-tailored-testing-strategies-objective-based-instructional-programs00572nas a2200121 4500008004100000245008700041210006900128260009400197100001700291700001400308700001500322856011300337 1977 eng d00aComputer-assisted tailored testing: Examinee reactions and evaluation (PB-276 748)0 aComputerassisted tailored testing Examinee reactions and evaluat aWashington DC: U. S. Civil Service Commission, Personnel Research and Development Center.1 aSchmidt, F L1 aUrry, V W1 aGugel, J F uhttp://www.iacat.org/content/computer-assisted-tailored-testing-examinee-reactions-and-evaluation-pb-276-74800590nas a2200097 4500008003900000245007500039210006900114260018600183100001900369856010400388 1977 d00aComputerized Adaptive Testing and Personnel Accessioning System Design0 aComputerized Adaptive Testing and Personnel Accessioning System  aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aUnderwood, M A uhttp://www.iacat.org/content/computerized-adaptive-testing-and-personnel-accessioning-system-design00525nas a2200097 4500008004100000245005900041210005900100260016300159100001700322856008800339 1977 eng d00aComputerized Adaptive Testing research and development0 aComputerized Adaptive Testing research and development aH. Taylor, Proceedings of the Second Training and Personnel Technology Conference. Washington, DC: Office of the Director of Defense Research and Engineering.1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-research-and-development00541nas a2200097 4500008003900000245006100039210006100100260018500161100001400346856008300360 1977 d00aComputerized Adaptive Testing with a Military Population0 aComputerized Adaptive Testing with a Military Population aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolls MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aGorman, S uhttp://www.iacat.org/content/computerized-adaptive-testing-military-population00360nas a2200109 4500008004100000245005000041210005000091300001200141490000600153100001800159856007300177 1977 eng d00aDescription of components in tailored testing0 aDescription of components in tailored testing a153-1570 v91 aPatience, W M uhttp://www.iacat.org/content/description-components-tailored-testing00468nas a2200109 4500008004500000245009500045210006900140300001200209490000600221100001400227856011700241 1977 Engldsh 00aEffects of Immediate Knowledge of Results and Adaptive Testing on Ability Test Performance0 aEffects of Immediate Knowledge of Results and Adaptive Testing o a259-2660 v11 aBetz, N E uhttp://www.iacat.org/content/effects-immediate-knowledge-results-and-adaptive-testing-ability-test-performance-000462nas a2200109 4500008004100000245009500041210006900136300001200205490000600217100001400223856011500237 1977 eng d00aEffects of immediate knowledge of results and adaptive testing on ability test performance0 aEffects of immediate knowledge of results and adaptive testing o a259-2660 v21 aBetz, N E uhttp://www.iacat.org/content/effects-immediate-knowledge-results-and-adaptive-testing-ability-test-performance00653nas a2200097 4500008003900000245012300039210006900162260018600231100001900417856011900436 1977 d00aEffects of Knowledge of Results and Varying Proportion Correct on Ability Test Performance and Psychological Variables0 aEffects of Knowledge of Results and Varying Proportion Correct o aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aPrestwood, J S uhttp://www.iacat.org/content/effects-knowledge-results-and-varying-proportion-correct-ability-test-performance-and00634nas a2200121 4500008004100000245007800041210006900119260018600188100001500374700001400389700001700403856009200420 1977 eng d00aAn empirical evaluation of implied orders as a basis for tailored testing0 aempirical evaluation of implied orders as a basis for tailored t aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aCliff, N A1 aCudeck, R1 aMcCormick, D uhttp://www.iacat.org/content/empirical-evaluation-implied-orders-basis-tailored-testing00441nas a2200109 4500008003900000245008500039210006900124300001200193490000600205100001600211856010400227 1977 d00aAn Empirical Investigation of the Stratified Adaptive Computerized Testing Model0 aEmpirical Investigation of the Stratified Adaptive Computerized  a141-1520 v11 aWaters, B K uhttp://www.iacat.org/content/empirical-investigation-stratified-adaptive-computerized-testing-model00530nas a2200097 4500008004100000245005800041210005800099260017700157100001700334856008100351 1977 eng d00aEstimation of latent trait status in adaptive testing0 aEstimation of latent trait status in adaptive testing aD. J. Weiss (Ed.), Applications of computerized testing (Research Report 77-1). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aSympson, J B uhttp://www.iacat.org/content/estimation-latent-trait-status-adaptive-testing00488nas a2200121 4500008004100000245007500041210006900116260003700185100001600222700001200238700001600250856010000266 1977 eng d00aFlexilevel adaptive testing paradigm: Validation in technical training0 aFlexilevel adaptive testing paradigm Validation in technical tra aAFHRL Technical Report 77-35 (I)1 aHansen, D N1 aRoss, S1 aHarris, D A uhttp://www.iacat.org/content/flexilevel-adaptive-testing-paradigm-validation-technical-training00492nas a2200121 4500008004100000245007500041210006900116260003800185100001600223700001200239700001600251856010300267 1977 eng d00aFlexilevel adaptive training paradigm: Hierarchical concept structures0 aFlexilevel adaptive training paradigm Hierarchical concept struc aAFHRL Technical Report 77-35 (II)1 aHansen, D N1 aRoss, S1 aHarris, D A uhttp://www.iacat.org/content/flexilevel-adaptive-training-paradigm-hierarchical-concept-structures00412nas a2200097 4500008004100000245006300041210006300104260004200167100001600209856008900225 1977 eng d00aFour realizations of pyramidal adaptive testing strategies0 aFour realizations of pyramidal adaptive testing strategies aUniversity of Leiden, The Netherlands1 aHornke, L F uhttp://www.iacat.org/content/four-realizations-pyramidal-adaptive-testing-strategies00428nas a2200109 4500008004100000245006300041210006300104260003700167100001200204700001300216856008900229 1977 eng d00aGroup tailored tests and some problems of their utlization0 aGroup tailored tests and some problems of their utlization aLeyden, The Netherlandsc06/19771 aLewy, A1 aDoron, R uhttp://www.iacat.org/content/group-tailored-tests-and-some-problems-their-utlization00635nas a2200097 4500008003900000245010600039210006900145260018600214100001300400856012400413 1977 d00aImplementation of a Model Adaptive Testing System at an Armed Forces Entrance and Examination Station0 aImplementation of a Model Adaptive Testing System at an Armed Fo aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aRee, M J uhttp://www.iacat.org/content/implementation-model-adaptive-testing-system-armed-forces-entrance-and-examination-station00570nas a2200097 4500008003900000245007100039210006900110260018500179100001800364856009000382 1977 d00aImplementation of Tailored Testing at the Civil Service Commission0 aImplementation of Tailored Testing at the Civil Service Commissi aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aMcKillip, R H uhttp://www.iacat.org/content/implementation-tailored-testing-civil-service-commission00605nas a2200121 4500008004100000245013200041210006900173260007200242100001500314700001400329700001800343856012200361 1977 eng d00aAn information comparison of conventional and adaptive tests in the measurement of classroom achievement (Research Report 77-7)0 ainformation comparison of conventional and adaptive tests in the aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBejar, I I1 aWeiss, DJ1 aGialluca, K A uhttp://www.iacat.org/content/information-comparison-conventional-and-adaptive-tests-measurement-classroom-achievement00580nas a2200109 4500008003900000245006500039210006200104260018500166100001500351700001600366856008800382 1977 d00aA Low-Cost Terminal Usable for Computerized Adaptive Testing0 aLowCost Terminal Usable for Computerized Adaptive Testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aLamos, J P1 aWaters, B K uhttp://www.iacat.org/content/low-cost-terminal-usable-computerized-adaptive-testing00516nas a2200097 4500008004100000245005200041210005000093260018600143100001700329856007200346 1977 eng d00aA model for testing with multidimensional items0 amodel for testing with multidimensional items aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSympson, J B uhttp://www.iacat.org/content/model-testing-multidimensional-items-000551nas a2200109 4500008003900000245005400039210005300093260018600146100001400332700001500346856008000361 1977 d00aMulti-Content Adaptive Measurement of Achievement0 aMultiContent Adaptive Measurement of Achievement aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWeiss, DJ1 aBrown, J M uhttp://www.iacat.org/content/multi-content-adaptive-measurement-achievement00616nas a2200097 4500008003900000245009400039210006900133260018600202100001400388856011600402 1977 d00aA Multivariate Model Sampling Procedure and a Method of Multidimensional Tailored Testing0 aMultivariate Model Sampling Procedure and a Method of Multidimen aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aUrry, V W uhttp://www.iacat.org/content/multivariate-model-sampling-procedure-and-method-multidimensional-tailored-testing00554nas a2200097 4500008003900000245006400039210006400103260018600167100001300353856009000366 1977 d00aOperational Considerations in Implementing Tailored Testing0 aOperational Considerations in Implementing Tailored Testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSegal, H uhttp://www.iacat.org/content/operational-considerations-implementing-tailored-testing00332nas a2200109 4500008004100000245004000041210004000081300001200121490000700133100001700140856006500157 1977 eng d00aProcedures for computerized testing0 aProcedures for computerized testing a351-3560 v701 aReckase, M D uhttp://www.iacat.org/content/procedures-computerized-testing00540nas a2200109 4500008004100000245008700041210006900128260009700197100001400294700001400308856010800322 1977 eng d00aA rapid item search procedure for Bayesian adaptive testing (Research Report 77-4)0 arapid item search procedure for Bayesian adaptive testing Resear aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aVale, C D1 aWeiss, DJ uhttp://www.iacat.org/content/rapid-item-search-procedure-bayesian-adaptive-testing-research-report-77-400391nas a2200097 4500008004100000245005900041210005800100260003700158100001900195856007900214 1977 eng d00aReal-data simulation of a proposal for tailored teting0 aRealdata simulation of a proposal for tailored teting aLeyden, The Netherlandsc06/19771 aKillcross, M C uhttp://www.iacat.org/content/real-data-simulation-proposal-tailored-teting00501nas a2200097 4500008003900000245004700039210004700086260018600133100001400319856007000333 1977 d00aReduction of Test Bias by Adaptive Testing0 aReduction of Test Bias by Adaptive Testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aPine, S M uhttp://www.iacat.org/content/reduction-test-bias-adaptive-testing00416nas a2200109 4500008004100000245006800041210006800109300001200177490000600189100001700195856009400212 1977 En d00aSome Properties of a Bayesian Adaptive Ability Testing Strategy0 aSome Properties of a Bayesian Adaptive Ability Testing Strategy a121-1400 v11 aMcBride, J R uhttp://www.iacat.org/content/some-properties-bayesian-adaptive-ability-testing-strategy-000414nas a2200109 4500008004100000245006800041210006800109300001200177490000600189100001700195856009200212 1977 eng d00aSome properties of a Bayesian adaptive ability testing strategy0 aSome properties of a Bayesian adaptive ability testing strategy a121-1400 v11 aMcBride, J R uhttp://www.iacat.org/content/some-properties-bayesian-adaptive-ability-testing-strategy00536nas a2200109 4500008004100000245004600041210004600087260018600133100001400319700001800333856007500351 1977 eng d00aStudent attitudes toward tailored testing0 aStudent attitudes toward tailored testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aKoch, W R1 aPatience, W M uhttp://www.iacat.org/content/student-attitudes-toward-tailored-testing00454nas a2200133 4500008004100000245006500041210006400106300001200170490000700182100001600189700001500205700001300220856008700233 1977 eng d00aTAILOR: A FORTRAN procedure for interactive tailored testing0 aTAILOR A FORTRAN procedure for interactive tailored testing a767-7690 v371 aCudeck, R A1 aCliff, N A1 aKehoe, J uhttp://www.iacat.org/content/tailor-fortran-procedure-interactive-tailored-testing00464nas a2200121 4500008004100000245008000041210006900121300001200190490000700202100001700209700001500226856010100241 1977 eng d00aTAILOR-APL: An interactive computer program for individual tailored testing0 aTAILORAPL An interactive computer program for individual tailore a771-7740 v371 aMcCormick, D1 aCliff, N A uhttp://www.iacat.org/content/tailor-apl-interactive-computer-program-individual-tailored-testing00491nas a2200097 4500008004100000245007800041210006900119260009300188100001400281856009800295 1977 eng d00aTailored testing: A spectacular success for latent trait theory (TS 77-2)0 aTailored testing A spectacular success for latent trait theory T aWashington DC: U. S. Civil Service Commission, Personnel Research and Development Center1 aUrry, V W uhttp://www.iacat.org/content/tailored-testing-spectacular-success-latent-trait-theory-ts-77-200416nas a2200109 4500008004100000245007000041210006900111300001200180490000700192100001400199856009300213 1977 eng d00aTailored testing: A successful application of latent trait theory0 aTailored testing A successful application of latent trait theory a181-1960 v141 aUrry, V W uhttp://www.iacat.org/content/tailored-testing-successful-application-latent-trait-theory00398nas a2200097 4500008004100000245007100041210006900112300001200181100001500193856009200208 1977 eng d00aA theory of consistency ordering generalizable to tailored testing0 atheory of consistency ordering generalizable to tailored testing a375-3991 aCliff, N A uhttp://www.iacat.org/content/theory-consistency-ordering-generalizable-tailored-testing00411nas a2200097 4500008004100000245005400041210004800095260007100143100002000214856007900234 1977 eng d00aA two-stage testing procedure (Memorandum 403-77)0 atwostage testing procedure Memorandum 40377 aUniversity of Leyden, The Netherlands, Educational Research Center1 aGruijter, D N M uhttp://www.iacat.org/content/two-stage-testing-procedure-memorandum-403-7700374nas a2200109 4500008004100000245005800041210005600099300001200155490000600167100001600173856007500189 1977 En d00aA Use of the Information Function in Tailored Testing0 aUse of the Information Function in Tailored Testing a233-2470 v11 aSamejima, F uhttp://www.iacat.org/content/use-information-function-tailored-testing00474nas a2200097 4500008004100000245007300041210006900114260008800183100001700271856008800288 1976 eng d00aAdaptive mental testing: The state of the art (Technical Report 423)0 aAdaptive mental testing The state of the art Technical Report 42 aWashington DC: U.S. Army Research Institute for the Social and Behavioral Sciences.1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-mental-testing-state-art-technical-report-42300432nas a2200109 4500008004100000245008400041210006900125300000700194490001000201100001200211856009900223 1976 eng d00aAdaptive testing: A Bayesian procedure for the efficient measurement of ability0 aAdaptive testing A Bayesian procedure for the efficient measurem a360 v13(2)1 aWood, R uhttp://www.iacat.org/content/adaptive-testing-bayesian-procedure-efficient-measurement-ability00589nas a2200097 4500008004100000245009200041210006900133260016000202100001400362856011500376 1976 eng d00aAdaptive testing research at Minnesota: Overview, recent results, and future directions0 aAdaptive testing research at Minnesota Overview recent results a aC. L. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 24-35). Washington DC: United States Civil Service Commission.1 aWeiss, DJ uhttp://www.iacat.org/content/adaptive-testing-research-minnesota-overview-recent-results-and-future-directions00617nas a2200097 4500008004100000245011800041210006900159260015300228100001700381856012100398 1976 eng d00aAdaptive testing research at Minnesota: Some properties of a Bayesian sequential adaptive mental testing strategy0 aAdaptive testing research at Minnesota Some properties of a Baye aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 36-53). Washington DC: U.S. Government Printing Office.1 aMcBride, J R uhttp://www.iacat.org/content/adaptive-testing-research-minnesota-some-properties-bayesian-sequential-adaptive-mental00457nas a2200097 4500008004100000245004400041210004200085260014400127100001700271856007100288 1976 eng d00aBandwidth, fidelity, and adaptive tests0 aBandwidth fidelity and adaptive tests aT. J. McConnell, Jr. (Ed.), CAT/C 2 1975: The second conference on computer-assisted test construction. Atlanta GA: Atlanta Public Schools.1 aMcBride, J R uhttp://www.iacat.org/content/bandwidth-fidelity-and-adaptive-tests00556nas a2200097 4500008004100000245007700041210006900118260015300187100001700340856010100357 1976 eng d00aBayesian tailored testing and the influence of item bank characteristics0 aBayesian tailored testing and the influence of item bank charact aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 82-89). Washington DC: U.S. Government Printing Office.1 aJensema, C J uhttp://www.iacat.org/content/bayesian-tailored-testing-and-influence-item-bank-characteristics-000479nas a2200097 4500008004100000245005000041210004800091260015300139100001300292856007600305 1976 eng d00aA broad range tailored test of verbal ability0 abroad range tailored test of verbal ability aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 75-78). Washington DC: U.S. Government Printing Office.1 aLord, FM uhttp://www.iacat.org/content/broad-range-tailored-test-verbal-ability-000576nas a2200109 4500008004100000245007700041210006900118260015300187100001800340700001400358856009400372 1976 eng d00aComputer-assisted testing: An orderly transition from theory to practice0 aComputerassisted testing An orderly transition from theory to pr aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 95-96). Washington DC: U.S. Government Printing Office.1 aMcKillip, R H1 aUrry, V W uhttp://www.iacat.org/content/computer-assisted-testing-orderly-transition-theory-practice00503nas a2200097 4500008004100000245008700041210006900128260009300197100001400290856010100304 1976 eng d00aComputer-assisted testing with live examinees: A rendezvous with reality (TN 75-3)0 aComputerassisted testing with live examinees A rendezvous with r aWashington DC: U. S. Civil Service Commission, Personnel Research and Development Center1 aUrry, V W uhttp://www.iacat.org/content/computer-assisted-testing-live-examinees-rendezvous-reality-tn-75-300388nas a2200097 4500008004100000245001500041210001500056260015900071100001400230856004600244 1976 eng d00aDiscussion0 aDiscussion aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. pp. 118-119). Washington DC: U.S. Government Printing Office.1 aGreen, BF uhttp://www.iacat.org/content/discussion-000383nas a2200097 4500008004100000245001500041210001500056260015500071100001300226856004600239 1976 eng d00aDiscussion0 aDiscussion aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 113-117). Washington DC: U.S. Government Printing Office.1 aLord, FM uhttp://www.iacat.org/content/discussion-200440nas a2200097 4500008004100000245009300041210006900134260001900203100001700222856010300239 1976 eng d00aThe effect of item pool characteristics on the operation of a tailored testing procedure0 aeffect of item pool characteristics on the operation of a tailor aMurray Hill NJ1 aReckase, M D uhttp://www.iacat.org/content/effect-item-pool-characteristics-operation-tailored-testing-procedure00554nas a2200121 4500008004100000245005600041210005600097260015500153100001500308700001700323700001400340856007800354 1976 eng d00aEffectiveness of the ancillary estimation procedure0 aEffectiveness of the ancillary estimation procedure aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 103-106). Washington DC: U.S. Government Printing Office.1 aGugel, J F1 aSchmidt, F L1 aUrry, V W uhttp://www.iacat.org/content/effectiveness-ancillary-estimation-procedure00629nas a2200109 4500008004100000245011800041210006900159260013900228100001400367700001400381856012400395 1976 eng d00aEffects of immediate knowledge of results and adaptive testing on ability test performance (Research Report 76-3)0 aEffects of immediate knowledge of results and adaptive testing o aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aBetz, N E1 aWeiss, DJ uhttp://www.iacat.org/content/effects-immediate-knowledge-results-and-adaptive-testing-ability-test-performance-research00411nas a2200097 4500008004100000245007000041210006900111260002700180100001500207856009100222 1976 eng d00aElements of a basic test theory generalizable to tailored testing0 aElements of a basic test theory generalizable to tailored testin aUnpublished manuscript1 aCliff, N A uhttp://www.iacat.org/content/elements-basic-test-theory-generalizable-tailored-testing00527nas a2200097 4500008004100000245006700041210006300108260015300171100001600324856008900340 1976 eng d00aAn empirical investigation of Weiss' stradaptive testing model0 aempirical investigation of Weiss stradaptive testing model aC. L. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 54-63.). Washington DC: U. S. Civil Service Commission.1 aWaters, B K uhttp://www.iacat.org/content/empirical-investigation-weiss-stradaptive-testing-model00463nas a2200109 4500008004100000245007800041210006900119260004300188490001300231100001600244856009300260 1976 eng d00aAn exploratory studyof the efficiency of the flexilevel testing procedure0 aexploratory studyof the efficiency of the flexilevel testing pro aToronto, CanadabUniversity of Toronto0 vDoctoral1 aSeguin, S P uhttp://www.iacat.org/content/exploratory-studyof-efficiency-flexilevel-testing-procedure00522nas a2200097 4500008004100000245006600041210006100107260015400168100001400322856008800336 1976 eng d00aA five-year quest: Is computerized adaptive testing feasible?0 afiveyear quest Is computerized adaptive testing feasible aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 97-102). Washington DC: U.S. Government Printing Office.1 aUrry, V W uhttp://www.iacat.org/content/five-year-quest-computerized-adaptive-testing-feasible00546nas a2200097 4500008004100000245007400041210006900115260015200184100001600336856009600352 1976 eng d00aThe graded response model of latent trait theory and tailored testing0 agraded response model of latent trait theory and tailored testin aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 5-17). Washington DC: U.S. Government Printing Office.1 aSamejima, F uhttp://www.iacat.org/content/graded-response-model-latent-trait-theory-and-tailored-testing00459nas a2200121 4500008004100000245007800041210006900119300001200188490000600200100001600206700001400222856010100236 1976 eng d00aHardware and software evolution of an adaptive ability measurement system0 aHardware and software evolution of an adaptive ability measureme a104-1070 v81 aDeWitt, L J1 aWeiss, DJ uhttp://www.iacat.org/content/hardware-and-software-evolution-adaptive-ability-measurement-system00480nam a2200097 4500008004100000245004700041210004700088260015600135100001500291856007600306 1976 eng d00aIncomplete orders and computerized testing0 aIncomplete orders and computerized testing aIn C. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 18-23). Washington DC: U.S. Government Printing Office.1 aCliff, N A uhttp://www.iacat.org/content/incomplete-orders-and-computerized-testing00515nas a2200109 4500008004100000245005200041210005200093260015600145100001700301700001400318856007300332 1976 eng d00aItem parameterization procedures for the future0 aItem parameterization procedures for the future aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 107-112.). Washington DC: U.S. Government Printing Office.1 aSchmidt, F L1 aUrry, V W uhttp://www.iacat.org/content/item-parameterization-procedures-future00587nas a2200133 4500008004100000245009400041210006900135260007200204100001600276700001500292700001800307700001900325856010900344 1976 eng d00aMonte carlo results from a computer program for tailored testing (Technical Report No. 2)0 aMonte carlo results from a computer program for tailored testing aLos Angeles CA: University of California, Department of Psychology.1 aCudeck, R A1 aCliff, N A1 aReynolds, T J1 aMcCormick, D J uhttp://www.iacat.org/content/monte-carlo-results-computer-program-tailored-testing-technical-report-no-200504nas a2200097 4500008004100000245002000041210002000061260026000081100001600341856004900357 1976 eng d00aOpening remarks0 aOpening remarks aW. H. Gorham (Chair), Computers and testing: Steps toward the inevitable conquest (PS 76-1). Symposium presented at the 83rd annual convention of the APA, Chicago IL. Washington DC: U.S. Civil Service Commission, Personnel Research and Developement Center1 aGorham, W A uhttp://www.iacat.org/content/opening-remarks00320nas a2200097 4500008004100000245004000041210004000081260001700121100001700138856006700155 1976 eng d00aProcedures for computerized testing0 aProcedures for computerized testing aSt. Louis MO1 aReckase, M D uhttp://www.iacat.org/content/procedures-computerized-testing-000439nam a2200097 4500008004100000245007300041210006900114260005100183100001500234856009200249 1976 eng d00aProceedings of the first conference on computerized adaptive testing0 aProceedings of the first conference on computerized adaptive tes aWashington DC: U.S. Government Printing Office1 aClark, C K uhttp://www.iacat.org/content/proceedings-first-conference-computerized-adaptive-testing00620nas a2200109 4500008004100000245011200041210006900153260013900222100001400361700001400375856012100389 1976 eng d00aPsychological effects of immediate knowledge of results and adaptive ability testing (Research Report 76-4)0 aPsychological effects of immediate knowledge of results and adap aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aBetz, N E1 aWeiss, DJ uhttp://www.iacat.org/content/psychological-effects-immediate-knowledge-results-and-adaptive-ability-testing-research00442nas a2200097 4500008004100000245003600041210003600077260015300113100001600266856006200282 1976 eng d00aReflections on adaptive testing0 aReflections on adaptive testing aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 90-94). Washington DC: U.S. Government Printing Office.1 aHansen, D N uhttp://www.iacat.org/content/reflections-adaptive-testing00435nas a2200097 4500008004100000245007100041210006900112260005200181100001700233856008700250 1976 eng d00aResearch on adaptive testing 1973-1976: A review of the literature0 aResearch on adaptive testing 19731976 A review of the literature aUnpublished manuscript, University of Minnesota1 aMcBride, J R uhttp://www.iacat.org/content/research-adaptive-testing-1973-1976-review-literature00456nas a2200097 4500008004100000245006100041210005800102260009800160100001900258856008100277 1976 eng d00aA review of research in tailored testing (Report APRE No0 areview of research in tailored testing Report APRE No a9/76, Farnborough, Hants, U. K.: Ministry of Defence, Army Personnel Research Establishment.)1 aKillcross, M C uhttp://www.iacat.org/content/review-research-tailored-testing-report-apre-no00465nam a2200097 4500008004100000245006900041210006800110260008000178100001700258856009200275 1976 eng d00aSimulation studies of adaptive testing: A comparative evaluation0 aSimulation studies of adaptive testing A comparative evaluation aUnpublished doctoral dissertation, University of Minnesota, Minneapolis, MN1 aMcBride, J R uhttp://www.iacat.org/content/simulation-studies-adaptive-testing-comparative-evaluation00499nas a2200097 4500008004100000245005600041210005600097260015300153100001300306856008200319 1976 eng d00aSome likelihood functions found in tailored testing0 aSome likelihood functions found in tailored testing aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 79-81). Washington DC: U.S. Government Printing Office.1 aLord, FM uhttp://www.iacat.org/content/some-likelihood-functions-found-tailored-testing00542nas a2200109 4500008004100000245009100041210006900132260008700201100001700288700001400305856011300319 1976 eng d00aSome properties of a Bayesian adaptive ability testing strategy (Research Report 76-1)0 aSome properties of a Bayesian adaptive ability testing strategy  aMinneapolis MN: Department of Psychology, Computerized Adaptive Testing Laboratory1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/some-properties-bayesian-adaptive-ability-testing-strategy-research-report-76-100372nas a2200097 4500008004100000245004000041210004000081260007500121100001300196856006500209 1976 eng d00aTest theory and the public interest0 aTest theory and the public interest aProceedings of the Educational Testing Service Invitational Conference1 aLord, FM uhttp://www.iacat.org/content/test-theory-and-public-interest00646nas a2200097 4500008004100000245014800041210006900189260015300258100001400411856012300425 1976 eng d00aUsing computerized tests to add new dimensions to the measurement of abilities which are important for on-job performance: An exploratory study0 aUsing computerized tests to add new dimensions to the measuremen aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 64-74). Washington DC: U.S. Government Printing Office.1 aCory, C H uhttp://www.iacat.org/content/using-computerized-tests-add-new-dimensions-measurement-abilities-which-are-important-job00490nas a2200097 4500008004100000245008200041210006900123260008100192100001500273856010400288 1975 eng d00aA basic test theory generalizable to tailored testing (Technical Report No 1)0 abasic test theory generalizable to tailored testing Technical Re aLos Angeles CA: University of Southern California, Department of Psychology.1 aCliff, N A uhttp://www.iacat.org/content/basic-test-theory-generalizable-tailored-testing-technical-report-no-100464nas a2200109 4500008004100000245009900041210006900140300001200209490000700221100001400228856011200242 1975 eng d00aA Bayesian sequential procedure for quantal response in the context of adaptive mental testing0 aBayesian sequential procedure for quantal response in the contex a351-3560 v701 aOwen, R J uhttp://www.iacat.org/content/bayesian-sequential-procedure-quantal-response-context-adaptive-mental-testing00435nas a2200097 4500008004100000245009000041210006900131260001400200100001600214856010700230 1975 eng d00aBehavior of the maximum likelihood estimate in a simulated tailored testing situation0 aBehavior of the maximum likelihood estimate in a simulated tailo aIowa City1 aSamejima, F uhttp://www.iacat.org/content/behavior-maximum-likelihood-estimate-simulated-tailored-testing-situation00515nas a2200109 4500008004100000245007500041210006900116260008500185100001600270700001700286856010200303 1975 eng d00aBest test design and self-tailored testing (Research Memorandum No 19)0 aBest test design and selftailored testing Research Memorandum No aChicago: University of Chicago, Department of Education, Statistical Laboratory.1 aWright, B D1 aDouglas, G A uhttp://www.iacat.org/content/best-test-design-and-self-tailored-testing-research-memorandum-no-1900367nas a2200097 4500008004100000245005100041210004500092260004600137100001300183856007300196 1975 eng d00aA broad range test of verbal ability (RB-75-5)0 abroad range test of verbal ability RB755 aPrinceton NJ: Educational Testing Service1 aLord, FM uhttp://www.iacat.org/content/broad-range-test-verbal-ability-rb-75-500445nas a2200109 4500008004100000245008400041210006900125300001200194490000700206100001500213856010700228 1975 eng d00aComplete orders from incomplete data: Interactive ordering and tailored testing0 aComplete orders from incomplete data Interactive ordering and ta a259-3020 v821 aCliff, N A uhttp://www.iacat.org/content/complete-orders-incomplete-data-interactive-ordering-and-tailored-testing00348nas a2200109 4500008004100000245004600041210004600087300000900133490000700142100001400149856007500163 1975 eng d00aComputerized adaptive ability measurement0 aComputerized adaptive ability measurement a1-180 v281 aWeiss, DJ uhttp://www.iacat.org/content/computerized-adaptive-ability-measurement00528nas a2200097 4500008004100000245009100041210006900132260009800201100001400299856011700313 1975 eng d00aComputerized adaptive trait measurement: Problems and prospects (Research Report 75-5)0 aComputerized adaptive trait measurement Problems and prospects R aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aWeiss, DJ uhttp://www.iacat.org/content/computerized-adaptive-trait-measurement-problems-and-prospects-research-report-75-500444nas a2200097 4500008004100000245001500041210001500056260021600071100001300287856004600300 1975 eng d00aDiscussion0 aDiscussion aD. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5), pp. 44-46. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aLinn, RL uhttp://www.iacat.org/content/discussion-100443nas a2200097 4500008004100000245001500041210001500056260021600071100001400287856004400301 1975 eng d00aDiscussion0 aDiscussion aD. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5), pp. 46-49. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aBock, R D uhttp://www.iacat.org/content/discussion00471nas a2200097 4500008004100000245010400041210006900145260002100214100001700235856012100252 1975 eng d00aThe effect of item choice on ability estimation when using a simple logistic tailored testing model0 aeffect of item choice on ability estimation when using a simple  aWashington, D.C.1 aReckase, M D uhttp://www.iacat.org/content/effect-item-choice-ability-estimation-when-using-simple-logistic-tailored-testing-model00524nas a2200109 4500008004100000245009000041210006900131260007200200100001400272700001400286856011400300 1975 eng d00aEmpirical and simulation studies of flexilevel ability testing (Research Report 75-3)0 aEmpirical and simulation studies of flexilevel ability testing R aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBetz, N E1 aWeiss, DJ uhttp://www.iacat.org/content/empirical-and-simulation-studies-flexilevel-ability-testing-research-report-75-300556nas a2200109 4500008004100000245009400041210006900135260009700204100001600301700001400317856011500331 1975 eng d00aAn empirical comparison of two-stage and pyramidal ability testing (Research Report 75-1)0 aempirical comparison of twostage and pyramidal ability testing R aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aLarkin, K C1 aWeiss, DJ uhttp://www.iacat.org/content/empirical-comparison-two-stage-and-pyramidal-ability-testing-research-report-75-100574nas a2200097 4500008004100000245006000041210006000101260021600161100001700377856008200394 1975 eng d00aEvaluating the results of computerized adaptive testing0 aEvaluating the results of computerized adaptive testing aD. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5), pp. 26-31. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSympson, J B uhttp://www.iacat.org/content/evaluating-results-computerized-adaptive-testing00575nas a2200097 4500008004100000245006000041210006000101260021600161100001400377856008600391 1975 eng d00aNew types of information and psychological implications0 aNew types of information and psychological implications aD. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5), pp. 32-43. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aBetz, N E uhttp://www.iacat.org/content/new-types-information-and-psychological-implications00485nas a2200097 4500008004100000245002700041210002700068260021900095100001700314856005600331 1975 eng d00aScoring adaptive tests0 aScoring adaptive tests aD. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5), pp. 17-25. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aMcBride, J R uhttp://www.iacat.org/content/scoring-adaptive-tests00376nas a2200109 4500008004100000245005600041210005600097300001000153490000600163100001600169856008100185 1975 eng d00aSequential testing for instructional classification0 aSequential testing for instructional classification a92-990 v11 aThomas, D B uhttp://www.iacat.org/content/sequential-testing-instructional-classification00521nas a2200109 4500008004100000245007700041210006900118260009700187100001400284700001400298856009900312 1975 eng d00aA simulation study of stradaptive ability testing (Research Report 75-6)0 asimulation study of stradaptive ability testing Research Report  aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aVale, C D1 aWeiss, DJ uhttp://www.iacat.org/content/simulation-study-stradaptive-ability-testing-research-report-75-600538nas a2200097 4500008004100000245004900041210004900090260021500139100001400354856007200368 1975 eng d00aStrategies of branching through an item pool0 aStrategies of branching through an item pool aD. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5), pp. 1-16. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aVale, C D uhttp://www.iacat.org/content/strategies-branching-through-item-pool00543nas a2200109 4500008004100000245008800041210006900129260009700198100001400295700001400309856011000323 1975 eng d00aA study of computer-administered stradaptive ability testing (Research Report 75-4)0 astudy of computeradministered stradaptive ability testing Resear aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aVale, C D1 aWeiss, DJ uhttp://www.iacat.org/content/study-computer-administered-stradaptive-ability-testing-research-report-75-400428nas a2200109 4500008004100000245007200041210006900113260001100182100001500193700001400208856009600222 1975 eng d00aTailored testing: Maximizing validity and utility for job selection0 aTailored testing Maximizing validity and utility for job selecti aCanada1 aCroll, P R1 aUrry, V W uhttp://www.iacat.org/content/tailored-testing-maximizing-validity-and-utility-job-selection00367nas a2200109 4500008004100000245005400041210005100095300001000146490000700156100001700163856007700180 1974 eng d00aAn application of latent trait mental test theory0 aapplication of latent trait mental test theory a29-480 v271 aJensema, C J uhttp://www.iacat.org/content/application-latent-trait-mental-test-theory00406nas a2200097 4500008004100000245007400041210006900115260001700184100001700201856009000218 1974 eng d00aAn application of the Rasch simple logistic model to tailored testing0 aapplication of the Rasch simple logistic model to tailored testi aSt. Loius MO1 aReckase, M D uhttp://www.iacat.org/content/application-rasch-simple-logistic-model-tailored-testing00360nas a2200109 4500008004100000245004600041210004400087260002400131100001100155700001400166856007000180 1974 eng d00aA Bayesian approach in sequential testing0 aBayesian approach in sequential testing aChicago ILc04/19741 aHsu, T1 aPingel, K uhttp://www.iacat.org/content/bayesian-approach-sequential-testing00507nam a2200097 4500008004100000245010500041210006900146260006400215100001700279856011300296 1974 eng d00aThe comparison of two tailored testing models and the effects of the models variables on actual loss0 acomparison of two tailored testing models and the effects of the aUnpublished doctoral dissertation, Florida State University1 aKalisch, S J uhttp://www.iacat.org/content/comparison-two-tailored-testing-models-and-effects-models-variables-actual-loss00558nas a2200109 4500008004100000245008700041210006900128260011200197100001700309700001400326856010800340 1974 eng d00aA computer software system for adaptive ability measurement (Research Report 74-1)0 acomputer software system for adaptive ability measurement Resear aMinneapolis MN: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aDe Witt, J J1 aWeiss, DJ uhttp://www.iacat.org/content/computer-software-system-adaptive-ability-measurement-research-report-74-100552nas a2200097 4500008004100000245011200041210006900153260009300222100001400315856012500329 1974 eng d00aComputer-assisted testing: The calibration and evaluation of the verbal ability bank (Technical Study 74-3)0 aComputerassisted testing The calibration and evaluation of the v aWashington DC: U. S. Civil Service Commission, Personnel Research and Development Center1 aUrry, V W uhttp://www.iacat.org/content/computer-assisted-testing-calibration-and-evaluation-verbal-ability-bank-technical-study-7400740nas a2200145 4500008004100000245018400041210006900225260010800294100001600402700001700418700001500435700001100450700001200461856012100473 1974 eng d00aComputer-based adaptive testing models for the Air Force technical training environment: Phase I: Development of a computerized measurement system for Air Force technical Training0 aComputerbased adaptive testing models for the Air Force technica aJSAS Catalogue of Selected Documents in Psychology, 5, 1-86 (MS No. 882). AFHRL Technical Report 74-48.1 aHansen, D N1 aJohnson, B F1 aFagan, R L1 aTan, P1 aDick, W uhttp://www.iacat.org/content/computer-based-adaptive-testing-models-air-force-technical-training-environment-phase-i00543nas a2200121 4500008004100000245006900041210006700110260010600177100001700283700001400300700001600314856009100330 1974 eng d00aDevelopment of a programmed testing system (Technical Paper 259)0 aDevelopment of a programmed testing system Technical Paper 259 aArlington VA: US Army Research Institute for the Behavioral and Social Sciences. NTIS No. AD A001534)1 aBayroff, A G1 aRoss, R M1 aFischl, M A uhttp://www.iacat.org/content/development-programmed-testing-system-technical-paper-25900578nas a2200109 4500008004100000245010500041210006900146260009700215100001600312700001400328856012600342 1974 eng d00aAn empirical investigation of computer-administered pyramidal ability testing (Research Report 74-3)0 aempirical investigation of computeradministered pyramidal abilit aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aLarkin, K C1 aWeiss, DJ uhttp://www.iacat.org/content/empirical-investigation-computer-administered-pyramidal-ability-testing-research-report-74-300426nas a2200097 4500008004100000245008100041210006900122260002400191100001600215856009700231 1974 eng d00aAn empirical investigation of the stability and accuracy of flexilevel tests0 aempirical investigation of the stability and accuracy of flexile aChicago ILc03/10741 aKocher, A T uhttp://www.iacat.org/content/empirical-investigation-stability-and-accuracy-flexilevel-tests00529nam a2200097 4500008004100000245012200041210006900163260006100232100001600293856012200309 1974 eng d00aAn empirical investigation of the stratified adaptive computerized testing model for the measurement of human ability0 aempirical investigation of the stratified adaptive computerized  aUnpublished Ph.D. dissertation, Florida State University1 aWaters, B K uhttp://www.iacat.org/content/empirical-investigation-stratified-adaptive-computerized-testing-model-measurement-human00389nas a2200097 4500008004100000245006300041210005900104260002900163100001500192856008400207 1974 eng d00aAn evaluation of the self-scoring flexilevel testing model0 aevaluation of the selfscoring flexilevel testing model bFlorida State University1 aOlivier, P uhttp://www.iacat.org/content/evaluation-self-scoring-flexilevel-testing-model-000467nam a2200097 4500008004100000245006300041210005900104260010900163100001500272856008200287 1974 eng d00aAn evaluation of the self-scoring flexilevel testing model0 aevaluation of the selfscoring flexilevel testing model aUnpublished dissertation, Florida State University. Dissertation Abstracts International, 35 (7-A), 42571 aOlivier, P uhttp://www.iacat.org/content/evaluation-self-scoring-flexilevel-testing-model00529nas a2200097 4500008004100000245006400041210006400105260015600169100001300325856009300338 1974 eng d00aIndividualized testing and item characteristic curve theory0 aIndividualized testing and item characteristic curve theory aD. H. Krantz, R. C. Atkinson, R. D. Luce, and P. Suppes (Eds.), Contemporary developments in mathematical psychology (Vol. II). San Francisco: Freeman.1 aLord, FM uhttp://www.iacat.org/content/individualized-testing-and-item-characteristic-curve-theory00468nas a2200109 4500008004100000245009900041210006900140300001200209490000600221100001700227856011400244 1974 eng d00aAn interactive computer program for tailored testing based on the one-parameter logistic model0 ainteractive computer program for tailored testing based on the o a208-2120 v61 aReckase, M D uhttp://www.iacat.org/content/interactive-computer-program-tailored-testing-based-one-parameter-logistic-model00493nas a2200097 4500008004100000245010600041210006900147260004600216100001300262856012000275 1974 eng d00aPractical methods for redesigning a homogeneous test, also for designing a multilevel test (RB-74-30)0 aPractical methods for redesigning a homogeneous test also for de aPrinceton NJ: Educational Testing Service1 aLord, FM uhttp://www.iacat.org/content/practical-methods-redesigning-homogeneous-test-also-designing-multilevel-test-rb-74-3000585nas a2200109 4500008004100000245006900041210006900110260017300179100001700352700001400369856009200383 1974 eng d00aRecent and projected developments in ability testing by computer0 aRecent and projected developments in ability testing by computer aEarl Jones (Ed.), Symposium Proceedings: Occupational Research and the Navy–Prospectus 1980 (TR-74-14). San Diego, CA: Navy Personnel Research and Development Center.1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/recent-and-projected-developments-ability-testing-computer00494nas a2200109 4500008004100000245007500041210006900116260007200185100001400257700001400271856009900285 1974 eng d00aSimulation studies of two-stage ability testing (Research Report 74-4)0 aSimulation studies of twostage ability testing Research Report 7 aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBetz, N E1 aWeiss, DJ uhttp://www.iacat.org/content/simulation-studies-two-stage-ability-testing-research-report-74-400481nas a2200097 4500008004100000245007000041210006700111260009700178100001400275856009400289 1974 eng d00aStrategies of adaptive ability measurement (Research Report 74-5)0 aStrategies of adaptive ability measurement Research Report 745 aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://www.iacat.org/content/strategies-adaptive-ability-measurement-research-report-74-500458nas a2200109 4500008004100000245009000041210006900131300001000200490000600210100001700216856011500233 1974 eng d00aA tailored testing model employing the beta distribution and conditional difficulties0 atailored testing model employing the beta distribution and condi a22-280 v11 aKalisch, S J uhttp://www.iacat.org/content/tailored-testing-model-employing-beta-distribution-and-conditional-difficulties-000499nas a2200097 4500008004100000245008600041210006900127260008100196100001700277856010700294 1974 eng d00aA tailored testing model employing the beta distribution (unpublished manuscript)0 atailored testing model employing the beta distribution unpublish aFlorida State University, Educational Evaluation and Research Design Program1 aKalisch, S J uhttp://www.iacat.org/content/tailored-testing-model-employing-beta-distribution-unpublished-manuscript00421nas a2200097 4500008004100000245007900041210006900120260002000189100001900209856009500228 1974 eng d00aA tailored testing system for selection and allocation in the British Army0 atailored testing system for selection and allocation in the Brit aMontreal Canada1 aKillcross, M C uhttp://www.iacat.org/content/tailored-testing-system-selection-and-allocation-british-army00466nas a2200109 4500008004100000245009200041210006900133300001200202490000700214100001800221856011700239 1974 eng d00aTesting and decision-making procedures for selected individualized instruction programs0 aTesting and decisionmaking procedures for selected individualize a371-4000 v101 aHambleton, RK uhttp://www.iacat.org/content/testing-and-decision-making-procedures-selected-individualized-instruction-programs00343nas a2200109 4500008004100000245004600041210004200087300001200129490000700141100001700148856006800165 1974 eng d00aThe validity of Bayesian tailored testing0 avalidity of Bayesian tailored testing a757-7560 v341 aJensema, C J uhttp://www.iacat.org/content/validity-bayesian-tailored-testing00533nas a2200109 4500008004100000245008700041210006900128260008700197100001700284700001400301856010800315 1974 eng d00aA word knowledge item pool for adaptive ability measurement (Research Report 74-2)0 aword knowledge item pool for adaptive ability measurement Resear aMinneapolis MN: Department of Psychology, Computerized Adaptive Testing Laboratory1 aMcBride, J R1 aWeiss, DJ uhttp://www.iacat.org/content/word-knowledge-item-pool-adaptive-ability-measurement-research-report-74-200518nas a2200109 4500008004100000245007400041210006900115260009700184100001400281700001400295856009900309 1973 eng d00aAbility measurement: Conventional or adaptive? (Research Report 73-1)0 aAbility measurement Conventional or adaptive Research Report 731 aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ1 aBetz, N E uhttp://www.iacat.org/content/ability-measurement-conventional-or-adaptive-research-report-73-100441nas a2200109 4500008004100000245004100041210004000082260011100122100001300233700001500246856007000261 1973 eng d00aComputer-based psychological testing0 aComputerbased psychological testing aA. Elithorn and D. Jones (Eds.), Artificial and human thinking (pp. 83-93). San Francisco CA: Jossey-Bass.1 aJones, D1 aWeinman, J uhttp://www.iacat.org/content/computer-based-psychological-testing00535nas a2200109 4500008004100000245009700041210006900138260007200207100001400279700001400293856011800307 1973 eng d00aAn empirical study of computer-administered two-stage ability testing (Research Report 73-4)0 aempirical study of computeradministered twostage ability testing aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBetz, N E1 aWeiss, DJ uhttp://www.iacat.org/content/empirical-study-computer-administered-two-stage-ability-testing-research-report-73-400569nas a2200109 4500008004100000245013800041210006900179260005100248100001800299700001600317856012600333 1973 eng d00aImplementation of a Bayesian system for decision analysis in a program of individually prescribed instruction (Research Report No 60)0 aImplementation of a Bayesian system for decision analysis in a p aIowa City IA: American College Testing Program1 aFerguson, R L1 aNovick, M R uhttp://www.iacat.org/content/implementation-bayesian-system-decision-analysis-program-individually-prescribed-instruction00457nas a2200097 4500008004100000245009900041210006900140260001700209100001700226856011600243 1973 eng d00aAn interactive computer program for tailored testing based on the one-parameter logistic model0 ainteractive computer program for tailored testing based on the o aSt. Louis MO1 aReckase, M D uhttp://www.iacat.org/content/interactive-computer-program-tailored-testing-based-one-parameter-logistic-model-000681nam a2200121 4500008004100000024006400041050003900105245014600144210006900290260006400359100001600423856012000439 1973 eng d aDissertation abstracts International, 1974, 34, 4010A-4011A aUniversity Microfims No.73-31, 53400aA multivariate experimental study of three computerized adaptive testing models for the measurement of attitude toward teaching effectiveness0 amultivariate experimental study of three computerized adaptive t aUnpublished doctoral dissertation, Florida State University1 aTam, P T -K uhttp://www.iacat.org/content/multivariate-experimental-study-three-computerized-adaptive-testing-models-measurement00437nas a2200097 4500008004100000245006100041210005600102260008400158100001500242856008200257 1973 eng d00aAn overview of tailored testing (unpublished manuscript)0 aoverview of tailored testing unpublished manuscript aFlorida State University, Program of Educational Evaluation and Research Design1 aOlivier, P uhttp://www.iacat.org/content/overview-tailored-testing-unpublished-manuscript00452nas a2200109 4500008004100000245007700041210006900118260003000187100001900217700001400236856009200250 1973 eng d00aThe potential use of tailored testing for allocation to army employments0 apotential use of tailored testing for allocation to army employm aLisbon, Portugalc06/19731 aKillcross, M C1 aCassie, A uhttp://www.iacat.org/content/potential-use-tailored-testing-allocation-army-employments00308nas a2200109 4500008004100000245003200041210003100073300001200104490000700116100001400123856006100137 1973 eng d00aResponse-contingent testing0 aResponsecontingent testing a529-5440 v431 aWood, R L uhttp://www.iacat.org/content/response-contingent-testing00464nas a2200097 4500008004100000245008200041210006900123260005200192100001800244856010400262 1973 eng d00aA review of testing and decision-making procedures (Technical Bulletin No. 150 areview of testing and decisionmaking procedures Technical Bullet aIowa City IA: American College Testing Program.1 aHambleton, RK uhttp://www.iacat.org/content/review-testing-and-decision-making-procedures-technical-bulletin-no-1500496nas a2200097 4500008004100000245007700041210006900118260009700187100001400284856010000298 1973 eng d00aThe stratified adaptive computerized ability test (Research Report 73-3)0 astratified adaptive computerized ability test Research Report 73 aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aWeiss, DJ uhttp://www.iacat.org/content/stratified-adaptive-computerized-ability-test-research-report-73-300458nas a2200109 4500008004100000245009000041210006900131300001200200490000600212100001700218856011300235 1973 eng d00aA tailored testing model employing the beta distribution and conditional difficulties0 atailored testing model employing the beta distribution and condi a111-1200 v11 aKalisch, S J uhttp://www.iacat.org/content/tailored-testing-model-employing-beta-distribution-and-conditional-difficulties00505nas a2200097 4500008004100000245010000041210006900141260006400210100001700274856011600291 1972 eng d00aAn application of latent trait mental test theory to the Washington Pre-College Testing Battery0 aapplication of latent trait mental test theory to the Washington aUnpublished doctoral dissertation, University of Washington1 aJensema, C J uhttp://www.iacat.org/content/application-latent-trait-mental-test-theory-washington-pre-college-testing-battery00482nas a2200097 4500008004100000245009400041210006900135260005000204100001400254856011600268 1972 eng d00aFully adaptive sequential testing: A Bayesian procedure for efficient ability measurement0 aFully adaptive sequential testing A Bayesian procedure for effic aUnpublished manuscript, University of Chicago1 aWood, R L uhttp://www.iacat.org/content/fully-adaptive-sequential-testing-bayesian-procedure-efficient-ability-measurement00485nas a2200121 4500008004100000245009300041210006900134300000900203490000700212100001600219700001700235856011100252 1972 eng d00aIndividual intelligence testing without the examiner: reliability of an automated method0 aIndividual intelligence testing without the examiner reliability a9-140 v381 aElwood, D L1 aGriffin, H R uhttp://www.iacat.org/content/individual-intelligence-testing-without-examiner-reliability-automated-method00444nas a2200097 4500008004100000245007500041210006900116260004600185100001300231856010200244 1972 eng d00aIndividualized testing and item characteristic curve theory (RB-72-50)0 aIndividualized testing and item characteristic curve theory RB72 aPrinceton NJ: Educational Testing Service1 aLord, FM uhttp://www.iacat.org/content/individualized-testing-and-item-characteristic-curve-theory-rb-72-5000406nam a2200097 4500008004100000245005600041210005200097260006100149100001600210856008200226 1972 eng d00aA modification to Lord’s model for tailored tests0 amodification to Lord s model for tailored tests aUnpublished doctoral dissertation, University of Toronto1 aMussio, J J uhttp://www.iacat.org/content/modification-lord%E2%80%99s-model-tailored-tests00566nas a2200181 4500008004100000245005100041210004900092300001100141490000700152653000900159653004900168653004100217653000900258100001300267700001400280700001600294856007400310 1972 eng d00aSequential testing for dichotomous decisions. 0 aSequential testing for dichotomous decisions a85-95.0 v3210aCCAT10aCLASSIFICATION Computerized Adaptive Testing10asequential probability ratio testing10aSPRT1 aLinn, RL1 aRock, D A1 aCleary, T A uhttp://www.iacat.org/content/sequential-testing-dichotomous-decisions00566nas a2200109 4500008004100000245011200041210006900153260008500222100001800307700001100325856012000336 1971 eng d00aThe application of item generators for individualizing mathematics testing and instruction (Report 1971/14)0 aapplication of item generators for individualizing mathematics t aPittsburgh PA: University of Pittsburgh Learning Research and Development Center1 aFerguson, R L1 aHsu, T uhttp://www.iacat.org/content/application-item-generators-individualizing-mathematics-testing-and-instruction-report00452nas a2200121 4500008004100000245007200041210006900113300001200182490000700194100001600201700001700217856009600234 1971 eng d00aA comparison of computer-simulated conventional and branching tests0 acomparison of computersimulated conventional and branching tests a125-1360 v311 aWaters, C J1 aBayroff, A G uhttp://www.iacat.org/content/comparison-computer-simulated-conventional-and-branching-tests00521nas a2200097 4500008003900000245011200039210006900151260006400220100001400284856012500298 1971 d00aA comparison of four methods of selecting items for computer-assisted testing (Technical Bulletin STB 72-5)0 acomparison of four methods of selecting items for computerassist aSan Diego: Naval Personnel and Training Research Laboratory1 aBryson, R uhttp://www.iacat.org/content/comparison-four-methods-selecting-items-computer-assisted-testing-technical-bulletin-stb-7200411nas a2200097 4500008004100000245005600041210005600097260005900153100001800212856008300230 1971 eng d00aComputer assistance for individualizing measurement0 aComputer assistance for individualizing measurement aPittsburgh PA: University of Pittsburgh R and D Center1 aFerguson, R L uhttp://www.iacat.org/content/computer-assistance-individualizing-measurement-100378nam a2200097 4500008004100000245004500041210004500086260006100131100001400192856007400206 1971 eng d00aComputerized adaptive sequential testing0 aComputerized adaptive sequential testing aUnpublished doctoral dissertation, University of Chicago1 aWood, R L uhttp://www.iacat.org/content/computerized-adaptive-sequential-testing00403nas a2200097 4500008004100000245005000041210005000091260007400141100001400215856007600229 1971 eng d00aIndividualized testing by Bayesian estimation0 aIndividualized testing by Bayesian estimation aSeattle: University of Washington, Bureau of Testing Project 0171-1771 aUrry, V W uhttp://www.iacat.org/content/individualized-testing-bayesian-estimation00406nas a2200109 4500008004100000245006700041210006300108300001000171490000700181100001800188856009000206 1971 eng d00aA model for computer-assisted criterion-referenced measurement0 amodel for computerassisted criterionreferenced measurement a25-310 v811 aFerguson, R L uhttp://www.iacat.org/content/model-computer-assisted-criterion-referenced-measurement00354nas a2200109 4500008004100000245005000041210004900091300000900140490000700149100001300156856007500169 1971 eng d00aRobbins-Monro procedures for tailored testing0 aRobbinsMonro procedures for tailored testing a3-310 v311 aLord, FM uhttp://www.iacat.org/content/robbins-monro-procedures-tailored-testing00313nas a2200109 4500008004100000245003700041210003200078300001200110490000600122100001300128856006200141 1971 eng d00aThe self-scoring flexilevel test0 aselfscoring flexilevel test a147-1510 v81 aLord, FM uhttp://www.iacat.org/content/self-scoring-flexilevel-test00437nas a2200097 4500008004100000245007500041210006900116260004600185100001300231856009500244 1971 eng d00aTailored testing: An application of stochastic approximation (RM 71-2)0 aTailored testing An application of stochastic approximation RM 7 aPrinceton NJ: Educational Testing Service1 aLord, FM uhttp://www.iacat.org/content/tailored-testing-application-stochastic-approximation-rm-71-200405nas a2200109 4500008004100000245006700041210006600108300001200174490000700186100001300193856008900206 1971 eng d00aTailored testing, an approximation of stochastic approximation0 aTailored testing an approximation of stochastic approximation a707-7110 v661 aLord, FM uhttp://www.iacat.org/content/tailored-testing-approximation-stochastic-approximation00423nas a2200109 4500008004100000245007700041210006900118300001200187490000700199100001300206856009400219 1971 eng d00aA theoretical study of the measurement effectiveness of flexilevel tests0 atheoretical study of the measurement effectiveness of flexilevel a805-8130 v311 aLord, FM uhttp://www.iacat.org/content/theoretical-study-measurement-effectiveness-flexilevel-tests00339nas a2200109 4500008004100000245004500041210004200086300001200128490000700140100001300147856006900160 1971 eng d00aA theoretical study of two-stage testing0 atheoretical study of twostage testing a227-2420 v361 aLord, FM uhttp://www.iacat.org/content/theoretical-study-two-stage-testing00342nas a2200109 4500008004100000245004100041210004100082300001200123490001500135100001500150856006700165 1970 eng d00aAdaptive testing of cognitive skills0 aAdaptive testing of cognitive skills a167-1680 v5 (part 1)1 aWargo, M J uhttp://www.iacat.org/content/adaptive-testing-cognitive-skills00399nas a2200097 4500008004100000245003300041210003300074260012100107100001400228856005900242 1970 eng d00aComments on tailored testing0 aComments on tailored testing aW. H. Holtzman, (Ed.), Computer-assisted instruction, testing, and guidance (pp. 184-197). New York: Harper and Row.1 aGreen, BF uhttp://www.iacat.org/content/comments-tailored-testing00384nas a2200109 4500008004100000245005600041210005600097300000700153490001500160100001800175856008100193 1970 eng d00aComputer assistance for individualizing measurement0 aComputer assistance for individualizing measurement a190 vMarch 19701 aFerguson, R L uhttp://www.iacat.org/content/computer-assistance-individualizing-measurement00438nas a2200097 4500008004100000245005600041210005600097260008600153100001800239856008300257 1970 eng d00aComputer assistance for individualizing measurement0 aComputer assistance for individualizing measurement aPittsburgh PA: University of Pittsburgh, Learning Research and Development Center1 aFerguson, R L uhttp://www.iacat.org/content/computer-assistance-individualizing-measurement-000442nas a2200097 4500008004100000245004600041210004500087260012000132100001800252856007400270 1970 eng d00aIndividually tailored testing: Discussion0 aIndividually tailored testing Discussion aW. H. Holtzman, (Ed.), Computer-assisted instruction, testing, and guidance (pp.198-200). New York: Harper and Row.1 aHoltzman, W H uhttp://www.iacat.org/content/individually-tailored-testing-discussion00396nas a2200097 4500008003900000245006700039210006300106260001900169100001800188856009200206 1970 d00aA model for computer-assisted criterion-referenced measurement0 amodel for computerassisted criterionreferenced measurement aMinneapolis MN1 aFerguson, R L uhttp://www.iacat.org/content/model-computer-assisted-criterion-referenced-measurement-000354nas a2200097 4500008004100000245004700041210003900088260004600127100001300173856007000186 1970 eng d00aThe self-scoring flexilevel test (RB-7043)0 aselfscoring flexilevel test RB7043 aPrinceton NJ: Educational Testing Service1 aLord, FM uhttp://www.iacat.org/content/self-scoring-flexilevel-test-rb-704300622nas a2200121 4500008004100000245017800041210006900219260004700288100001300335700001400348700001600362856012200378 1970 eng d00aSequential testing for dichotomous decisions. College Entrance Examination Board Research and Development Report (RDR 69-70, No 3", and Educational Testing Service RB-70-31)0 aSequential testing for dichotomous decisions College Entrance Ex aPrinceton NJ: Educational Testing Service.1 aLinn, RL1 aRock, D A1 aCleary, T A uhttp://www.iacat.org/content/sequential-testing-dichotomous-decisions-college-entrance-examination-board-research-and00422nas a2200097 4500008004100000245004200041210004200083260011900125100001300244856006700257 1970 eng d00aSome test theory for tailored testing0 aSome test theory for tailored testing aW. H. Holtzman (Ed.), Computer-assisted instruction, testing, and guidance (pp.139-183). New York: Harper and Row.1 aLord, FM uhttp://www.iacat.org/content/some-test-theory-tailored-testing00332nas a2200109 4500008004100000245004000041210004000081300001200121490000700133100001600140856006600156 1969 eng d00aAutomation of psychological testing0 aAutomation of psychological testing a287-2890 v241 aElwood, D L uhttp://www.iacat.org/content/automation-psychological-testing00420nas a2200097 4500008004100000245006800041210006300109260004600172100001400218856009000232 1969 eng d00aA Bayesian approach to tailored testing (Research Report 69-92)0 aBayesian approach to tailored testing Research Report 6992 aPrinceton NJ: Educational Testing Service1 aOwen, R J uhttp://www.iacat.org/content/bayesian-approach-tailored-testing-research-report-69-9200444nas a2200097 4500008004100000245007500041210006900116260004600185100001600231856009900247 1969 eng d00aBayesian methods in psychological testing (Research Bulletin RB-69-31)0 aBayesian methods in psychological testing Research Bulletin RB69 aPrinceton NJ: Educational Testing Service1 aNovick, M R uhttp://www.iacat.org/content/bayesian-methods-psychological-testing-research-bulletin-rb-69-3100516nas a2200097 4500008004100000245007700041210006900118260010900187100001800296856010400314 1969 eng d00aComputer-assisted criterion-referenced measurement (Working Paper No 49)0 aComputerassisted criterionreferenced measurement Working Paper N aPittsburgh PA: University of Pittsburgh, Learning and Research Development Center. (ERIC No. ED 037 089)1 aFerguson, R L uhttp://www.iacat.org/content/computer-assisted-criterion-referenced-measurement-working-paper-no-4900448nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001600215856009500231 1969 eng d00aThe development and evaluation of several programmed testing methods0 adevelopment and evaluation of several programmed testing methods a129-1460 v291 aLinn, RL1 aCleary, T A uhttp://www.iacat.org/content/development-and-evaluation-several-programmed-testing-methods00623nam a2200097 4500008003900000245014200039210006900181260014200250100001800392856011500410 1969 d00aThe development, implementation, and evaluation of a computer-assisted branched test for a program of individually prescribed instruction0 adevelopment implementation and evaluation of a computerassisted  aDoctoral dissertation, University of Pittsburgh. Dissertation Abstracts International, 30-09A, 3856. (University Microfilms No. 70-4530).1 aFerguson, R L uhttp://www.iacat.org/content/development-implementation-and-evaluation-computer-assisted-branched-test-program00313nas a2200109 4500008004100000245003700041210003300078300001200111490000700123100001400130856005900144 1969 eng d00aThe efficacy of tailored testing0 aefficacy of tailored testing a219-2220 v111 aWood, R L uhttp://www.iacat.org/content/efficacy-tailored-testing00392nas a2200133 4500008004100000245004500041210004200086300001200128490000700140100001600147700001300163700001400176856006800190 1969 eng d00aAn exploratory study of programmed tests0 aexploratory study of programmed tests a345-3600 v281 aCleary, T A1 aLinn, RL1 aRock, D A uhttp://www.iacat.org/content/exploratory-study-programmed-tests00335nas a2200085 4500008004100000245005600041210005600097100001400153856008200167 1969 eng d00aIndividualized assessment of differential abilities0 aIndividualized assessment of differential abilities1 aWeiss, DJ uhttp://www.iacat.org/content/individualized-assessment-differential-abilities00462nas a2200097 4500008004100000245005500041210005100096260012100147100001600268856008000284 1969 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aR. C. Atkinson and H. A. Wilson (Eds.), Computer-assisted instruction: A book of readings. New York: Academic Press.1 aHansen, D N uhttp://www.iacat.org/content/investigation-computer-based-science-testing-100309nas a2200085 4500008004100000245004700041210004700088100001700135856007100152 1969 eng d00aPsychometric problems with branching tests0 aPsychometric problems with branching tests1 aBayroff, A G uhttp://www.iacat.org/content/psychometric-problems-branching-tests00334nas a2200097 4500008004100000245003600041210003200077260004600109100001800155856006300173 1969 eng d00aShort tailored tests (RB-69-63)0 aShort tailored tests RB6963 aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/short-tailored-tests-rb-69-6300430nas a2200109 4500008004100000245008500041210006900126300001200195490000700207100001700214856008900231 1969 eng d00aUse of an on-line computer for psychological testing with the up-and-down method0 aUse of an online computer for psychological testing with the upa a207-2110 v241 aKappauf, W E uhttp://www.iacat.org/content/use-line-computer-psychological-testing-and-down-method00386nam a2200121 4500008004100000245003700041210003300078260004600111100001600157700001400173700001400187856006300201 1968 eng d00aComputer-assisted testing (Eds.)0 aComputerassisted testing Eds aPrinceton NJ: Educational Testing Service1 aHarman, H H1 aHelm, C E1 aLoye, D E uhttp://www.iacat.org/content/computer-assisted-testing-eds00537nas a2200121 4500008004100000245009800041210006900139260004600208100001300254700001400267700001600281856011800297 1968 eng d00aThe development and evaluation of several programmed testing methods (Research Bulletin 68-5)0 adevelopment and evaluation of several programmed testing methods aPrinceton NJ: Educational Testing Service1 aLinn, RL1 aRock, D A1 aCleary, T A uhttp://www.iacat.org/content/development-and-evaluation-several-programmed-testing-methods-research-bulletin-68-500411nas a2200109 4500008004100000245005500041210005100096260004500147100001600192700001500208856007800223 1968 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aTallahassee FL: Florida State University1 aHansen, D N1 aSchwarz, G uhttp://www.iacat.org/content/investigation-computer-based-science-testing00439nas a2200109 4500008004100000245005500041210005100096260007100147100001600218700001500234856008000249 1968 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aTallahassee: Institute of Human Learning, Florida State University1 aHansen, D N1 aSchwarz, G uhttp://www.iacat.org/content/investigation-computer-based-science-testing-000470nas a2200109 4500008004100000245010000041210006900141300001200210490000600222100001500228856011700243 1968 eng d00aMethodological determination of the PEST (parameter estimation by sequential testing) procedure0 aMethodological determination of the PEST parameter estimation by a285-2890 v31 aPollack, I uhttp://www.iacat.org/content/methodological-determination-pest-parameter-estimation-sequential-testing-procedure00492nas a2200133 4500008004100000245008400041210006900125300001200194490000600206100001600212700001300228700001400241856010300255 1968 eng d00aReproduction of total test score through the use of sequential programmed tests0 aReproduction of total test score through the use of sequential p a183-1870 v51 aCleary, T A1 aLinn, RL1 aRock, D A uhttp://www.iacat.org/content/reproduction-total-test-score-through-use-sequential-programmed-tests00510nas a2200109 4500008004100000245007400041210006900115260008800184100001700272700001600289856009500305 1967 eng d00aAn exploratory study of branching tests (Technical Research Note 188)0 aexploratory study of branching tests Technical Research Note 188 aWashington DC: US Army Behavioral Science Research Laboratory. (NTIS No. AD 655263)1 aBayroff, A G1 aSeeley, L C uhttp://www.iacat.org/content/exploratory-study-branching-tests-technical-research-note-18800436nas a2200097 4500008004100000245005200041210005200093260010200145100001800247856007300265 1966 eng d00aNew light on test strategy from decision theory0 aNew light on test strategy from decision theory aA. Anastasi (Ed.). Testing problems in perspective. Washington DC: American Council on Education.1 aCronbach, L J uhttp://www.iacat.org/content/new-light-test-strategy-decision-theory00511nas a2200097 4500008004100000245008600041210006900127260010200196100001700298856009800315 1966 eng d00aProgrammed testing in the examinations of the National Board of Medical Examiners0 aProgrammed testing in the examinations of the National Board of  aA. Anastasi (Ed.), Testing problems in perspective. Washington DC: American Council on Education.1 aHubbard, J P uhttp://www.iacat.org/content/programmed-testing-examinations-national-board-medical-examiners00370nas a2200121 4500008004100000245004400041210004400085300001200129490000700141100001900148700001400167856006700181 1965 eng d00aAdaptive testing in an older population0 aAdaptive testing in an older population a193-1980 v601 aGreenwood, D I1 aTaylor, C uhttp://www.iacat.org/content/adaptive-testing-older-population00381nas a2200097 4500008003900000245004800039210004800087260005900135100001700194856007200211 1964 d00aFeasibility of a programmed testing machine0 aFeasibility of a programmed testing machine aUS Army Personnel Research Office Research Study 64-3.1 aBayroff, A G uhttp://www.iacat.org/content/feasibility-programmed-testing-machine00418nas a2200097 4500008004100000245005600041210005600097260006900153100001600222856008200238 1964 eng d00aPreliminary evaluation of simulated branching tests0 aPreliminary evaluation of simulated branching tests aU.S. Army Personnel Research Office Technical Research Note 140.1 aWaters, C J uhttp://www.iacat.org/content/preliminary-evaluation-simulated-branching-tests00397nam a2200097 4500008004100000245005400041210005100095260006500146100001800211856007000229 1962 eng d00aAn evaluation of the sequential method of testing0 aevaluation of the sequential method of testing aUnpublished doctoral dissertation, Michigan State University1 aPaterson, J J uhttp://www.iacat.org/content/evaluation-sequential-method-testing00451nas a2200121 4500008004100000245004800041210004800089260007000137100001600207700001600223700001800239856007200257 1962 eng d00aExploratory study of a sequential item test0 aExploratory study of a sequential item test aU.S. Army Personnel Research Office, Technical Research Note 129.1 aSeeley, L C1 aMorton, M A1 aAnderson, A A uhttp://www.iacat.org/content/exploratory-study-sequential-item-test00494nam a2200097 4500008004100000245010000041210006900141260006100210100001900271856010600290 1961 eng d00aAn analysis of the application of utility theory to the development of two-stage testing models0 aanalysis of the application of utility theory to the development aUnpublished doctoral dissertation, University of Buffalo1 aRosenbach, J H uhttp://www.iacat.org/content/analysis-application-utility-theory-development-two-stage-testing-models00541nas a2200121 4500008004100000245008400041210006900125260006900194100001700263700001600280700001800296856010500314 1960 eng d00aConstruction of an experimental sequential item test (Research Memorandum 60-1)0 aConstruction of an experimental sequential item test Research Me aWashington DC: Personnel Research Branch, Department of the Army1 aBayroff, A G1 aThomas, J J1 aAnderson, A A uhttp://www.iacat.org/content/construction-experimental-sequential-item-test-research-memorandum-60-100401nas a2200097 4500008004100000245004800041210004800089260007900137100001700216856007000233 1959 eng d00aProgress report on the sequential item test0 aProgress report on the sequential item test aEast Lansing MI: Michigan State University, Bureau of Educational Research1 aKrathwohl, D uhttp://www.iacat.org/content/progress-report-sequential-item-test00507nas a2200097 4500008004100000245011400041210006900155260004600224100001600270856012300286 1958 eng d00aThe multi-level experiment: A study of a two-level test system for the College Board Scholastic Aptitude Test0 amultilevel experiment A study of a twolevel test system for the  aPrinceton NJ: Educational Testing Service1 aAngoff, E M uhttp://www.iacat.org/content/multi-level-experiment-study-two-level-test-system-college-board-scholastic-aptitude-test00320nas a2200121 4500008004100000245002900041210002500070300000800095490000600103100001900109700001600128856005400144 1956 eng d00aThe sequential item test0 asequential item test a4190 v21 aKrathwohl, D R1 aHuyser, R J uhttp://www.iacat.org/content/sequential-item-test00436nas a2200109 4500008004100000245008600041210006900127300000900196490000700205100001600212856009800228 1953 eng d00a An empirical study of the applicability of sequential analysis to item selection0 aempirical study of the applicability of sequential analysis to i a3-130 v131 aAnastasi, A uhttp://www.iacat.org/content/empirical-study-applicability-sequential-analysis-item-selection00498nas a2200109 4500008004100000245011900041210006900160300001200229490000700241100001600248856012400264 1950 eng d00a Sequential analysis with more than two alternative hypotheses, and its relation to discriminant function analysis0 aSequential analysis with more than two alternative hypotheses an a137-1440 v121 aArmitage, P uhttp://www.iacat.org/content/sequential-analysis-more-two-alternative-hypotheses-and-its-relation-discriminant-function00478nas a2200109 4500008004100000245010500041210006900146300001200215490000700227100001600234856011800250 1950 eng d00aSome empirical aspects of the sequential analysis technique as applied to an achievement examination0 aSome empirical aspects of the sequential analysis technique as a a195-2070 v181 aMoonan, W J uhttp://www.iacat.org/content/some-empirical-aspects-sequential-analysis-technique-applied-achievement-examination00445nas a2200109 4500008004100000245008900041210006900130300001100199490000700210100001400217856010400231 1947 eng d00aA clinical study of consecutive and adaptive testing with the revised Stanford-Binet0 aclinical study of consecutive and adaptive testing with the revi a93-1030 v111 aHutt, M L uhttp://www.iacat.org/content/clinical-study-consecutive-and-adaptive-testing-revised-stanford-binet00389nas a2200109 4500008004100000245006200041210005900103300001200162490000700174100001600181856008200197 1946 eng d00aAn application of sequential sampling to testing students0 aapplication of sequential sampling to testing students a547-5560 v411 aCowden, D J uhttp://www.iacat.org/content/application-sequential-sampling-testing-students00453nam a2200109 4500008004100000245008000041210006900121260003700190100001300227700001300240856009000253 1915 eng d00aA method of measuring the development of the intelligence of young children0 amethod of measuring the development of the intelligence of young aChicago: Chicago Medical Book Co1 aBinet, A1 aSimon, T uhttp://www.iacat.org/content/method-measuring-development-intelligence-young-children00396nas a2200121 4500008004400000245005300044210005300097300000900150490000700159100001300166700001300179856008200192 1908 Frendh 00aLe development de lintelligence chez les enfants0 aLe development de lintelligence chez les enfants a1-940 v141 aBinet, A1 aSimon, T uhttp://www.iacat.org/content/le-development-de-lintelligence-chez-les-enfants00464nas a2200121 4500008004400000245007500044210006900119300001200188490000700200100001300207700001800220856010400238 1905 Frendh 00aMthode nouvelle pour le diagnostic du niveau intellectuel des anormaux0 aMthode nouvelle pour le diagnostic du niveau intellectuel des an a191-2440 v111 aBinet, A1 aSimon, Th., A uhttp://www.iacat.org/content/mthode-nouvelle-pour-le-diagnostic-du-niveau-intellectuel-des-anormaux00487nas a2200133 4500008004000000245006900040210006500109260006300174100001200237700001500249700001500264700001600279856005800295 0 engd00aMicrocomputer network for computer­ized adaptive testing (CAT) 0 aMicrocomputer network for computer ized adaptive testing CAT bSan Diego: Navy Personnel Research and Development Center.1 aQuan, B1 aPark, T.A.1 aSandahl, G1 aWolfe, J.H. uhttps://apps.dtic.mil/dtic/tr/fulltext/u2/a140256.pdf