00541nas 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-testing01445nas 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.1220301674nas 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.1219306631nas 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.
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 aCalibration 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
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 aUnlike 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 aParameter 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.
10aCAT10aDIF10aParameter Drift10aParameter Recovery1 aThompson, Nathan1 aStoeger, Jordan uhttps://drive.google.com/open?id=1F7HCZWD28Q97sCKFIJB0Yps0H66NPeKq00925nas 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.abstract01791nas 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-testing01835nas 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 aComputerized 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 aThis 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.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-testing01355nas 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 aSuccessful 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 aIn 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.abstract02037nas 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 aThe 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-ability00605nas 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-testing00531nas 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-000483nam 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-physical01798nas 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 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.
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-item01613nas 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 aThe 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-research00463nas 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-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-setting00527nas 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-using00382nas 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-000386nas 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-bundles02777nas 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-model00528nas 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-tests00478nas 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-000624nas 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-testing00547nas 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-001310nas 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-items00392nas 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-tests00525nas 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-analyses00480nas 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-000478nas 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-algorithm00407nas 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-methods00469nas 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-mcat00551nas 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-002101nas 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-using00548nas 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-analysis00589nas 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-100571nas 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-computerized00587nas 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-001432nas 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-time01684nas 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-adaptive00574nas 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-000621nas 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-computerized01753nas 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-testing00495nas 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-cat00482nas 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-testing00466nas 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-procedures00517nas 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-uirt00592nas 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-vs00552nas 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-battery00355nas 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-cat00478nas 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-tests00477nas 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-001351nas 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-tests00533nas 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-tests01335nas 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-concepts00459nas 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-selection00511nas 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-001702nas 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-measurement00470nas 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-200395nas 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-testing00557nas 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-college00620nas 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-project00433nas 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-tests00489nas 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-tests00396nas 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-82-100526nam a2200097 4500008004100000245011300041210006900154260006300223100001700286856012500303 1983 eng d00aEffects of item parameter error and other factors on trait estimation in latent trait based adaptive testing0 aEffects of item parameter error and other factors on trait estim aUnpublished doctoral dissertation, University of Minnesota1 aMattson, J D uhttp://www.iacat.org/content/effects-item-parameter-error-and-other-factors-trait-estimation-latent-trait-based-adaptive00571nas a2200109 4500008004100000245013900041210006900180260005100249100001800300700001700318856012600335 1983 eng d00aAn evaluation of one- and three-parameter logistic tailored testing procedures for use with small item pools (Research Report ONR83-1)0 aevaluation of one and threeparameter logistic tailored testing p aIowa City IA: American College Testing Program1 aMcKinley, R L1 aReckase, M D uhttp://www.iacat.org/content/evaluation-one-and-three-parameter-logistic-tailored-testing-procedures-use-small-item-pools00515nam 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-testing00616nas 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-administration00597nas 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-000591nas 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-400468nas 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-testing00440nas 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-procedure00471nas 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-testing00578nas 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-human00467nam 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-model00389nas 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-000535nas 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-73-400313nas 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-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-18800397nam 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-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-selection