01538nas a2200169 4500008004200000245012100042210006900163520094900232100001801181700001701199700002501216700001801241700002201259700002201281700002001303856004501323 In Press d 00aDevelopment of a Computerized Adaptive Test for Anxiety Based on the Dutch–Flemish Version of the PROMIS Item Bank0 aDevelopment of a Computerized Adaptive Test for Anxiety Based on3 aWe used the Dutch–Flemish version of the USA PROMIS adult V1.0 item bank for Anxiety as input for developing a computerized adaptive test (CAT) to measure the entire latent anxiety continuum. First, psychometric analysis of a combined clinical and general population sample (N = 2,010) showed that the 29-item bank has psychometric properties that are required for a CAT administration. Second, a post hoc CAT simulation showed efficient and highly precise measurement, with an average number of 8.64 items for the clinical sample, and 9.48 items for the general population sample. Furthermore, the accuracy of our CAT version was highly similar to that of the full item bank administration, both in final score estimates and in distinguishing clinical subjects from persons without a mental health disorder. We discuss the future directions and limitations of CAT development with the Dutch–Flemish version of the PROMIS Anxiety item bank.1 aFlens, Gerard1 aSmits, Niels1 aTerwee, Caroline, B.1 aDekker, Joost1 aHuijbrechts, Irma1 aSpinhoven, Philip1 ade Beurs, Edwin uhttps://doi.org/10.1177/107319111774674202064nas a2200157 4500008003900000245009100039210006900130300001200199490000700211520157600218100001501794700001901809700001401828700001901842856004501861 2020 d00aStratified Item Selection Methods in Cognitive Diagnosis Computerized Adaptive Testing0 aStratified Item Selection Methods in Cognitive Diagnosis Compute a346-3610 v443 aCognitive diagnostic computerized adaptive testing (CD-CAT) aims to obtain more useful diagnostic information by taking advantages of computerized adaptive testing (CAT). Cognitive diagnosis models (CDMs) have been developed to classify examinees into the correct proficiency classes so as to get more efficient remediation, whereas CAT tailors optimal items to the examinee’s mastery profile. The item selection method is the key factor of the CD-CAT procedure. In recent years, a large number of parametric/nonparametric item selection methods have been proposed. In this article, the authors proposed a series of stratified item selection methods in CD-CAT, which are combined with posterior-weighted Kullback–Leibler (PWKL), nonparametric item selection (NPS), and weighted nonparametric item selection (WNPS) methods, and named S-PWKL, S-NPS, and S-WNPS, respectively. Two different types of stratification indices were used: original versus novel. The performances of the proposed item selection methods were evaluated via simulation studies and compared with the PWKL, NPS, and WNPS methods without stratification. Manipulated conditions included calibration sample size, item quality, number of attributes, number of strata, and data generation models. Results indicated that the S-WNPS and S-NPS methods performed similarly, and both outperformed the S-PWKL method. And item selection methods with novel stratification indices performed slightly better than the ones with original stratification indices, and those without stratification performed the worst.1 aYang, Jing1 aChang, Hua-Hua1 aTao, Jian1 aShi, Ningzhong uhttps://doi.org/10.1177/014662161989378301943nas a2200145 4500008003900000245007700039210006900116300001200185490000700197520148100204100002101685700002301706700002301729856004501752 2019 d00aComputerized Adaptive Testing for Cognitively Based Multiple-Choice Data0 aComputerized Adaptive Testing for Cognitively Based MultipleChoi a388-4010 v433 aCognitive diagnosis models (CDMs) are latent class models that hold great promise for providing diagnostic information about student knowledge profiles. The increasing use of computers in classrooms enhances the advantages of CDMs for more efficient diagnostic testing by using adaptive algorithms, referred to as cognitive diagnosis computerized adaptive testing (CD-CAT). When multiple-choice items are involved, CD-CAT can be further improved by using polytomous scoring (i.e., considering the specific options students choose), instead of dichotomous scoring (i.e., marking answers as either right or wrong). In this study, the authors propose and evaluate the performance of the Jensen–Shannon divergence (JSD) index as an item selection method for the multiple-choice deterministic inputs, noisy “and” gate (MC-DINA) model. Attribute classification accuracy and item usage are evaluated under different conditions of item quality and test termination rule. The proposed approach is compared with the random selection method and an approximate approach based on dichotomized responses. The results show that under the MC-DINA model, JSD improves the attribute classification accuracy significantly by considering the information from distractors, even with a very short test length. This result has important implications in practical classroom settings as it can allow for dramatically reduced testing times, thus resulting in more targeted learning opportunities.1 aYigit, Hulya, D.1 aSorrel, Miguel, A.1 ade la Torre, Jimmy uhttps://doi.org/10.1177/014662161879866501544nas a2200145 4500008003900000245009800039210006900137300001200206490000700218520104000225100002901265700002501294700003401319856004501353 2019 d00aImputation Methods to Deal With Missing Responses in Computerized Adaptive Multistage Testing0 aImputation Methods to Deal With Missing Responses in Computerize a495-5110 v793 aRouting examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated multiple missing data methods in computerized adaptive multistage testing, including two imputation techniques, the use of full information maximum likelihood and the use of scoring missing data as incorrect. These methods were examined under the missing completely at random, missing at random, and missing not at random frameworks, as well as other testing conditions. Comparisons were made to baseline conditions where no missing data were present. The results showed that imputation and the full information maximum likelihood methods outperformed incorrect scoring methods in terms of average bias, average root mean square error, and correlation between estimated and true thetas.1 aCetin-Berber, Dee, Duygu1 aSari, Halil, Ibrahim1 aHuggins-Manley, Anne, Corinne uhttps://doi.org/10.1177/001316441880553201927nas a2200157 4500008003900000245010900039210006900148300001200217490000700229520138500236100002201621700002001643700002201663700002101685856006301706 2019 d00aRouting Strategies and Optimizing Design for Multistage Testing in International Large-Scale Assessments0 aRouting Strategies and Optimizing Design for Multistage Testing  a192-2130 v563 aAbstract This study investigates the effect of several design and administration choices on item exposure and person/item parameter recovery under a multistage test (MST) design. In a simulation study, we examine whether number-correct (NC) or item response theory (IRT) methods are differentially effective at routing students to the correct next stage(s) and whether routing choices (optimal versus suboptimal routing) have an impact on achievement precision. Additionally, we examine the impact of testlet length on both person and item recovery. Overall, our results suggest that no single approach works best across the studied conditions. With respect to the mean person parameter recovery, IRT scoring (via either Fisher information or preliminary EAP estimates) outperformed classical NC methods, although differences in bias and root mean squared error were generally small. Item exposure rates were found to be more evenly distributed when suboptimal routing methods were used, and item recovery (both difficulty and discrimination) was most precisely observed for items with moderate difficulties. Based on the results of the simulation study, we draw conclusions and discuss implications for practice in the context of international large-scale assessments that recently introduced adaptive assessment in the form of MST. Future research directions are also discussed.1 aSvetina, Dubravka1 aLiaw, Yuan-Ling1 aRutkowski, Leslie1 aRutkowski, David uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1220600444nas a2200145 4500008004500000245005100045210005100096260001200147300001000159490000600169100002200175700001800197700002300215856006000238 2018 Engldsh 00aImplementing Three CATs Within Eighteen Months0 aImplementing Three CATs Within Eighteen Months c09/2018 a38-550 v61 aSpoden, Christian1 aFrey, Andreas1 aBernhardt, Raphael uhttp://iacat.org/jcat/index.php/jcat/article/view/70/3300949nas a2200169 4500008003900000022001400039245011500053210006900168260000800237300001600245490000700261520040300268100001700671700002400688700002100712856004600733 2018 d a1573-264900aSome recommendations for developing multidimensional computerized adaptive tests for patient-reported outcomes0 aSome recommendations for developing multidimensional computerize cApr a1055–10630 v273 aMultidimensional item response theory and computerized adaptive testing (CAT) are increasingly used in mental health, quality of life (QoL), and patient-reported outcome measurement. Although multidimensional assessment techniques hold promises, they are more challenging in their application than unidimensional ones. The authors comment on minimal standards when developing multidimensional CATs.1 aSmits, Niels1 aPaap, Muirne, C. S.1 aBöhnke, Jan, R. uhttps://doi.org/10.1007/s11136-018-1821-801986nas a2200133 4500008003900000245006600039210006400105300001200169490000700181520157400188100002501762700002001787856004501807 2018 d00aWhat Information Works Best?: A Comparison of Routing Methods0 aWhat Information Works Best A Comparison of Routing Methods a499-5150 v423 aThere are many item selection methods proposed for computerized adaptive testing (CAT) applications. However, not all of them have been used in computerized multistage testing (ca-MST). This study uses some item selection methods as a routing method in ca-MST framework. These are maximum Fisher information (MFI), maximum likelihood weighted information (MLWI), maximum posterior weighted information (MPWI), Kullback–Leibler (KL), and posterior Kullback–Leibler (KLP). The main purpose of this study is to examine the performance of these methods when they are used as a routing method in ca-MST applications. These five information methods under four ca-MST panel designs and two test lengths (30 items and 60 items) were tested using the parameters of a real item bank. Results were evaluated with overall findings (mean bias, root mean square error, correlation between true and estimated thetas, and module exposure rates) and conditional findings (conditional absolute bias, standard error of measurement, and root mean square error). It was found that test length affected the outcomes much more than other study conditions. Under 30-item conditions, 1-3 designs outperformed other panel designs. Under 60-item conditions, 1-3-3 designs were better than other panel designs. Each routing method performed well under particular conditions; there was no clear best method in the studied conditions. The recommendations for routing methods in any particular condition were provided for researchers and practitioners as well as the limitations of these results.1 aSari, Halil, Ibrahim1 aRaborn, Anthony uhttps://doi.org/10.1177/014662161775299005518nas a2200193 4500008004100000245009000041210006900131260005500200520480200255653002305057653001905080653002105099653002605120100002205146700002005168700001605188700001905204856010105223 2017 eng d00aAdaptive Item and Feedback Selection in Personalized Learning with a Network Approach0 aAdaptive Item and Feedback Selection in Personalized Learning wi aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

References

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

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

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

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

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

Session Video

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

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

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

Session Video

10aCAT10aDiagnostic tests10aEducation1 aSchouwstra, Sanneke uhttp://www.iacat.org/adaptivity-diagnostic-educational-test-001537nas a2200181 4500008003900000245006700039210006500106300001200171490000700183520099700190100002001187700001801207700002101225700002201246700002201268700002001290856004501310 2017 d00aATS-PD: An Adaptive Testing System for Psychological Disorders0 aATSPD An Adaptive Testing System for Psychological Disorders a792-8150 v773 aThe clinical assessment of mental disorders can be a time-consuming and error-prone procedure, consisting of a sequence of diagnostic hypothesis formulation and testing aimed at restricting the set of plausible diagnoses for the patient. In this article, we propose a novel computerized system for the adaptive testing of psychological disorders. The proposed system combines a mathematical representation of psychological disorders, known as the “formal psychological assessment,” with an algorithm designed for the adaptive assessment of an individual’s knowledge. The assessment algorithm is extended and adapted to the new application domain. Testing the system on a real sample of 4,324 healthy individuals, screened for obsessive-compulsive disorder, we demonstrate the system’s ability to support clinical testing, both by identifying the correct critical areas for each individual and by reducing the number of posed questions with respect to a standard written questionnaire.1 aDonadello, Ivan1 aSpoto, Andrea1 aSambo, Francesco1 aBadaloni, Silvana1 aGranziol, Umberto1 aVidotto, Giulio uhttps://doi.org/10.1177/001316441665218801722nas a2200133 4500008004100000245009200041210006900133260005500202520120200257653000801459653001601467100001801483856008701501 2017 eng d00aA Comparison of Three Empirical Reliability Estimates for Computerized Adaptive Testing0 aComparison of Three Empirical Reliability Estimates for Computer aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

Session Video 

10aCAT10aReliability1 aSeo, Dong, Gi uhttps://drive.google.com/file/d/1gXgH-epPIWJiE0LxMHGiCAxZZAwy4dAH/view?usp=sharing02166nas a2200157 4500008003900000245007600039210006900115300001200184490000700196520167900203100002001882700001801902700001801920700002501938856004501963 2017 d00aIs a Computerized Adaptive Test More Motivating Than a Fixed-Item Test?0 aComputerized Adaptive Test More Motivating Than a FixedItem Test a495-5110 v413 aComputer adaptive tests provide important measurement advantages over traditional fixed-item tests, but research on the psychological reactions of test takers to adaptive tests is lacking. In particular, it has been suggested that test-taker engagement, and possibly test performance as a consequence, could benefit from the control that adaptive tests have on the number of test items examinees answer correctly. However, previous research on this issue found little support for this possibility. This study expands on previous research by examining this issue in the context of a mathematical ability assessment and by considering the possible effect of immediate feedback of response correctness on test engagement, test anxiety, time on task, and test performance. Middle school students completed a mathematics assessment under one of three test type conditions (fixed, adaptive, or easier adaptive) and either with or without immediate feedback about the correctness of responses. Results showed little evidence for test type effects. The easier adaptive test resulted in higher engagement and lower anxiety than either the adaptive or fixed-item tests; however, no significant differences in performance were found across test types, although performance was significantly higher across all test types when students received immediate feedback. In addition, these effects were not related to ability level, as measured by the state assessment achievement levels. The possibility that test experiences in adaptive tests may not in practice be significantly different than in fixed-item tests is raised and discussed to explain the results of this and previous studies.1 aLing, Guangming1 aAttali, Yigal1 aFinn, Bridgid1 aStone, Elizabeth, A. uhttps://doi.org/10.1177/014662161770755601506nas a2200133 4500008004100000245006000041210005900101260005500160520103000215653001501245653002001260100002101280856007101301 2017 eng d00aConcerto 5 Open Source CAT Platform: From Code to Nodes0 aConcerto 5 Open Source CAT Platform From Code to Nodes aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

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

Session Video

10aConcerto 510aOpen Source CAT1 aStillwell, David uhttps://drive.google.com/open?id=11eu1KKILQEoK5c-CYO1P1AiJgiQxX0E001568nas a2200181 4500008003900000245011800039210006900157300001100226490000700237520097700244100001801221700001701239700002501256700001801281700002201299700002001321856004501341 2017 d00aDevelopment of a Computer Adaptive Test for Depression Based on the Dutch-Flemish Version of the PROMIS Item Bank0 aDevelopment of a Computer Adaptive Test for Depression Based on  a79-1050 v403 aWe developed a Dutch-Flemish version of the patient-reported outcomes measurement information system (PROMIS) adult V1.0 item bank for depression as input for computerized adaptive testing (CAT). As item bank, we used the Dutch-Flemish translation of the original PROMIS item bank (28 items) and additionally translated 28 U.S. depression items that failed to make the final U.S. item bank. Through psychometric analysis of a combined clinical and general population sample (N = 2,010), 8 added items were removed. With the final item bank, we performed several CAT simulations to assess the efficiency of the extended (48 items) and the original item bank (28 items), using various stopping rules. Both item banks resulted in highly efficient and precise measurement of depression and showed high similarity between the CAT simulation scores and the full item bank scores. We discuss the implications of using each item bank and stopping rule for further CAT development.1 aFlens, Gerard1 aSmits, Niels1 aTerwee, Caroline, B.1 aDekker, Joost1 aHuijbrechts, Irma1 ade Beurs, Edwin uhttps://doi.org/10.1177/016327871668416802133nas a2200169 4500008004100000245006700041210006500108260005500173520156400228653000801792653000801800653002001808653002301828100002101851700002001872856007101892 2017 eng d00aEvaluation of Parameter Recovery, Drift, and DIF with CAT Data0 aEvaluation of Parameter Recovery Drift and DIF with CAT Data aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

Session Video

10aCAT10aDIF10aParameter Drift10aParameter Recovery1 aThompson, Nathan1 aStoeger, Jordan uhttps://drive.google.com/open?id=1F7HCZWD28Q97sCKFIJB0Yps0H66NPeKq03463nas a2200145 4500008004100000245004500041210004500086260005500131520301500186653000803201653001803209653001603227100001403243856006003257 2017 eng d00aItem Response Time on Task Effect in CAT0 aItem Response Time on Task Effect in CAT aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

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

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

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

Session Video

10aCAT10aResponse time10aTask effect1 aShi, Yang uhttp://www.iacat.org/item-response-time-task-effect-cat03876nas a2200193 4500008004100000245007700041210006900118260005500187520320800242653000803450653002103458653001603479100002003495700001803515700002003533700003803553700002003591856007103611 2017 eng d00aMulti-stage Testing for a Multi-disciplined End-of primary-school Test 0 aMultistage Testing for a Multidisciplined Endof primaryschool Te aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

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

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

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

Session Video 1

Session Video 2

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

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

Session Video

10aCAT10achallenges10ainnovative applications1 aWang, Chun1 aWeiss, David, J.1 aZhang, Xue1 aTao, Jian1 aHe, Yinhong1 aChen, Ping1 aWang, Shiyu1 aZhang, Susu1 aLin, Haiyan1 aGao, Xiaohong1 aChang, Hua-Hua1 aShang, Zhuoran uhttps://drive.google.com/open?id=1Wvgxw7in_QCq_F7kzID6zCZuVXWcFDPa03772nas a2200145 4500008004100000245007300041210006900114260005500183520325500238653000803493653002203501653001803523100001403541856007103555 2017 eng d00aResponse Time and Response Accuracy in Computerized Adaptive Testing0 aResponse Time and Response Accuracy in Computerized Adaptive Tes aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

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

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

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

Session Video

10aCAT10aresponse accuracy10aResponse time1 aShi, Yang uhttps://drive.google.com/open?id=1yYP01bzGrKvJnfLwepcAoQQ2F4TdSvZ201840nas a2200145 4500008004100000245010900041210006900150260005500219520128100274100001501555700001401570700001901584700002001603856007101623 2017 eng d00aA Simulation Study to Compare Classification Method in Cognitive Diagnosis Computerized Adaptive Testing0 aSimulation Study to Compare Classification Method in Cognitive D aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

References

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

Session Video

1 aYang, Jing1 aTao, Jian1 aChang, Hua-Hua1 aShi, Ning-Zhong uhttps://drive.google.com/open?id=1jCL3fPZLgzIdwvEk20D-FliZ15OTUtpr04519nas a2200181 4500008004100000245010800041210006900149260005500218520381200273653000804085653002404093653002604117100001604143700001204159700001604171700002004187856013004207 2017 eng d00aUsing Computerized Adaptive Testing to Detect Students’ Misconceptions: Exploration of Item Selection0 aUsing Computerized Adaptive Testing to Detect Students Misconcep aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

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

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

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

References

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

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

Session Video

10aCAT10aincorrect answering10aStudent Misconception1 aShen, Yawei1 aBao, Yu1 aWang, Shiyu1 aBradshaw, Laine uhttp://www.iacat.org/using-computerized-adaptive-testing-detect-students%E2%80%99-misconceptions-exploration-item-selection-001793nas a2200121 4500008003900000245010500039210006900144300001200213490000700225520137100232100001501603856005301618 2016 d00aA Comparison of Constrained Item Selection Methods in Multidimensional Computerized Adaptive Testing0 aComparison of Constrained Item Selection Methods in Multidimensi a346-3600 v403 aThe construction of assessments in computerized adaptive testing (CAT) usually involves fulfilling a large number of statistical and non-statistical constraints to meet test specifications. To improve measurement precision and test validity, the multidimensional priority index (MPI) and the modified MPI (MMPI) can be used to monitor many constraints simultaneously under a between-item and a within-item multidimensional framework, respectively. As both item selection methods can be implemented easily and computed efficiently, they are important and useful for operational CATs; however, no thorough simulation study has compared the performance of these two item selection methods under two different item bank structures. The purpose of this study was to investigate the efficiency of the MMPI and the MPI item selection methods under the between-item and within-item multidimensional CAT through simulations. The MMPI and the MPI item selection methods yielded similar performance in measurement precision for both multidimensional pools and yielded similar performance in exposure control and constraint management for the between-item multidimensional pool. For the within-item multidimensional pool, the MPI method yielded slightly better performance in exposure control but yielded slightly worse performance in constraint management than the MMPI method.1 aSu, Ya-Hui uhttp://apm.sagepub.com/content/40/5/346.abstract00925nas a2200133 4500008003900000022001400039245012600053210006900179300001600248490000700264520045700271100001700728856004600745 2016 d a1573-264900aOn the effect of adding clinical samples to validation studies of patient-reported outcome item banks: a simulation study0 aeffect of adding clinical samples to validation studies of patie a1635–16440 v253 aTo increase the precision of estimated item parameters of item response theory models for patient-reported outcomes, general population samples are often enriched with samples of clinical respondents. Calibration studies provide little information on how this sampling scheme is incorporated into model estimation. In a small simulation study the impact of ignoring the oversampling of clinical respondents on item and person parameters is illustrated.1 aSmits, Niels uhttps://doi.org/10.1007/s11136-015-1199-901723nas a2200145 4500008003900000245015500039210006900194300001000263490000700273520118100280100001701461700002701478700002001505856005201525 2016 d00aStochastic Curtailment of Questionnaires for Three-Level Classification: Shortening the CES-D for Assessing Low, Moderate, and High Risk of Depression0 aStochastic Curtailment of Questionnaires for ThreeLevel Classifi a22-360 v403 aIn clinical assessment, efficient screeners are needed to ensure low respondent burden. In this article, Stochastic Curtailment (SC), a method for efficient computerized testing for classification into two classes for observable outcomes, was extended to three classes. In a post hoc simulation study using the item scores on the Center for Epidemiologic Studies–Depression Scale (CES-D) of a large sample, three versions of SC, SC via Empirical Proportions (SC-EP), SC via Simple Ordinal Regression (SC-SOR), and SC via Multiple Ordinal Regression (SC-MOR) were compared at both respondent burden and classification accuracy. All methods were applied under the regular item order of the CES-D and under an ordering that was optimal in terms of the predictive power of the items. Under the regular item ordering, the three methods were equally accurate, but SC-SOR and SC-MOR needed less items. Under the optimal ordering, additional gains in efficiency were found, but SC-MOR suffered from capitalization on chance substantially. It was concluded that SC-SOR is an efficient and accurate method for clinical screening. Strengths and weaknesses of the methods are discussed.1 aSmits, Niels1 aFinkelman, Matthew, D.1 aKelderman, Henk uhttp://apm.sagepub.com/content/40/1/22.abstract01699nas a2200145 4500008003900000245009300039210006900132490000700201520118000208100001301388700001901401700001501420700001101435856010701446 2016 d00aUsing Response Time to Detect Item Preknowledge in Computer?Based Licensure Examinations0 aUsing Response Time to Detect Item Preknowledge in ComputerBased0 v353 aThis article addresses the issue of how to detect item preknowledge using item response time data in two computer-based large-scale licensure examinations. Item preknowledge is indicated by an unexpected short response time and a correct response. Two samples were used for detecting item preknowledge for each examination. The first sample was from the early stage of the operational test and was used for item calibration. The second sample was from the late stage of the operational test, which may feature item preknowledge. The purpose of this research was to explore whether there was evidence of item preknowledge and compromised items in the second sample using the parameters estimated from the first sample. The results showed that for one nonadaptive operational examination, two items (of 111) were potentially exposed, and two candidates (of 1,172) showed some indications of preknowledge on multiple items. For another licensure examination that featured computerized adaptive testing, there was no indication of item preknowledge or compromised items. Implications for detected aberrant examinees and compromised items are discussed in the article.1 aH., Qian1 aStaniewska, D.1 aReckase, M1 aWoo, A uhttp://www.iacat.org/using-response-time-detect-item-preknowledge-computerbased-licensure-examinations01559nas a2200169 4500008003900000022001400039245007700053210006900130300001300199490000700212520105800219100002101277700001401298700001901312700001701331856004101348 2015 d a1745-398400aAssessing Individual-Level Impact of Interruptions During Online Testing0 aAssessing IndividualLevel Impact of Interruptions During Online  a80–1050 v523 aWith an increase in the number of online tests, the number of interruptions during testing due to unexpected technical issues seems to be on the rise. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. Researchers such as Hill and Sinharay et al. examined the impact of interruptions at an aggregate level. However, there is a lack of research on the assessment of impact of interruptions at an individual level. We attempt to fill that void. We suggest four methodological approaches, primarily based on statistical hypothesis testing, linear regression, and item response theory, which can provide evidence on the individual-level impact of interruptions. We perform a realistic simulation study to compare the Type I error rate and power of the suggested approaches. We then apply the approaches to data from the 2013 Indiana Statewide Testing for Educational Progress-Plus (ISTEP+) test that experienced interruptions.1 aSinharay, Sandip1 aWan, Ping1 aChoi, Seung, W1 aKim, Dong-In uhttp://dx.doi.org/10.1111/jedm.1206401780nas a2200145 4500008003900000245008400039210006900123300001200192490000700204520131700211100001601528700002301544700001401567856005301581 2015 d00aa-Stratified Computerized Adaptive Testing in the Presence of Calibration Error0 aaStratified Computerized Adaptive Testing in the Presence of Cal a260-2830 v753 aa-Stratified computerized adaptive testing with b-blocking (AST), as an alternative to the widely used maximum Fisher information (MFI) item selection method, can effectively balance item pool usage while providing accurate latent trait estimates in computerized adaptive testing (CAT). However, previous comparisons of these methods have treated item parameter estimates as if they are the true population parameter values. Consequently, capitalization on chance may occur. In this article, we examined the performance of the AST method under more realistic conditions where item parameter estimates instead of true parameter values are used in the CAT. Its performance was compared against that of the MFI method when the latter is used in conjunction with Sympson–Hetter or randomesque exposure control. Results indicate that the MFI method, even when combined with exposure control, is susceptible to capitalization on chance. This is particularly true when the calibration sample size is small. On the other hand, AST is more robust to capitalization on chance. Consistent with previous investigations using true item parameter values, AST yields much more balanced item pool usage, with a small loss in the precision of latent trait estimates. The loss is negligible when the test is as long as 40 items.1 aCheng, Ying1 aPatton, Jeffrey, M1 aShao, Can uhttp://epm.sagepub.com/content/75/2/260.abstract01735nas a2200133 4500008003900000245009100039210006900130300001200199490000700211520129100218100001801509700002101527856005301548 2015 d00aBest Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model0 aBest Design for Multidimensional Computerized Adaptive Testing W a954-9780 v753 aMost computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection.1 aSeo, Dong, Gi1 aWeiss, David, J. uhttp://epm.sagepub.com/content/75/6/954.abstract01433nas a2200145 4500008003900000245011700039210006900156300001200225490000700237520092600244100002601170700001401196700002401210856005301234 2015 d00aComparing Simple Scoring With IRT Scoring of Personality Measures: The Navy Computer Adaptive Personality Scales0 aComparing Simple Scoring With IRT Scoring of Personality Measure a144-1540 v393 a

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

1 aOswald, Frederick, L.1 aShaw, Amy1 aFarmer, William, L. uhttp://apm.sagepub.com/content/39/2/144.abstract01379nas a2200157 4500008003900000245012700039210006900166300001200235490000700247520082800254100001701082700002701099700001801126700002401144856005301168 2015 d00aStochastic Curtailment in Adaptive Mastery Testing: Improving the Efficiency of Confidence Interval–Based Stopping Rules0 aStochastic Curtailment in Adaptive Mastery Testing Improving the a278-2920 v393 aA well-known stopping rule in adaptive mastery testing is to terminate the assessment once the examinee’s ability confidence interval lies entirely above or below the cut-off score. This article proposes new procedures that seek to improve such a variable-length stopping rule by coupling it with curtailment and stochastic curtailment. Under the new procedures, test termination can occur earlier if the probability is high enough that the current classification decision remains the same should the test continue. Computation of this probability utilizes normality of an asymptotically equivalent version of the maximum likelihood ability estimate. In two simulation sets, the new procedures showed a substantial reduction in average test length while maintaining similar classification accuracy to the original method.1 aSie, Haskell1 aFinkelman, Matthew, D.1 aBartroff, Jay1 aThompson, Nathan, A uhttp://apm.sagepub.com/content/39/4/278.abstract01461nas a2200157 4500008003900000245006800039210006800107300001200175490000700187520097800194100001701172700002701189700001701216700001701233856005301250 2015 d00aUtilizing Response Times in Computerized Classification Testing0 aUtilizing Response Times in Computerized Classification Testing a389-4050 v393 aA well-known approach in computerized mastery testing is to combine the Sequential Probability Ratio Test (SPRT) stopping rule with item selection to maximize Fisher information at the mastery threshold. This article proposes a new approach in which a time limit is defined for the test and examinees’ response times are considered in both item selection and test termination. Item selection is performed by maximizing Fisher information per time unit, rather than Fisher information itself. The test is terminated once the SPRT makes a classification decision, the time limit is exceeded, or there is no remaining item that has a high enough probability of being answered before the time limit. In a simulation study, the new procedure showed a substantial reduction in average testing time while slightly improving classification accuracy compared with the original method. In addition, the new procedure reduced the percentage of examinees who exceeded the time limit.1 aSie, Haskell1 aFinkelman, Matthew, D.1 aRiley, Barth1 aSmits, Niels uhttp://apm.sagepub.com/content/39/5/389.abstract01617nas a2200193 4500008003900000022001400039245007400053210006900127300001400196490000700210520105700217100002101274700001401295700001901309700001701328700001801345700001901363856004101382 2014 d a1745-398400aDetermining the Overall Impact of Interruptions During Online Testing0 aDetermining the Overall Impact of Interruptions During Online Te a419–4400 v513 a

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

1 aSinharay, Sandip1 aWan, Ping1 aWhitaker, Mike1 aKim, Dong-In1 aZhang, Litong1 aChoi, Seung, W uhttp://dx.doi.org/10.1111/jedm.1205201548nas a2200145 4500008003900000245008200039210006900121300001200190490000700202520108300209100001501292700002001307700002201327856005301349 2014 d00aUsing Multidimensional CAT to Administer a Short, Yet Precise, Screening Test0 aUsing Multidimensional CAT to Administer a Short Yet Precise Scr a614-6310 v383 a

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

1 aYao, Lihua1 aPommerich, Mary1 aSegall, Daniel, O uhttp://apm.sagepub.com/content/38/8/614.abstract00520nas a2200121 4500008004500000245011300045210006900158300001000227490000600237100001300243700001900256856012300275 2013 Engldsh 00aA Comparison of Computerized Classification Testing and Computerized Adaptive Testing in Clinical Psychology0 aComparison of Computerized Classification Testing and Computeriz a19-370 v11 aSmits, N1 aFinkelman, M D uhttp://www.iacat.org/content/comparison-computerized-classification-testing-and-computerized-adaptive-testing-clinical00583nas a2200121 4500008004600000245017700046210006900223300001100292490000600303100001100309700001700320856012400337 2013 Engldish 00aA Comparison of Four Methods for Obtaining Information Functions for Scores From Computerized Adaptive Tests With Normally Distributed Item Difficulties and Discriminations0 aComparison of Four Methods for Obtaining Information Functions f a88-1070 v11 aIto, K1 aSegall, D.O. uhttp://www.iacat.org/content/comparison-four-methods-obtaining-information-functions-scores-computerized-adaptive-tests00532nas 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-testing00637nas a2200181 4500008003900000022001400039245011500053210006900168300001100237490000700248653001800255653002900273653003000302653004200332100002200374700001800396856004100414 2013 d a1745-399200aThe Philosophical Aspects of IRT Equating: Modeling Drift to Evaluate Cohort Growth in Large-Scale Assessments0 aPhilosophical Aspects of IRT Equating Modeling Drift to Evaluate a2–140 v3210acohort growth10aconstruct-relevant drift10aevaluation of scale drift10aphilosophical aspects of IRT equating1 aTaherbhai, Husein1 aSeo, Daeryong uhttp://dx.doi.org/10.1111/emip.1200000516nas a2200121 4500008004100000245009900041210006900140260002300209100001200232700001500244700001500259856012000274 2013 eng d00aReporting differentiated literacy results in PISA by using multidimensional adaptive testing. 0 aReporting differentiated literacy results in PISA by using multi bDodrecht: Springer1 aFrey, A1 aSeitz, N-N1 aKröhne, U uhttp://www.iacat.org/content/reporting-differentiated-literacy-results-pisa-using-multidimensional-adaptive-testing01089nas a2200157 4500008003900000022001400039245007000053210006900123300001400192490000700206520061300213100001600826700001700842700001700859856005500876 2012 d a1745-398400aInvestigating the Effect of Item Position in Computer-Based Tests0 aInvestigating the Effect of Item Position in ComputerBased Tests a362–3790 v493 a

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

1 aLi, Feiming1 aCohen, Allan1 aShen, Linjun uhttp://dx.doi.org/10.1111/j.1745-3984.2012.00181.x01222nas a2200157 4500008003900000245013900039210006900178300001200247490000700259520066600266100002100932700001900953700001500972700002400987856005301011 2012 d00aOn the Reliability and Validity of a Numerical Reasoning Speed Dimension Derived From Response Times Collected in Computerized Testing0 aReliability and Validity of a Numerical Reasoning Speed Dimensio a245-2630 v723 a

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

1 aDavison, Mark, L1 aSemmes, Robert1 aHuang, Lan1 aClose, Catherine, N uhttp://epm.sagepub.com/content/72/2/245.abstract00627nas a2200169 4500008004100000245008900041210006900130260001200199653000800211653002500219653002700244653002100271653001200292100002300304700001600327856011400343 2011 eng d00aAdaptive Item Calibration and Norming: Unique Considerations of a Global Deployment0 aAdaptive Item Calibration and Norming Unique Considerations of a c10/201110aCAT10acommon item equating10aFigural Reasoning Test10aitem calibration10anorming1 aSchwall, Alexander1 aSinar, Evan uhttp://www.iacat.org/content/adaptive-item-calibration-and-norming-%0Bunique-considerations-global-deployment00493nas a2200133 4500008003900000245008200039210006900121300001400190490000800204100001300212700001600225700001500241856010300256 2011 d00aApplying computerized adaptive testing to the CES-D scale: A simulation study0 aApplying computerized adaptive testing to the CESD scale A simul a147–1550 v1881 aSmits, N1 aCuijpers, P1 aStraten, A uhttp://www.iacat.org/content/applying-computerized-adaptive-testing-ces-d-scale-simulation-study-001666nas a2200169 4500008004100000020004100041022001300082245008200095210006900177250001500246260001000261520108000271100001301351700001601364700001501380856010101395 2011 Eng d a0165-1781 (Print)0165-1781 (Linking) a2120866000aApplying computerized adaptive testing to the CES-D scale: A simulation study0 aApplying computerized adaptive testing to the CESD scale A simul a2011/01/07 cJan 33 aIn this paper we studied the appropriateness of developing an adaptive version of the Center of Epidemiological Studies-Depression (CES-D, Radloff, 1977) scale. Computerized Adaptive Testing (CAT) involves the computerized administration of a test in which each item is dynamically selected from a pool of items until a pre-specified measurement precision is reached. Two types of analyses were performed using the CES-D responses of a large sample of adolescents (N=1392). First, it was shown that the items met the psychometric requirements needed for CAT. Second, CATs were simulated by using the existing item responses as if they had been collected adaptively. CATs selecting only a small number of items gave results which, in terms of depression measurement and criterion validity, were only marginally different from the results of full CES-D assessment. It was concluded that CAT is a very fruitful way of improving the efficiency of the CES-D questionnaire. The discussion addresses the strengths and limitations of the application of CAT in mental health research.1 aSmits, N1 aCuijpers, P1 aStraten, A uhttp://www.iacat.org/content/applying-computerized-adaptive-testing-ces-d-scale-simulation-study01960nas a2200193 4500008004100000020001400041245009500055210006900150300001200219490000700231520131000238100001501548700001801563700001701581700001401598700001301612700001901625856012201644 2011 eng d a0022-389100aComputerized adaptive assessment of personality disorder: Introducing the CAT–PD project0 aComputerized adaptive assessment of personality disorder Introdu a380-3890 v933 aAssessment of personality disorders (PD) has been hindered by reliance on the problematic categorical model embodied in the most recent Diagnostic and Statistical Model of Mental Disorders (DSM), lack of consensus among alternative dimensional models, and inefficient measurement methods. This article describes the rationale for and early results from a multiyear study funded by the National Institute of Mental Health that was designed to develop an integrative and comprehensive model and efficient measure of PD trait dimensions. To accomplish these goals, we are in the midst of a 5-phase project to develop and validate the model and measure. The results of Phase 1 of the project—which was focused on developing the PD traits to be assessed and the initial item pool—resulted in a candidate list of 59 PD traits and an initial item pool of 2,589 items. Data collection and structural analyses in community and patient samples will inform the ultimate structure of the measure, and computerized adaptive testing will permit efficient measurement of the resultant traits. The resultant Computerized Adaptive Test of Personality Disorder (CAT–PD) will be well positioned as a measure of the proposed DSM–5 PD traits. Implications for both applied and basic personality research are discussed.1 aSimms, L J1 aGoldberg, L R1 aRoberts, J E1 aWatson, D1 aWelte, J1 aRotterman, J H uhttp://www.iacat.org/content/computerized-adaptive-assessment-personality-disorder-introducing-cat%E2%80%93pd-project00466nas a2200121 4500008003900000245009900039210006900138300001200207490000700219100001900226700003100245856006800276 2011 d00aComputerized Adaptive Testing with the Zinnes and Griggs Pairwise Preference Ideal Point Model0 aComputerized Adaptive Testing with the Zinnes and Griggs Pairwis a231-2470 v111 aStark, Stephen1 aChernyshenko, Oleksandr, S uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2011.56145900482nas a2200145 4500008004100000245006100041210005900102653000800161653001600169653001300185100001900198700001600217700002200233856008100255 2011 eng d00aA Heuristic Of CAT Item Selection Procedure For Testlets0 aHeuristic Of CAT Item Selection Procedure For Testlets10aCAT10ashadow test10atestlets1 aChien, Yuehmei1 aShin, David1 aWay, Walter Denny uhttp://www.iacat.org/content/heuristic-cat-item-selection-procedure-testlets00506nas a2200121 4500008003900000245011000039210006900149300001200218490000700230100001200237700001500249856012000264 2011 d00aHypothetical use of multidimensional adaptive testing for the assessment of student achievement in PISA. 0 aHypothetical use of multidimensional adaptive testing for the as a503-5220 v711 aFrey, A1 aSeitz, N-N uhttp://www.iacat.org/content/hypothetical-use-multidimensional-adaptive-testing-assessment-student-achievement-pisa00653nas a2200157 4500008004100000020001400041245015700055210006900212100001800281700001400299700001500313700001600328700001500344700001300359856012300372 2011 eng d a1073-191100aItem banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): depression, anxiety, and anger0 aItem banks for measuring emotional distress from the PatientRepo1 aPilkonis, P A1 aChoi, S W1 aReise, S P1 aStover, A M1 aRiley, W T1 aCella, D uhttp://www.iacat.org/content/item-banks-measuring-emotional-distress-patient-reported-outcomes-measurement-information00688nas a2200217 4500008004100000245006000041210005800101260001200159653001700171653001700188653000800205653001500213653002500228653003200253653001700285100001800302700002100320700001600341700002400357856008900381 2011 eng d00aPractitioner’s Approach to Identify Item Drift in CAT0 aPractitioner s Approach to Identify Item Drift in CAT c10/201110aCUSUM method10aG2 statistic10aIPA10aitem drift10aitem parameter drift10aLord's chi-square statistic10aRaju's NCDIF1 aMeng, Huijuan1 aSteinkamp, Susan1 aJones, Paul1 aMatthews-Lopez, Joy uhttp://www.iacat.org/content/practitioner%E2%80%99s-approach-identify-item-drift-cat00465nas a2200133 4500008004100000245005800041210005800099260004200157300001200199490000700211100001200218700001700230856008400247 2010 eng d00aComputerized adaptive testing based on decision trees0 aComputerized adaptive testing based on decision trees aSousse, TunisiabIEEE Computer Sience a191-1930 v581 aUeno, M1 aSongmuang, P uhttp://www.iacat.org/content/computerized-adaptive-testing-based-decision-trees01349nas a2200229 4500008004100000020001300041245011700054210006900171300001200240490000700252520057500259653000800834653003400842653001900876653001500895100002000910700001600930700001800946700001500964700001400979856012600993 2010 eng d a0191886900aDetection of aberrant item score patterns in computerized adaptive testing: An empirical example using the CUSUM0 aDetection of aberrant item score patterns in computerized adapti a921-9250 v483 aThe scalability of individual trait scores on a computerized adaptive test (CAT) was assessed through investigating the consistency of individual item score patterns. A sample of N = 428 persons completed a personality CAT as part of a career development procedure. To detect inconsistent item score patterns, we used a cumulative sum (CUSUM) procedure. Combined information from the CUSUM, other personality measures, and interviews showed that similar estimated trait values may have a different interpretation.Implications for computer-based assessment are discussed.10aCAT10acomputerized adaptive testing10aCUSUM approach10aperson Fit1 aEgberink, I J L1 aMeijer, R R1 aVeldkamp, B P1 aSchakel, L1 aSmid, N G uhttp://www.iacat.org/content/detection-aberrant-item-score-patterns-computerized-adaptive-testing-empirical-example-using03103nas a2200445 4500008004100000020004100041245012000082210006900202250001500271260001000286300001100296490000700307520175400314653003802068653002102106653001002127653000902137653002202146653002802168653003302196653001102229653001102240653000902251653001602260653001802276653001902294653003102313653003102344653001602375100001602391700001002407700001402417700001502431700001402446700001502460700001802475700002402493700001802517856012202535 2010 eng d a0161-8105 (Print)0161-8105 (Linking)00aDevelopment and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments0 aDevelopment and validation of patientreported outcome measures f a2010/06/17 cJun 1 a781-920 v333 aSTUDY OBJECTIVES: To develop an archive of self-report questions assessing sleep disturbance and sleep-related impairments (SRI), to develop item banks from this archive, and to validate and calibrate the item banks using classic validation techniques and item response theory analyses in a sample of clinical and community participants. DESIGN: Cross-sectional self-report study. SETTING: Academic medical center and participant homes. PARTICIPANTS: One thousand nine hundred ninety-three adults recruited from an Internet polling sample and 259 adults recruited from medical, psychiatric, and sleep clinics. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: This study was part of PROMIS (Patient-Reported Outcomes Information System), a National Institutes of Health Roadmap initiative. Self-report item banks were developed through an iterative process of literature searches, collecting and sorting items, expert content review, qualitative patient research, and pilot testing. Internal consistency, convergent validity, and exploratory and confirmatory factor analysis were examined in the resulting item banks. Factor analyses identified 2 preliminary item banks, sleep disturbance and SRI. Item response theory analyses and expert content review narrowed the item banks to 27 and 16 items, respectively. Validity of the item banks was supported by moderate to high correlations with existing scales and by significant differences in sleep disturbance and SRI scores between participants with and without sleep disorders. CONCLUSIONS: The PROMIS sleep disturbance and SRI item banks have excellent measurement properties and may prove to be useful for assessing general aspects of sleep and SRI with various groups of patients and interventions.10a*Outcome Assessment (Health Care)10a*Self Disclosure10aAdult10aAged10aAged, 80 and over10aCross-Sectional Studies10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aPsychometrics10aQuestionnaires10aReproducibility of Results10aSleep Disorders/*diagnosis10aYoung Adult1 aBuysse, D J1 aYu, L1 aMoul, D E1 aGermain, A1 aStover, A1 aDodds, N E1 aJohnston, K L1 aShablesky-Cade, M A1 aPilkonis, P A uhttp://www.iacat.org/content/development-and-validation-patient-reported-outcome-measures-sleep-disturbance-and-sleep02223nas a2200289 4500008004100000020004600041245010800087210006900195250001500264300001200279490000700291520131000298100001801608700001701626700001801643700001401661700001401675700001801689700001401707700001701721700001501738700001301753700001401766700001601780700001301796856012401809 2010 Eng d a1573-2649 (Electronic)0962-9343 (Linking)00aDevelopment of computerized adaptive testing (CAT) for the EORTC QLQ-C30 physical functioning dimension0 aDevelopment of computerized adaptive testing CAT for the EORTC Q a2010/10/26 a479-4900 v203 aPURPOSE: Computerized adaptive test (CAT) methods, based on item response theory (IRT), enable a patient-reported outcome instrument to be adapted to the individual patient while maintaining direct comparability of scores. The EORTC Quality of Life Group is developing a CAT version of the widely used EORTC QLQ-C30. We present the development and psychometric validation of the item pool for the first of the scales, physical functioning (PF). METHODS: Initial developments (including literature search and patient and expert evaluations) resulted in 56 candidate items. Responses to these items were collected from 1,176 patients with cancer from Denmark, France, Germany, Italy, Taiwan, and the United Kingdom. The items were evaluated with regard to psychometric properties. RESULTS: Evaluations showed that 31 of the items could be included in a unidimensional IRT model with acceptable fit and good content coverage, although the pool may lack items at the upper extreme (good PF). There were several findings of significant differential item functioning (DIF). However, the DIF findings appeared to have little impact on the PF estimation. CONCLUSIONS: We have established an item pool for CAT measurement of PF and believe that this CAT instrument will clearly improve the EORTC measurement of PF.1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aChie, W C1 aConroy, T1 aCostantini, A1 aFayers, P1 aHelbostad, J1 aHolzner, B1 aKaasa, S1 aSinger, S1 aVelikova, G1 aYoung, T uhttp://www.iacat.org/content/development-computerized-adaptive-testing-cat-eortc-qlq-c30-physical-functioning-dimension00450nas a2200109 4500008004100000245007500041210006900116300001200185100002500197700002400222856009400246 2010 eng d00aMATHCAT: A Flexible Testing System in Mathematics Education for Adults0 aMATHCAT A Flexible Testing System in Mathematics Education for A a137-1501 aVerschoor, Angela, J1 aStraetmans, G J J M uhttp://www.iacat.org/content/mathcat-flexible-testing-system-mathematics-education-adults00561nas a2200145 4500008003900000245015500039210006900194300001200263490000700275100001700282700001400299700001800313700001600331856006800347 2010 d00aA Monte Carlo Simulation Investigating the Validity and Reliability of Ability Estimation in Item Response Theory with Speeded Computer Adaptive Tests0 aMonte Carlo Simulation Investigating the Validity and Reliabilit a230-2610 v101 aSchmitt, T A1 aSass, D A1 aSullivan, J R1 aWalker, C M uhttp://www.tandfonline.com/doi/abs/10.1080/15305058.2010.48809800581nas a2200121 4500008004400000245017600044210006900220300001000289490000700299100001200306700001500318856012600333 2010 Germdn 00aMultidimensionale adaptive Kompetenzdiagnostik: Ergebnisse zur Messeffizienz [Multidimensional adaptive testing of competencies: Results regarding measurement efficiency].0 aMultidimensionale adaptive Kompetenzdiagnostik Ergebnisse zur Me a40-510 v561 aFrey, A1 aSeitz, N-N uhttp://www.iacat.org/content/multidimensionale-adaptive-kompetenzdiagnostik-ergebnisse-zur-messeffizienz-multidimensional00349nas a2200097 4500008004100000245005200041210005200093300001000145100001600155856008000171 2010 eng d00aPrinciples of Multidimensional Adaptive Testing0 aPrinciples of Multidimensional Adaptive Testing a57-761 aSegall, D O uhttp://www.iacat.org/content/principles-multidimensional-adaptive-testing-001940nas a2200121 4500008004100000245010300041210006900144260010000213520135600313100001601669700001401685856011901699 2009 eng d00aA burdened CAT: Incorporating response burden with maximum Fisher's information for item selection0 aburdened CAT Incorporating response burden with maximum Fishers  aIn D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aWidely used in various educational and vocational assessment applications, computerized adaptive testing (CAT) has recently begun to be used to measure patient-reported outcomes Although successful in reducing respondent burden, most current CAT algorithms do not formally consider it as part of the item selection process. This study used a loss function approach motivated by decision theory to develop an item selection method that incorporates respondent burden into the item selection process based on maximum Fisher information item selection. Several different loss functions placing varying degrees of importance on respondent burden were compared, using an item bank of 62 polytomous items measuring depressive symptoms. One dataset consisted of the real responses from the 730 subjects who responded to all the items. A second dataset consisted of simulated responses to all the items based on a grid of latent trait scores with replicates at each grid point. The algorithm enables a CAT administrator to more efficiently control the respondent burden without severely affecting the measurement precision than when using MFI alone. In particular, the loss function incorporating respondent burden protected respondents from receiving longer tests when their estimated trait score fell in a region where there were few informative items. 1 aSwartz, R J1 aChoi, S W uhttp://www.iacat.org/content/burdened-cat-incorporating-response-burden-maximum-fishers-information-item-selection00437nas a2200121 4500008004100000245006700041210006700108300001400175490000700189100001400196700001600210856008900226 2009 eng d00aComparison of CAT item selection criteria for polytomous items0 aComparison of CAT item selection criteria for polytomous items a419–4400 v331 aChoi, S W1 aSwartz, R J uhttp://www.iacat.org/content/comparison-cat-item-selection-criteria-polytomous-items01148nas a2200133 4500008003900000245006700039210006700106300001200173490000700185520072700192100001900919700002300938856005300961 2009 d00aComparison of CAT Item Selection Criteria for Polytomous Items0 aComparison of CAT Item Selection Criteria for Polytomous Items a419-4400 v333 a

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

1 aChoi, Seung, W1 aSwartz, Richard, J uhttp://apm.sagepub.com/content/33/6/419.abstract00459nas a2200097 4500008004100000245010100041210006900142100001500211700001400226856012100240 2009 eng d00aComputerized adaptive testing using the two parameter logistic model with ability-based guessing0 aComputerized adaptive testing using the two parameter logistic m1 aShih, H -J1 aWang, W-C uhttp://www.iacat.org/content/computerized-adaptive-testing-using-two-parameter-logistic-model-ability-based-guessing01893nas a2200157 4500008004100000245007800041210006900119260009700188520126000285100001801545700001801563700002001581700001701601700001601618856010101634 2009 eng d00aCriterion-related validity of an innovative CAT-based personality measure0 aCriterionrelated validity of an innovative CATbased personality  aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThis paper describes development and initial criterion-related validation of the PreVisor Computer Adaptive Personality Scales (PCAPS), a computerized adaptive testing-based personality measure that uses an ideal point IRT model based on forced-choice, paired-comparison responses. Based on results from a large consortium study, a composite of six PCAPS scales identified as relevant to the population of interest (first-line supervisors) had an estimated operational validity against an overall job performance criterion of ρ = .25. Uncorrected and corrected criterion-related validity results for each of the six PCAPS scales making up the composite are also reported. Because the PCAPS algorithm computes intermediate scale scores until a stopping rule is triggered, we were able to graph number of statement-pairs presented against criterion-related validities. Results showed generally monotonically increasing functions. However, asymptotic validity levels, or at least a reduction in the rate of increase in slope, were often reached after 5-7 statement-pairs were presented. In the case of the composite measure, there was some evidence that validities decreased after about six statement-pairs. A possible explanation for this is provided.1 aSchneider, RJ1 aMcLellan, R A1 aKantrowitz, T M1 aHouston, J S1 aBorman, W C uhttp://www.iacat.org/content/criterion-related-validity-innovative-cat-based-personality-measure02749nas a2200409 4500008004100000020004600041245009400087210006900181250001500250260000800265300001200273490000700285520144500292653001501737653002001752653003101772653003001803653002001833653001901853653002601872653001101898653001101909653000901920653001601929653002601945653003701971653003002008653004402038653001802082653002002100653002802120100002002148700002302168700001602191700001702207856011502224 2009 eng d a1528-8447 (Electronic)1526-5900 (Linking)00aDevelopment and preliminary testing of a computerized adaptive assessment of chronic pain0 aDevelopment and preliminary testing of a computerized adaptive a a2009/07/15 cSep a932-9430 v103 aThe aim of this article is to report the development and preliminary testing of a prototype computerized adaptive test of chronic pain (CHRONIC PAIN-CAT) conducted in 2 stages: (1) evaluation of various item selection and stopping rules through real data-simulated administrations of CHRONIC PAIN-CAT; (2) a feasibility study of the actual prototype CHRONIC PAIN-CAT assessment system conducted in a pilot sample. Item calibrations developed from a US general population sample (N = 782) were used to program a pain severity and impact item bank (kappa = 45), and real data simulations were conducted to determine a CAT stopping rule. The CHRONIC PAIN-CAT was programmed on a tablet PC using QualityMetric's Dynamic Health Assessment (DYHNA) software and administered to a clinical sample of pain sufferers (n = 100). The CAT was completed in significantly less time than the static (full item bank) assessment (P < .001). On average, 5.6 items were dynamically administered by CAT to achieve a precise score. Scores estimated from the 2 assessments were highly correlated (r = .89), and both assessments discriminated across pain severity levels (P < .001, RV = .95). Patients' evaluations of the CHRONIC PAIN-CAT were favorable. PERSPECTIVE: This report demonstrates that the CHRONIC PAIN-CAT is feasible for administration in a clinic. The application has the potential to improve pain assessment and help clinicians manage chronic pain.10a*Computers10a*Questionnaires10aActivities of Daily Living10aAdaptation, Psychological10aChronic Disease10aCohort Studies10aDisability Evaluation10aFemale10aHumans10aMale10aMiddle Aged10aModels, Psychological10aOutcome Assessment (Health Care)10aPain Measurement/*methods10aPain, Intractable/*diagnosis/psychology10aPsychometrics10aQuality of Life10aUser-Computer Interface1 aAnatchkova, M D1 aSaris-Baglama, R N1 aKosinski, M1 aBjorner, J B uhttp://www.iacat.org/content/development-and-preliminary-testing-computerized-adaptive-assessment-chronic-pain02881nas a2200493 4500008004100000020004100041245014100082210006900223250001500292260000800307300001100315490000700326520125100333653003001584653001001614653000901624653004601633653003301679653001101712653003101723653001101754653000901765653003301774653001601807653002401823653004601847653005501893653005501948653004602003653001902049653003102068653001402099100001602113700001502129700001302144700001402157700001502171700001702186700001502203700001702218700001502235700001302250856012402263 2009 eng d a0090-5550 (Print)0090-5550 (Linking)00aDevelopment of an item bank for the assessment of depression in persons with mental illnesses and physical diseases using Rasch analysis0 aDevelopment of an item bank for the assessment of depression in  a2009/05/28 cMay a186-970 v543 aOBJECTIVE: The calibration of item banks provides the basis for computerized adaptive testing that ensures high diagnostic precision and minimizes participants' test burden. The present study aimed at developing a new item bank that allows for assessing depression in persons with mental and persons with somatic diseases. METHOD: The sample consisted of 161 participants treated for a depressive syndrome, and 206 participants with somatic illnesses (103 cardiologic, 103 otorhinolaryngologic; overall mean age = 44.1 years, SD =14.0; 44.7% women) to allow for validation of the item bank in both groups. Persons answered a pool of 182 depression items on a 5-point Likert scale. RESULTS: Evaluation of Rasch model fit (infit < 1.3), differential item functioning, dimensionality, local independence, item spread, item and person separation (>2.0), and reliability (>.80) resulted in a bank of 79 items with good psychometric properties. CONCLUSIONS: The bank provides items with a wide range of content coverage and may serve as a sound basis for computerized adaptive testing applications. It might also be useful for researchers who wish to develop new fixed-length scales for the assessment of depression in specific rehabilitation settings.10aAdaptation, Psychological10aAdult10aAged10aDepressive Disorder/*diagnosis/psychology10aDiagnosis, Computer-Assisted10aFemale10aHeart Diseases/*psychology10aHumans10aMale10aMental Disorders/*psychology10aMiddle Aged10aModels, Statistical10aOtorhinolaryngologic Diseases/*psychology10aPersonality Assessment/statistics & numerical data10aPersonality Inventory/*statistics & numerical data10aPsychometrics/statistics & numerical data10aQuestionnaires10aReproducibility of Results10aSick Role1 aForkmann, T1 aBoecker, M1 aNorra, C1 aEberle, N1 aKircher, T1 aSchauerte, P1 aMischke, K1 aWesthofen, M1 aGauggel, S1 aWirtz, M uhttp://www.iacat.org/content/development-item-bank-assessment-depression-persons-mental-illnesses-and-physical-diseases00616nas 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-computerized00460nas a2200109 4500008004100000245005600041210005300097260009700150100001300247700001300260856007700273 2009 eng d00aItem selection with biased-coin up-and-down designs0 aItem selection with biasedcoin upanddown designs aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aSheng, Y1 aSheng, Z uhttp://www.iacat.org/content/item-selection-biased-coin-and-down-designs01383nas a2200145 4500008004100000020001300041245012000054210006900174300001000243490000700253520082700260100001201087700001501099856012301114 2009 eng d a0191491X00aMultidimensional adaptive testing in educational and psychological measurement: Current state and future challenges0 aMultidimensional adaptive testing in educational and psychologic a89-940 v353 aThe paper gives an overview of multidimensional adaptive testing (MAT) and evaluates its applicability in educational and psychological testing. The approach of Segall (1996) is described as a general framework for MAT. The main advantage of MAT is its capability to increase measurement efficiency. In simulation studies conceptualizing situations typical to large scale assessments, the number of presented items was reduced by MAT by about 30–50% compared to unidimensional adaptive testing and by about 70% compared to fixed item testing holding measurement precision constant. Empirical results underline these findings. Before MAT is used routinely some open questions should be answered first. After that, MAT represents a very promising approach to highly efficient simultaneous testing of multiple competencies.1 aFrey, A1 aSeitz, N-N uhttp://www.iacat.org/content/multidimensional-adaptive-testing-educational-and-psychological-measurement-current-state02048nas a2200133 4500008004100000245006100041210005500102260010000157520152600257100001701783700001601800700001601816856008201832 2009 eng d00aThe nine lives of CAT-ASVAB: Innovations and revelations0 anine lives of CATASVAB Innovations and revelations aIn D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThe Armed Services Vocational Aptitude Battery (ASVAB) is administered annually to more than one million military applicants and high school students. ASVAB scores are used to determine enlistment eligibility, assign applicants to military occupational specialties, and aid students in career exploration. The ASVAB is administered as both a paper-and-pencil (P&P) test and a computerized adaptive test (CAT). CAT-ASVAB holds the distinction of being the first large-scale adaptive test battery to be administered in a high-stakes setting. Approximately two-thirds of military applicants currently take CAT-ASVAB; long-term plans are to replace P&P-ASVAB with CAT-ASVAB at all test sites. Given CAT-ASVAB’s pedigree—approximately 20 years in development and 20 years in operational administration—much can be learned from revisiting some of the major highlights of CATASVAB history. This paper traces the progression of CAT-ASVAB through nine major phases of development including: research and evelopment of the CAT-ASVAB prototype, the initial development of psychometric procedures and item pools, initial and full-scale operational implementation, the introduction of new item pools, the introduction of Windows administration, the introduction of Internet administration, and research and development of the next generation CATASVAB. A background and history is provided for each phase, including discussions of major research and operational issues, innovative approaches and practices, and lessons learned.1 aPommerich, M1 aSegall, D O1 aMoreno, K E uhttp://www.iacat.org/content/nine-lives-cat-asvab-innovations-and-revelations00717nas a2200229 4500008004100000020004100041245005200082210005100134250001500185260000800200300000800208490000700216653003400223653005000257653001100307653003200318653001300350100001500363700001500378700001800393856007600411 2008 eng d a1075-2730 (Print)1075-2730 (Linking)00aAre we ready for computerized adaptive testing?0 aAre we ready for computerized adaptive testing a2008/04/02 cApr a3690 v5910a*Attitude of Health Personnel10a*Diagnosis, Computer-Assisted/instrumentation10aHumans10aMental Disorders/*diagnosis10aSoftware1 aUnick, G J1 aShumway, M1 aHargreaves, W uhttp://www.iacat.org/content/are-we-ready-computerized-adaptive-testing01669nas a2200169 4500008003900000245009500039210007100134300000900205490000700214520113900221100001701360700001401377700002201391700001901413700001601432856005101448 2008 d00aComparability of Computer-Based and Paper-and-Pencil Testing in K–12 Reading Assessments0 aComparability of ComputerBased and PaperandPencil Testing in K–1 a5-240 v683 a

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

1 aShudong Wang1 aHong Jiao1 aYoung, Michael, J1 aBrooks, Thomas1 aOlson, John uhttp://epm.sagepub.com/content/68/1/5.abstract03041nas a2200481 4500008004100000020004600041245012200087210006900209250001500278260000800293300001200301490000700313520155700320653003201877653003101909653002201940653002001962653001001982653000901992653002202001653002802023653003302051653001102084653001102095653002502106653000902131653001602140653004602156653002202202653002402224653003002248653002902278100001502307700001402322700001502336700002402351700001802375700001102393700001602404700001002420700001502430856011402445 2008 eng d a1532-821X (Electronic)0003-9993 (Linking)00aComputerized adaptive testing for follow-up after discharge from inpatient rehabilitation: II. Participation outcomes0 aComputerized adaptive testing for followup after discharge from  a2008/01/30 cFeb a275-2830 v893 aOBJECTIVES: To measure participation outcomes with a computerized adaptive test (CAT) and compare CAT and traditional fixed-length surveys in terms of score agreement, respondent burden, discriminant validity, and responsiveness. DESIGN: Longitudinal, prospective cohort study of patients interviewed approximately 2 weeks after discharge from inpatient rehabilitation and 3 months later. SETTING: Follow-up interviews conducted in patient's home setting. PARTICIPANTS: Adults (N=94) with diagnoses of neurologic, orthopedic, or medically complex conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Participation domains of mobility, domestic life, and community, social, & civic life, measured using a CAT version of the Participation Measure for Postacute Care (PM-PAC-CAT) and a 53-item fixed-length survey (PM-PAC-53). RESULTS: The PM-PAC-CAT showed substantial agreement with PM-PAC-53 scores (intraclass correlation coefficient, model 3,1, .71-.81). On average, the PM-PAC-CAT was completed in 42% of the time and with only 48% of the items as compared with the PM-PAC-53. Both formats discriminated across functional severity groups. The PM-PAC-CAT had modest reductions in sensitivity and responsiveness to patient-reported change over a 3-month interval as compared with the PM-PAC-53. CONCLUSIONS: Although continued evaluation is warranted, accurate estimates of participation status and responsiveness to change for group-level analyses can be obtained from CAT administrations, with a sizeable reduction in respondent burden.10a*Activities of Daily Living10a*Adaptation, Physiological10a*Computer Systems10a*Questionnaires10aAdult10aAged10aAged, 80 and over10aChi-Square Distribution10aFactor Analysis, Statistical10aFemale10aHumans10aLongitudinal Studies10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPatient Discharge10aProspective Studies10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aGandek, B1 aSiebens, H1 aBlack-Schaffer, R M1 aSinclair, S J1 aTao, W1 aCoster, W J1 aNi, P1 aJette, A M uhttp://www.iacat.org/content/computerized-adaptive-testing-follow-after-discharge-inpatient-rehabilitation-ii00581nas a2200145 4500008004100000245012000041210006900161300001400230490000700244100001400251700001400265700001900279700001800298856011900316 2008 eng d00aComputerized adaptive testing for patients with knee inpairments produced valid and responsive measures of function0 aComputerized adaptive testing for patients with knee inpairments a1113-11240 v611 aHart, D L1 aWang, Y-C1 aStratford, P W1 aMioduski, J E uhttp://www.iacat.org/content/computerized-adaptive-testing-patients-knee-inpairments-produced-valid-and-responsive03313nas a2200433 4500008004100000020004600041245007700087210006900164250001500233260001100248300001200259490000700271520203200278653002702310653003002337653002102367653001002388653000902398653001502407653003602422653002102458653004402479653002402523653001102547653001102558653001302569653000902582653001602591653003002607653003002637653003102667100001502698700001302713700001502726700001402741700001502755700001402770856009502784 2008 eng d a1528-1159 (Electronic)0362-2436 (Linking)00aComputerized adaptive testing in back pain: Validation of the CAT-5D-QOL0 aComputerized adaptive testing in back pain Validation of the CAT a2008/05/23 cMay 20 a1384-900 v333 aSTUDY DESIGN: We have conducted an outcome instrument validation study. OBJECTIVE: Our objective was to develop a computerized adaptive test (CAT) to measure 5 domains of health-related quality of life (HRQL) and assess its feasibility, reliability, validity, and efficiency. SUMMARY OF BACKGROUND DATA: Kopec and colleagues have recently developed item response theory based item banks for 5 domains of HRQL relevant to back pain and suitable for CAT applications. The domains are Daily Activities (DAILY), Walking (WALK), Handling Objects (HAND), Pain or Discomfort (PAIN), and Feelings (FEEL). METHODS: An adaptive algorithm was implemented in a web-based questionnaire administration system. The questionnaire included CAT-5D-QOL (5 scales), Modified Oswestry Disability Index (MODI), Roland-Morris Disability Questionnaire (RMDQ), SF-36 Health Survey, and standard clinical and demographic information. Participants were outpatients treated for mechanical back pain at a referral center in Vancouver, Canada. RESULTS: A total of 215 patients completed the questionnaire and 84 completed a retest. On average, patients answered 5.2 items per CAT-5D-QOL scale. Reliability ranged from 0.83 (FEEL) to 0.92 (PAIN) and was 0.92 for the MODI, RMDQ, and Physical Component Summary (PCS-36). The ceiling effect was 0.5% for PAIN compared with 2% for MODI and 5% for RMQ. The CAT-5D-QOL scales correlated as anticipated with other measures of HRQL and discriminated well according to the level of satisfaction with current symptoms, duration of the last episode, sciatica, and disability compensation. The average relative discrimination index was 0.87 for PAIN, 0.67 for DAILY and 0.62 for WALK, compared with 0.89 for MODI, 0.80 for RMDQ, and 0.59 for PCS-36. CONCLUSION: The CAT-5D-QOL is feasible, reliable, valid, and efficient in patients with back pain. This methodology can be recommended for use in back pain research and should improve outcome assessment, facilitate comparisons across studies, and reduce patient burden.10a*Disability Evaluation10a*Health Status Indicators10a*Quality of Life10aAdult10aAged10aAlgorithms10aBack Pain/*diagnosis/psychology10aBritish Columbia10aDiagnosis, Computer-Assisted/*standards10aFeasibility Studies10aFemale10aHumans10aInternet10aMale10aMiddle Aged10aPredictive Value of Tests10aQuestionnaires/*standards10aReproducibility of Results1 aKopec, J A1 aBadii, M1 aMcKenna, M1 aLima, V D1 aSayre, E C1 aDvorak, M uhttp://www.iacat.org/content/computerized-adaptive-testing-back-pain-validation-cat-5d-qol01188nas a2200157 4500008004500000245009300045210006900138300001200207490000600219520062800225100001600853700001900869700001400888700001500902856011300917 2008 Engldsh 00aImpact of altering randomization intervals on precision of measurement and item exposure0 aImpact of altering randomization intervals on precision of measu a160-1670 v93 a

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

1 aMuckle, T J1 aBergstrom, B A1 aBecker, K1 aStahl, J A uhttp://www.iacat.org/content/impact-altering-randomization-intervals-precision-measurement-and-item-exposure01442nas a2200145 4500008003900000022001400039245007100053210006900124300001400193490000700207520098500214100002001199700002201219856005501241 2008 d a1745-398400aLocal Dependence in an Operational CAT: Diagnosis and Implications0 aLocal Dependence in an Operational CAT Diagnosis and Implication a201–2230 v453 a

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

1 aPommerich, Mary1 aSegall, Daniel, O uhttp://dx.doi.org/10.1111/j.1745-3984.2008.00061.x03157nas a2200493 4500008004100000020002200041245008900063210006900152250001500221260000800236300001000244490000700254520169600261653003401957653002001991653001502011653001002026653000902036653002602045653003202071653003102103653001102134653001102145653000902156653003202165653001602197653002902213653004402242653002902286653003102315653003102346653001702377100001702394700001402411700001602425700001302441700001702454700002202471700001702493700001402510700001402524700001702538856010802555 2008 eng d a1075-2730 (Print)00aUsing computerized adaptive testing to reduce the burden of mental health assessment0 aUsing computerized adaptive testing to reduce the burden of ment a2008/04/02 cApr a361-80 v593 aOBJECTIVE: This study investigated the combination of item response theory and computerized adaptive testing (CAT) for psychiatric measurement as a means of reducing the burden of research and clinical assessments. METHODS: Data were from 800 participants in outpatient treatment for a mood or anxiety disorder; they completed 616 items of the 626-item Mood and Anxiety Spectrum Scales (MASS) at two times. The first administration was used to design and evaluate a CAT version of the MASS by using post hoc simulation. The second confirmed the functioning of CAT in live testing. RESULTS: Tests of competing models based on item response theory supported the scale's bifactor structure, consisting of a primary dimension and four group factors (mood, panic-agoraphobia, obsessive-compulsive, and social phobia). Both simulated and live CAT showed a 95% average reduction (585 items) in items administered (24 and 30 items, respectively) compared with administration of the full MASS. The correlation between scores on the full MASS and the CAT version was .93. For the mood disorder subscale, differences in scores between two groups of depressed patients--one with bipolar disorder and one without--on the full scale and on the CAT showed effect sizes of .63 (p<.003) and 1.19 (p<.001) standard deviation units, respectively, indicating better discriminant validity for CAT. CONCLUSIONS: Instead of using small fixed-length tests, clinicians can create item banks with a large item pool, and a small set of the items most relevant for a given individual can be administered with no loss of information, yielding a dramatic reduction in administration time and patient and clinician burden.10a*Diagnosis, Computer-Assisted10a*Questionnaires10aAdolescent10aAdult10aAged10aAgoraphobia/diagnosis10aAnxiety Disorders/diagnosis10aBipolar Disorder/diagnosis10aFemale10aHumans10aMale10aMental Disorders/*diagnosis10aMiddle Aged10aMood Disorders/diagnosis10aObsessive-Compulsive Disorder/diagnosis10aPanic Disorder/diagnosis10aPhobic Disorders/diagnosis10aReproducibility of Results10aTime Factors1 aGibbons, R D1 aWeiss, DJ1 aKupfer, D J1 aFrank, E1 aFagiolini, A1 aGrochocinski, V J1 aBhaumik, D K1 aStover, A1 aBock, R D1 aImmekus, J C uhttp://www.iacat.org/content/using-computerized-adaptive-testing-reduce-burden-mental-health-assessment02410nas a2200193 4500008004100000020002200041245011700063210006900180250001500249300001100264490000600275520172700281100001502008700001702023700001602040700001802056700001802074856012402092 2008 eng d a1740-7745 (Print)00aUsing item banks to construct measures of patient reported outcomes in clinical trials: investigator perceptions0 aUsing item banks to construct measures of patient reported outco a2008/11/26 a575-860 v53 aBACKGROUND: Item response theory (IRT) promises more sensitive and efficient measurement of patient-reported outcomes (PROs) than traditional approaches; however, the selection and use of PRO measures from IRT-based item banks differ from current methods of using PRO measures. PURPOSE: To anticipate barriers to the adoption of IRT item banks into clinical trials. METHODS: We conducted semistructured telephone or in-person interviews with 42 clinical researchers who published results from clinical trials in the Journal of the American Medical Association, the New England Journal of Medicine, or other leading clinical journals from July 2005 through May 2006. Interviews included a brief tutorial on IRT item banks. RESULTS: After the tutorial, 39 of 42 participants understood the novel products available from an IRT item bank, namely customized short forms and computerized adaptive testing. Most participants (38/42) thought that item banks could be useful in their clinical trials, but they mentioned several potential barriers to adoption, including economic and logistical constraints, concerns about whether item banks are better than current PRO measures, concerns about how to convince study personnel or statisticians to use item banks, concerns about FDA or sponsor acceptance, and the lack of availability of item banks validated in specific disease populations. LIMITATIONS: Selection bias might have led to more positive responses to the concept of item banks in clinical trials. CONCLUSIONS: Clinical investigators are open to a new method of PRO measurement offered in IRT item banks, but bank developers must address investigator and stakeholder concerns before widespread adoption can be expected.1 aFlynn, K E1 aDombeck, C B1 aDeWitt, E M1 aSchulman, K A1 aWeinfurt, K P uhttp://www.iacat.org/content/using-item-banks-construct-measures-patient-reported-outcomes-clinical-trials-investigator00526nas a2200109 4500008004100000245007700041210006900118260009700187100001300284700002200297856009700319 2007 eng d00aAdaptive testing with the multi-unidimensional pairwise preference model0 aAdaptive testing with the multiunidimensional pairwise preferenc aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aStark, S1 aChernyshenko, O S uhttp://www.iacat.org/content/adaptive-testing-multi-unidimensional-pairwise-preference-model00522nas a2200109 4500008004100000245007700041210006900118260009700187100001500284700001400299856009900313 2007 eng d00aBundle models for computerized adaptive testing in e-learning assessment0 aBundle models for computerized adaptive testing in elearning ass aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aScalise, K1 aWilson, M uhttp://www.iacat.org/content/bundle-models-computerized-adaptive-testing-e-learning-assessment00638nas a2200145 4500008004100000245009700041210006900138260009700207100001600304700001200320700001900332700001300351700001300364856011500377 2007 eng d00aDevelopment of a multiple-component CAT for measuring foreign language proficiency (SIMTEST)0 aDevelopment of a multiplecomponent CAT for measuring foreign lan aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aSumbling, M1 aSanz, P1 aViladrich, M C1 aDoval, E1 aRiera, L uhttp://www.iacat.org/content/development-multiple-component-cat-measuring-foreign-language-proficiency-simtest04076nas 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-diagnosis02412nas a2200361 4500008004500000020001400045245011100059210006900170300001200239490000700251520135900258653001601617653002001633653001301653653002401666653002501690653001101715653001401726653001301740653001801753653002701771653001001798653001101808100001501819700001201834700001601846700001201862700001601874700001301890700001301903700001401916856012001930 2007 Engldsh  a1057-924900aThe initial development of an item bank to assess and screen for psychological distress in cancer patients0 ainitial development of an item bank to assess and screen for psy a724-7320 v163 aPsychological distress is a common problem among cancer patients. Despite the large number of instruments that have been developed to assess distress, their utility remains disappointing. This study aimed to use Rasch models to develop an item-bank which would provide the basis for better means of assessing psychological distress in cancer patients. An item bank was developed from eight psychological distress questionnaires using Rasch analysis to link common items. Items from the questionnaires were added iteratively with common items as anchor points and misfitting items (infit mean square > 1.3) removed, and unidimensionality assessed. A total of 4914 patients completed the questionnaires providing an initial pool of 83 items. Twenty items were removed resulting in a final pool of 63 items. Good fit was demonstrated and no additional factor structure was evident from the residuals. However, there was little overlap between item locations and person measures, since items mainly targeted higher levels of distress. The Rasch analysis allowed items to be pooled and generated a unidimensional instrument for measuring psychological distress in cancer patients. Additional items are required to more accurately assess patients across the whole continuum of psychological distress. (PsycINFO Database Record (c) 2007 APA ) (journal abstract)10a3293 Cancer10acancer patients10aDistress10ainitial development10aItem Response Theory10aModels10aNeoplasms10aPatients10aPsychological10apsychological distress10aRasch10aStress1 aSmith, A B1 aRush, R1 aVelikova, G1 aWall, L1 aWright, E P1 aStark, D1 aSelby, P1 aSharpe, M uhttp://www.iacat.org/content/initial-development-item-bank-assess-and-screen-psychological-distress-cancer-patients00408nas a2200097 4500008004100000245004200041210004200083260009800125100001600223856007100239 2007 eng d00aNonparametric online item calibration0 aNonparametric online item calibration aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing. 1 aSamejima, F uhttp://www.iacat.org/content/nonparametric-online-item-calibration00585nas a2200121 4500008004100000245009300041210006900134260009700203100001300300700001600313700001900329856011500348 2007 eng d00aUp-and-down procedures for approximating optimal designs using person-response functions0 aUpanddown procedures for approximating optimal designs using per aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aSheng, Y1 aFlournoy, N1 aOsterlind, S J uhttp://www.iacat.org/content/and-down-procedures-approximating-optimal-designs-using-person-response-functions02403nas a2200241 4500008004100000020002200041245008500063210006900148260002500217300001200242490000700254520161500261653000801876653003401884653002601918653003001944653002601974100001402000700001402014700001602028700001502044856010202059 2006 eng d a0439-755X (Print)00aThe comparison among item selection strategies of CAT with multiple-choice items0 acomparison among item selection strategies of CAT with multiplec bScience Press: China a778-7830 v383 aThe initial purpose of comparing item selection strategies for CAT was to increase the efficiency of tests. As studies continued, however, it was found that increasing the efficiency of item bank using was also an important goal of comparing item selection strategies. These two goals often conflicted. The key solution was to find a strategy with which both goals could be accomplished. The item selection strategies for graded response model in this study included: the average of the difficulty orders matching with the ability; the medium of the difficulty orders matching with the ability; maximum information; A stratified (average); and A stratified (medium). The evaluation indexes used for comparison included: the bias of ability estimates for the true; the standard error of ability estimates; the average items which the examinees have administered; the standard deviation of the frequency of items selected; and sum of the indices weighted. Using the Monte Carlo simulation method, we obtained some data and computer iterated the data 20 times each under the conditions that the item difficulty parameters followed the normal distribution and even distribution. The results were as follows; The results indicated that no matter difficulty parameters followed the normal distribution or even distribution. Every type of item selection strategies designed in this research had its strong and weak points. In general evaluation, under the condition that items were stratified appropriately, A stratified (medium) (ASM) had the best effect. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aCAT10acomputerized adaptive testing10agraded response model10aitem selection strategies10amultiple choice items1 aHai-qi, D1 aDe-zhi, C1 aShuliang, D1 aTaiping, D uhttp://www.iacat.org/content/comparison-among-item-selection-strategies-cat-multiple-choice-items00642nas a2200169 4500008004100000020001300041245013500054210006900189300001400258490000700272100001300279700001000292700001800302700001400320700001300334856012500347 2006 eng d a0895435600aComputer adaptive testing improved accuracy and precision of scores over random item selection in a physical functioning item bank0 aComputer adaptive testing improved accuracy and precision of sco a1174-11820 v591 aHaley, S1 aNi, P1 aHambleton, RK1 aSlavin, M1 aJette, A uhttp://www.iacat.org/content/computer-adaptive-testing-improved-accuracy-and-precision-scores-over-random-item-selection02652nas a2200397 4500008004100000020002200041245013500063210006900198250001500267260000800282300001200290490000700302520140700309653002601716653003101742653001501773653001001788653000901798653002201807653002501829653003301854653001101887653001101898653000901909653001601918653004601934653003001980653003102010653001302041100001502054700001002069700001802079700001602097700001502113856012602128 2006 eng d a0895-4356 (Print)00aComputer adaptive testing improved accuracy and precision of scores over random item selection in a physical functioning item bank0 aComputer adaptive testing improved accuracy and precision of sco a2006/10/10 cNov a1174-820 v593 aBACKGROUND AND OBJECTIVE: Measuring physical functioning (PF) within and across postacute settings is critical for monitoring outcomes of rehabilitation; however, most current instruments lack sufficient breadth and feasibility for widespread use. Computer adaptive testing (CAT), in which item selection is tailored to the individual patient, holds promise for reducing response burden, yet maintaining measurement precision. We calibrated a PF item bank via item response theory (IRT), administered items with a post hoc CAT design, and determined whether CAT would improve accuracy and precision of score estimates over random item selection. METHODS: 1,041 adults were interviewed during postacute care rehabilitation episodes in either hospital or community settings. Responses for 124 PF items were calibrated using IRT methods to create a PF item bank. We examined the accuracy and precision of CAT-based scores compared to a random selection of items. RESULTS: CAT-based scores had higher correlations with the IRT-criterion scores, especially with short tests, and resulted in narrower confidence intervals than scores based on a random selection of items; gains, as expected, were especially large for low and high performing adults. CONCLUSION: The CAT design may have important precision and efficiency advantages for point-of-care functional assessment in rehabilitation practice settings.10a*Recovery of Function10aActivities of Daily Living10aAdolescent10aAdult10aAged10aAged, 80 and over10aConfidence Intervals10aFactor Analysis, Statistical10aFemale10aHumans10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aRehabilitation/*standards10aReproducibility of Results10aSoftware1 aHaley, S M1 aNi, P1 aHambleton, RK1 aSlavin, M D1 aJette, A M uhttp://www.iacat.org/content/computer-adaptive-testing-improved-accuracy-and-precision-scores-over-random-item-selectio-003329nas a2200469 4500008004100000020002200041245011600063210006900179250001500248260000800263300001200271490000700283520189400290653003202184653003102216653002202247653002002269653001002289653000902299653002202308653002802330653003302358653001102391653001102402653002502413653000902438653001602447653004602463653002202509653002402531653003002555653002902585100001502614700001502629700001602644700001102660700002402671700001402695700001802709700001002727856012202737 2006 eng d a0003-9993 (Print)00aComputerized adaptive testing for follow-up after discharge from inpatient rehabilitation: I. Activity outcomes0 aComputerized adaptive testing for followup after discharge from  a2006/08/01 cAug a1033-420 v873 aOBJECTIVE: To examine score agreement, precision, validity, efficiency, and responsiveness of a computerized adaptive testing (CAT) version of the Activity Measure for Post-Acute Care (AM-PAC-CAT) in a prospective, 3-month follow-up sample of inpatient rehabilitation patients recently discharged home. DESIGN: Longitudinal, prospective 1-group cohort study of patients followed approximately 2 weeks after hospital discharge and then 3 months after the initial home visit. SETTING: Follow-up visits conducted in patients' home setting. PARTICIPANTS: Ninety-four adults who were recently discharged from inpatient rehabilitation, with diagnoses of neurologic, orthopedic, and medically complex conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Summary scores from AM-PAC-CAT, including 3 activity domains of movement and physical, personal care and instrumental, and applied cognition were compared with scores from a traditional fixed-length version of the AM-PAC with 66 items (AM-PAC-66). RESULTS: AM-PAC-CAT scores were in good agreement (intraclass correlation coefficient model 3,1 range, .77-.86) with scores from the AM-PAC-66. On average, the CAT programs required 43% of the time and 33% of the items compared with the AM-PAC-66. Both formats discriminated across functional severity groups. The standardized response mean (SRM) was greater for the movement and physical fixed form than the CAT; the effect size and SRM of the 2 other AM-PAC domains showed similar sensitivity between CAT and fixed formats. Using patients' own report as an anchor-based measure of change, the CAT and fixed length formats were comparable in responsiveness to patient-reported change over a 3-month interval. CONCLUSIONS: Accurate estimates for functional activity group-level changes can be obtained from CAT administrations, with a considerable reduction in administration time.10a*Activities of Daily Living10a*Adaptation, Physiological10a*Computer Systems10a*Questionnaires10aAdult10aAged10aAged, 80 and over10aChi-Square Distribution10aFactor Analysis, Statistical10aFemale10aHumans10aLongitudinal Studies10aMale10aMiddle Aged10aOutcome Assessment (Health Care)/*methods10aPatient Discharge10aProspective Studies10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aSiebens, H1 aCoster, W J1 aTao, W1 aBlack-Schaffer, R M1 aGandek, B1 aSinclair, S J1 aNi, P uhttp://www.iacat.org/content/computerized-adaptive-testing-follow-after-discharge-inpatient-rehabilitation-i-activity03166nas a2200361 4500008004100000020002200041245013600063210006900199250001500268260000800283300001200291490000700303520206800310653001502378653002402393653002102417653001002438653000902448653002902457653003402486653002402520653001102544653001102555653001302566653000902579653001602588100001602604700001302620700002302633700001202656700001102668856012502679 2006 eng d a0962-9343 (Print)00aComputerized adaptive testing of diabetes impact: a feasibility study of Hispanics and non-Hispanics in an active clinic population0 aComputerized adaptive testing of diabetes impact a feasibility s a2006/10/13 cNov a1503-180 v153 aBACKGROUND: Diabetes is a leading cause of death and disability in the US and is twice as common among Hispanic Americans as non-Hispanics. The societal costs of diabetes provide an impetus for developing tools that can improve patient care and delay or prevent diabetes complications. METHODS: We implemented a feasibility study of a Computerized Adaptive Test (CAT) to measure diabetes impact using a sample of 103 English- and 97 Spanish-speaking patients (mean age = 56.5, 66.5% female) in a community medical center with a high proportion of minority patients (28% African-American). The 37 items of the Diabetes Impact Survey were translated using forward-backward translation and cognitive debriefing. Participants were randomized to receive either the full-length tool or the Diabetes-CAT first, in the patient's native language. RESULTS: The number of items and the amount of time to complete the survey for the CAT was reduced to one-sixth the amount for the full-length tool in both languages, across disease severity. Confirmatory Factor Analysis confirmed that the Diabetes Impact Survey is unidimensional. The Diabetes-CAT demonstrated acceptable internal consistency reliability, construct validity, and discriminant validity in the overall sample, although subgroup analyses suggested that the English sample data evidenced higher levels of reliability and validity than the Spanish sample and issues with discriminant validity in the Spanish sample. Differential Item Function analysis revealed differences in responses tendencies by language group in 3 of the 37 items. Participant interviews suggested that the Spanish-speaking patients generally preferred the paper survey to the computer-assisted tool, and were twice as likely to experience difficulties understanding the items. CONCLUSIONS: While the Diabetes-CAT demonstrated clear advantages in reducing respondent burden as compared to the full-length tool, simplifying the item bank will be necessary for enhancing the feasibility of the Diabetes-CAT for use with low literacy patients.10a*Computers10a*Hispanic Americans10a*Quality of Life10aAdult10aAged10aData Collection/*methods10aDiabetes Mellitus/*psychology10aFeasibility Studies10aFemale10aHumans10aLanguage10aMale10aMiddle Aged1 aSchwartz, C1 aWelch, G1 aSantiago-Kelley, P1 aBode, R1 aSun, X uhttp://www.iacat.org/content/computerized-adaptive-testing-diabetes-impact-feasibility-study-hispanics-and-non-hispanics02132nas 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-002398nas 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-research03383nas a2200205 4500008004100000020002200041245009700063210006900160260002500229300001200254490000700266520266000273653003402933653002802967100001502995700001903010700001703029700001403046856011703060 2006 eng d a0439-755X (Print)00a[Item Selection Strategies of Computerized Adaptive Testing based on Graded Response Model.]0 aItem Selection Strategies of Computerized Adaptive Testing based bScience Press: China a461-4670 v383 aItem selection strategy (ISS) is an important component of Computerized Adaptive Testing (CAT). Its performance directly affects the security, efficiency and precision of the test. Thus, ISS becomes one of the central issues in CATs based on the Graded Response Model (GRM). It is well known that the goal of IIS is to administer the next unused item remaining in the item bank that best fits the examinees current ability estimate. In dichotomous IRT models, every item has only one difficulty parameter and the item whose difficulty matches the examinee's current ability estimate is considered to be the best fitting item. However, in GRM, each item has more than two ordered categories and has no single value to represent the item difficulty. Consequently, some researchers have used to employ the average or the median difficulty value across categories as the difficulty estimate for the item. Using the average value and the median value in effect introduced two corresponding ISSs. In this study, we used computer simulation compare four ISSs based on GRM. We also discussed the effect of "shadow pool" on the uniformity of pool usage as well as the influence of different item parameter distributions and different ability estimation methods on the evaluation criteria of CAT. In the simulation process, Monte Carlo method was adopted to simulate the entire CAT process; 1,000 examinees drawn from standard normal distribution and four 1,000-sized item pools of different item parameter distributions were also simulated. The assumption of the simulation is that a polytomous item is comprised of six ordered categories. In addition, ability estimates were derived using two methods. They were expected a posteriori Bayesian (EAP) and maximum likelihood estimation (MLE). In MLE, the Newton-Raphson iteration method and the Fisher Score iteration method were employed, respectively, to solve the likelihood equation. Moreover, the CAT process was simulated with each examinee 30 times to eliminate random error. The IISs were evaluated by four indices usually used in CAT from four aspects--the accuracy of ability estimation, the stability of IIS, the usage of item pool, and the test efficiency. Simulation results showed adequate evaluation of the ISS that matched the estimate of an examinee's current trait level with the difficulty values across categories. Setting "shadow pool" in ISS was able to improve the uniformity of pool utilization. Finally, different distributions of the item parameter and different ability estimation methods affected the evaluation indices of CAT. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aitem selection strategy1 aPing, Chen1 aShuliang, Ding1 aHaijing, Lin1 aJie, Zhou uhttp://www.iacat.org/content/item-selection-strategies-computerized-adaptive-testing-based-graded-response-model02405nas a2200337 4500008004100000020002200041245010800063210006900171250001500240260000800255300001100263490000700274520139300281653002101674653002101695653001001716653001101726653001801737653001101755653000901766653001601775653003001791653002801821100001801849700001701867700001801884700001401902700001701916700001701933856011701950 2006 eng d a0962-9343 (Print)00aMultidimensional computerized adaptive testing of the EORTC QLQ-C30: basic developments and evaluations0 aMultidimensional computerized adaptive testing of the EORTC QLQC a2006/03/21 cApr a315-290 v153 aOBJECTIVE: Self-report questionnaires are widely used to measure health-related quality of life (HRQOL). Ideally, such questionnaires should be adapted to the individual patient and at the same time scores should be directly comparable across patients. This may be achieved using computerized adaptive testing (CAT). Usually, CAT is carried out for a single domain at a time. However, many HRQOL domains are highly correlated. Multidimensional CAT may utilize these correlations to improve measurement efficiency. We investigated the possible advantages and difficulties of multidimensional CAT. STUDY DESIGN AND SETTING: We evaluated multidimensional CAT of three scales from the EORTC QLQ-C30: the physical functioning, emotional functioning, and fatigue scales. Analyses utilised a database with 2958 European cancer patients. RESULTS: It was possible to obtain scores for the three domains with five to seven items administered using multidimensional CAT that were very close to the scores obtained using all 12 items and with no or little loss of measurement precision. CONCLUSION: The findings suggest that multidimensional CAT may significantly improve measurement precision and efficiency and encourage further research into multidimensional CAT. Particularly, the estimation of the model underlying the multidimensional CAT and the conceptual aspects need further investigations.10a*Quality of Life10a*Self Disclosure10aAdult10aFemale10aHealth Status10aHumans10aMale10aMiddle Aged10aQuestionnaires/*standards10aUser-Computer Interface1 aPetersen, M A1 aGroenvold, M1 aAaronson, N K1 aFayers, P1 aSprangers, M1 aBjorner, J B uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-eortc-qlq-c30-basic-developments-and00404nas a2200121 4500008003900000245005500039210005300094300001200147490000700159100001900166700003100185856006600216 2006 d00aMultistage Testing: Widely or Narrowly Applicable?0 aMultistage Testing Widely or Narrowly Applicable a257-2600 v191 aStark, Stephen1 aChernyshenko, Oleksandr, S uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_600595nas a2200145 4500008004100000245013800041210006900179300001200248490000700260100001200267700001600279700001500295700001700310856012200327 2006 eng d00aSimulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with lumbar sp a947-9560 v591 aHart, D1 aMioduski, J1 aWerenke, M1 aStratford, P uhttp://www.iacat.org/content/simulated-computerized-adaptive-test-patients-lumbar-spine-impairments-was-efficient-and02111nas a2200229 4500008004100000245013800041210006900179300001400248490000700262520127000269653003101539653003401570653002501604653001701629653001901646653002401665100001401689700001801703700001701721700001901738856012401757 2006 eng d00aSimulated computerized adaptive test for patients with lumbar spine impairments was efficient and produced valid measures of function0 aSimulated computerized adaptive test for patients with lumbar sp a947–9560 v593 aObjective: To equate physical functioning (PF) items with Back Pain Functional Scale (BPFS) items, develop a computerized adaptive test (CAT) designed to assess lumbar spine functional status (LFS) in people with lumbar spine impairments, and compare discriminant validity of LFS measures (qIRT) generated using all items analyzed with a rating scale Item Response Theory model (RSM) and measures generated using the simulated CAT (qCAT). Methods: We performed a secondary analysis of retrospective intake rehabilitation data. Results: Unidimensionality and local independence of 25 BPFS and PF items were supported. Differential item functioning was negligible for levels of symptom acuity, gender, age, and surgical history. The RSM fit the data well. A lumbar spine specific CAT was developed that was 72% more efficient than using all 25 items to estimate LFS measures. qIRT and qCAT measures did not discriminate patients by symptom acuity, age, or gender, but discriminated patients by surgical history in similar clinically logical ways. qCAT measures were as precise as qIRT measures. Conclusion: A body part specific simulated CAT developed from an LFS item bank was efficient and produced precise measures of LFS without eroding discriminant validity.10aBack Pain Functional Scale10acomputerized adaptive testing10aItem Response Theory10aLumbar spine10aRehabilitation10aTrue-score equating1 aHart, D L1 aMioduski, J E1 aWerneke, M W1 aStratford, P W uhttp://www.iacat.org/content/simulated-computerized-adaptive-test-patients-lumbar-spine-impairments-was-efficient-and-000587nas a2200121 4500008004100000245016300041210006900204260001800273100001800291700001600309700001400325856012600339 2006 eng d00aA variant of the progressive restricted item exposure control procedure in computerized adaptive testing systems based on the 3PL and the partial credit model0 avariant of the progressive restricted item exposure control proc aSan Francisco1 aMcClarty, L K1 aSperling, R1 aDodd, B G uhttp://www.iacat.org/content/variant-progressive-restricted-item-exposure-control-procedure-computerized-adaptive-testing01469nas a2200217 4500008004100000245015400041210006900195260004600264300001200310520063100322653003000953653001100983653002500994653001601019653002201035653002301057100001801080700001501098700001401113856012401127 2005 eng d00aApplications of item response theory to improve health outcomes assessment: Developing item banks, linking instruments, and computer-adaptive testing0 aApplications of item response theory to improve health outcomes  aCambridge, UKbCambridge University Press a445-4643 a(From the chapter) The current chapter builds on Reise's introduction to the basic concepts, assumptions, popular models, and important features of IRT and discusses the applications of item response theory (IRT) modeling to health outcomes assessment. In particular, we highlight the critical role of IRT modeling in: developing an instrument to match a study's population; linking two or more instruments measuring similar constructs on a common metric; and creating item banks that provide the foundation for tailored short-form instruments or for computerized adaptive assessments. (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aHealth10aItem Response Theory10aMeasurement10aTest Construction10aTreatment Outcomes1 aHambleton, RK1 aGotay, C C1 aSnyder, C uhttp://www.iacat.org/content/applications-item-response-theory-improve-health-outcomes-assessment-developing-item-banks02791nas a2200469 4500008004100000020002200041245010400063210006900167250001500236260000800251300001200259490000700271520132800278653002201606653003101628653001501659653001601674653001001690653003401700653002101734653002401755653002501779653001501804653001101819653005301830653002901883653001101912653001101923653002001934653000901954653003101963653004601994653003102040653001402071653003202085100001502117700001002132700002502142700001702167700001302184856012402197 2005 eng d a0012-1622 (Print)00aA computer adaptive testing approach for assessing physical functioning in children and adolescents0 acomputer adaptive testing approach for assessing physical functi a2005/02/15 cFeb a113-1200 v473 aThe purpose of this article is to demonstrate: (1) the accuracy and (2) the reduction in amount of time and effort in assessing physical functioning (self-care and mobility domains) of children and adolescents using computer-adaptive testing (CAT). A CAT algorithm selects questions directly tailored to the child's ability level, based on previous responses. Using a CAT algorithm, a simulation study was used to determine the number of items necessary to approximate the score of a full-length assessment. We built simulated CAT (5-, 10-, 15-, and 20-item versions) for self-care and mobility domains and tested their accuracy in a normative sample (n=373; 190 males, 183 females; mean age 6y 11mo [SD 4y 2m], range 4mo to 14y 11mo) and a sample of children and adolescents with Pompe disease (n=26; 21 males, 5 females; mean age 6y 1mo [SD 3y 10mo], range 5mo to 14y 10mo). Results indicated that comparable score estimates (based on computer simulations) to the full-length tests can be achieved in a 20-item CAT version for all age ranges and for normative and clinical samples. No more than 13 to 16% of the items in the full-length tests were needed for any one administration. These results support further consideration of using CAT programs for accurate and efficient clinical assessments of physical functioning.10a*Computer Systems10aActivities of Daily Living10aAdolescent10aAge Factors10aChild10aChild Development/*physiology10aChild, Preschool10aComputer Simulation10aConfidence Intervals10aDemography10aFemale10aGlycogen Storage Disease Type II/physiopathology10aHealth Status Indicators10aHumans10aInfant10aInfant, Newborn10aMale10aMotor Activity/*physiology10aOutcome Assessment (Health Care)/*methods10aReproducibility of Results10aSelf Care10aSensitivity and Specificity1 aHaley, S M1 aNi, P1 aFragala-Pinkham, M A1 aSkrinar, A M1 aCorzo, D uhttp://www.iacat.org/content/computer-adaptive-testing-approach-assessing-physical-functioning-children-and-adolescents01564nas a2200157 4500008003900000245014400039210006900183300001200252490000700264520099200271100002101263700002101284700002701305700002101332856005301353 2005 d00aComputerized Adaptive Testing With the Partial Credit Model: Estimation Procedures, Population Distributions, and Item Pool Characteristics0 aComputerized Adaptive Testing With the Partial Credit Model Esti a433-4560 v293 a

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

1 aGorin, Joanna, S1 aDodd, Barbara, G1 aFitzpatrick, Steven, J1 aShieh, Yann Yann uhttp://apm.sagepub.com/content/29/6/433.abstract00601nas a2200145 4500008004100000245014400041210006900185300001200254490000700266100001300273700001400286700002100300700001500321856011900336 2005 eng d00aComputerized adaptive testing with the partial credit model: Estimation procedures, population distributions, and item pool characteristics0 aComputerized adaptive testing with the partial credit model Esti a533-5460 v291 aGorin, J1 aDodd, B G1 aFitzpatrick, S J1 aShieh, Y Y uhttp://www.iacat.org/content/computerized-adaptive-testing-partial-credit-model-estimation-procedures-population-002241nas a2200217 4500008004100000020002200041245014200063210006900205260004100274300001200315490000700327520142600334653001401760653003401774653002301808653001601831653002701847100001201874700001701886856012001903 2005 eng d a0022-0655 (Print)00aIncreasing the homogeneity of CAT's item-exposure rates by minimizing or maximizing varied target functions while assembling shadow tests0 aIncreasing the homogeneity of CATs itemexposure rates by minimiz bBlackwell Publishing: United Kingdom a245-2690 v423 aA computerized adaptive testing (CAT) algorithm that has the potential to increase the homogeneity of CATs item-exposure rates without significantly sacrificing the precision of ability estimates was proposed and assessed in the shadow-test (van der Linden & Reese, 1998) CAT context. This CAT algorithm was formed by a combination of maximizing or minimizing varied target functions while assembling shadow tests. There were four target functions to be separately used in the first, second, third, and fourth quarter test of CAT. The elements to be used in the four functions were associated with (a) a random number assigned to each item, (b) the absolute difference between an examinee's current ability estimate and an item difficulty, (c) the absolute difference between an examinee's current ability estimate and an optimum item difficulty, and (d) item information. The results indicated that this combined CAT fully utilized all the items in the pool, reduced the maximum exposure rates, and achieved more homogeneous exposure rates. Moreover, its precision in recovering ability estimates was similar to that of the maximum item-information method. The combined CAT method resulted in the best overall results compared with the other individual CAT item-selection methods. The findings from the combined CAT are encouraging. Future uses are discussed. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aalgorithm10acomputerized adaptive testing10aitem exposure rate10ashadow test10avaried target function1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/increasing-homogeneity-cats-item-exposure-rates-minimizing-or-maximizing-varied-target02443nas a2200373 4500008004100000020004100041245008200082210006900164250001500233260000800248300001000256490000700266520136700273653001001640653000901650653002201659653003301681653003301714653001101747653001101758653000901769653001601778653004001794653001801834653001901852100001301871700001301884700001401897700001201911700001701923700001601940700001501956856009801971 2005 eng d a0895-4356 (Print)0895-4356 (Linking)00aAn item bank was created to improve the measurement of cancer-related fatigue0 aitem bank was created to improve the measurement of cancerrelate a2005/02/01 cFeb a190-70 v583 aOBJECTIVE: Cancer-related fatigue (CRF) is one of the most common unrelieved symptoms experienced by patients. CRF is underrecognized and undertreated due to a lack of clinically sensitive instruments that integrate easily into clinics. Modern computerized adaptive testing (CAT) can overcome these obstacles by enabling precise assessment of fatigue without requiring the administration of a large number of questions. A working item bank is essential for development of a CAT platform. The present report describes the building of an operational item bank for use in clinical settings with the ultimate goal of improving CRF identification and treatment. STUDY DESIGN AND SETTING: The sample included 301 cancer patients. Psychometric properties of items were examined by using Rasch analysis, an Item Response Theory (IRT) model. RESULTS AND CONCLUSION: The final bank includes 72 items. These 72 unidimensional items explained 57.5% of the variance, based on factor analysis results. Excellent internal consistency (alpha=0.99) and acceptable item-total correlation were found (range: 0.51-0.85). The 72 items covered a reasonable range of the fatigue continuum. No significant ceiling effects, floor effects, or gaps were found. A sample short form was created for demonstration purposes. The resulting bank is amenable to the development of a CAT platform.10aAdult10aAged10aAged, 80 and over10aFactor Analysis, Statistical10aFatigue/*etiology/psychology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/*complications/psychology10aPsychometrics10aQuestionnaires1 aLai, J-S1 aCella, D1 aDineen, K1 aBode, R1 aVon Roenn, J1 aGershon, RC1 aShevrin, D uhttp://www.iacat.org/content/item-bank-was-created-improve-measurement-cancer-related-fatigue01315nas a2200229 4500008004100000020002200041245007700063210006900140260002500209300001200234490000700246520057900253653002700832653003000859653002500889100001100914700001600925700001500941700001300956700001500969856010100984 2005 eng d a0439-755X (Print)00a[Item characteristic curve equating under graded response models in IRT]0 aItem characteristic curve equating under graded response models  bScience Press: China a832-8380 v373 aIn one of the largest qualificatory tests--economist test, to guarantee the comparability among different years, construct item bank and prepare for computerized adaptive testing, item characteristic curve equating and anchor test equating design under graded models in IRT are used, which have realized the item and ability parameter equating of test data in five years and succeeded in establishing an item bank. Based on it, cut scores of different years are compared by equating and provide demonstrational gist to constitute the eligibility standard of economist test. 10agraded response models10aitem characteristic curve10aItem Response Theory1 aJun, Z1 aDongming, O1 aShuyuan, X1 aHaiqi, D1 aShuqing, Q uhttp://www.iacat.org/content/item-characteristic-curve-equating-under-graded-response-models-irt00559nas a2200145 4500008003900000245011100039210006900150300001000219490000700229100001400236700001400250700001800264700001700282856011400299 2005 d00aItem response theory in computer adaptive testing: implications for outcomes measurement in rehabilitation0 aItem response theory in computer adaptive testing implications f a71-780 v501 aWare, J E1 aGandek, B1 aSinclair, S J1 aBjorner, J B uhttp://www.iacat.org/content/item-response-theory-computer-adaptive-testing-implications-outcomes-measurement01743nas a2200229 4500008004100000245008300041210006900124300001100193490000700204520103000211653003401241100001301275700001401288700001501302700001701317700001501334700001501349700001401364700001301378700001301391856010901404 2005 eng d00aAn item response theory-based pain item bank can enhance measurement precision0 aitem response theorybased pain item bank can enhance measurement a278-880 v303 aCancer-related pain is often under-recognized and undertreated. This is partly due to the lack of appropriate assessments, which need to be comprehensive and precise yet easily integrated into clinics. Computerized adaptive testing (CAT) can enable precise-yet-brief assessments by only selecting the most informative items from a calibrated item bank. The purpose of this study was to create such a bank. The sample included 400 cancer patients who were asked to complete 61 pain-related items. Data were analyzed using factor analysis and the Rasch model. The final bank consisted of 43 items which satisfied the measurement requirement of factor analysis and the Rasch model, demonstrated high internal consistency and reasonable item-total correlations, and discriminated patients with differing degrees of pain. We conclude that this bank demonstrates good psychometric properties, is sensitive to pain reported by patients, and can be used as the foundation for a CAT pain-testing platform for use in clinical practice.10acomputerized adaptive testing1 aLai, J-S1 aDineen, K1 aReeve, B B1 aVon Roenn, J1 aShervin, D1 aMcGuire, M1 aBode, R K1 aPaice, J1 aCella, D uhttp://www.iacat.org/content/item-response-theory-based-pain-item-bank-can-enhance-measurement-precision02902nas a2200409 4500008004100000245012300041210006900164260000800233300001000241490000700251520159700258653004701855653001001902653000901912653001901921653003101940653002601971653001101997653002902008653001102037653000902048653001602057653003902073653001402112653002502126653002702151653003002178653003202208653002802240653002202268100001502290700001602305700001702321700001602338700001502354856012302369 2005 eng d00aMeasuring physical function in patients with complex medical and postsurgical conditions: a computer adaptive approach0 aMeasuring physical function in patients with complex medical and cOct a741-80 v843 aOBJECTIVE: To examine whether the range of disability in the medically complex and postsurgical populations receiving rehabilitation is adequately sampled by the new Activity Measure--Post-Acute Care (AM-PAC), and to assess whether computer adaptive testing (CAT) can derive valid patient scores using fewer questions. DESIGN: Observational study of 158 subjects (mean age 67.2 yrs) receiving skilled rehabilitation services in inpatient (acute rehabilitation hospitals, skilled nursing facility units) and community (home health services, outpatient departments) settings for recent-onset or worsening disability from medical (excluding neurological) and surgical (excluding orthopedic) conditions. Measures were interviewer-administered activity questions (all patients) and physical functioning portion of the SF-36 (outpatients) and standardized chart items (11 Functional Independence Measure (FIM), 19 Standardized Outcome and Assessment Information Set (OASIS) items, and 22 Minimum Data Set (MDS) items). Rasch modeling analyzed all data and the relationship between person ability estimates and average item difficulty. CAT assessed the ability to derive accurate patient scores using a sample of questions. RESULTS: The 163-item activity item pool covered the range of physical movement and personal and instrumental activities. CAT analysis showed comparable scores between estimates using 10 items or the total item pool. CONCLUSION: The AM-PAC can assess a broad range of function in patients with complex medical illness. CAT achieves valid patient scores using fewer questions.10aActivities of Daily Living/*classification10aAdult10aAged10aCohort Studies10aContinuity of Patient Care10aDisability Evaluation10aFemale10aHealth Services Research10aHumans10aMale10aMiddle Aged10aPostoperative Care/*rehabilitation10aPrognosis10aRecovery of Function10aRehabilitation Centers10aRehabilitation/*standards10aSensitivity and Specificity10aSickness Impact Profile10aTreatment Outcome1 aSiebens, H1 aAndres, P L1 aPengsheng, N1 aCoster, W J1 aHaley, S M uhttp://www.iacat.org/content/measuring-physical-function-patients-complex-medical-and-postsurgical-conditions-computer02720nas a2200373 4500008004100000245017500041210006900216300001100285490000700296520137800303653003001681653003101711653001501742653001001757653000901767653002201776653003201798653004201830653001101872653003001883653001101913653005101924653003101975653003702006653000902043653001602052653004102068653004102109653002602150100001402176700001802190700001902208856011902227 2005 eng d00aSimulated computerized adaptive tests for measuring functional status were efficient with good discriminant validity in patients with hip, knee, or foot/ankle impairments0 aSimulated computerized adaptive tests for measuring functional s a629-380 v583 aBACKGROUND AND OBJECTIVE: To develop computerized adaptive tests (CATs) designed to assess lower extremity functional status (FS) in people with lower extremity impairments using items from the Lower Extremity Functional Scale and compare discriminant validity of FS measures generated using all items analyzed with a rating scale Item Response Theory model (theta(IRT)) and measures generated using the simulated CATs (theta(CAT)). METHODS: Secondary analysis of retrospective intake rehabilitation data. RESULTS: Unidimensionality of items was strong, and local independence of items was adequate. Differential item functioning (DIF) affected item calibration related to body part, that is, hip, knee, or foot/ankle, but DIF did not affect item calibration for symptom acuity, gender, age, or surgical history. Therefore, patients were separated into three body part specific groups. The rating scale model fit all three data sets well. Three body part specific CATs were developed: each was 70% more efficient than using all LEFS items to estimate FS measures. theta(IRT) and theta(CAT) measures discriminated patients by symptom acuity, age, and surgical history in similar ways. theta(CAT) measures were as precise as theta(IRT) measures. CONCLUSION: Body part-specific simulated CATs were efficient and produced precise measures of FS with good discriminant validity.10a*Health Status Indicators10aActivities of Daily Living10aAdolescent10aAdult10aAged10aAged, 80 and over10aAnkle Joint/physiopathology10aDiagnosis, Computer-Assisted/*methods10aFemale10aHip Joint/physiopathology10aHumans10aJoint Diseases/physiopathology/*rehabilitation10aKnee Joint/physiopathology10aLower Extremity/*physiopathology10aMale10aMiddle Aged10aResearch Support, N.I.H., Extramural10aResearch Support, U.S. Gov't, P.H.S.10aRetrospective Studies1 aHart, D L1 aMioduski, J E1 aStratford, P W uhttp://www.iacat.org/content/simulated-computerized-adaptive-tests-measuring-functional-status-were-efficient-good10201nas a2200553 4500008004100000245016300041210006900204300001400273490000700287520862500294653001808919653003208937100001608969700001608985700001409001700001609015700001409031700001509045700001609060700001409076700001509090700001509105700001409120700001709134700001709151700001709168700001609185700001709201700001609218700001509234700001609249700001709265700002309282700001609305700002209321700001609343700001609359700001709375700001309392700001509405700001309420700001609433700001209449700001409461700001609475700002009491700001209511856012409523 2005 eng d00aToward efficient and comprehensive measurement of the alcohol problems continuum in college students: The Brief Young Adult Alcohol Consequences Questionnaire0 aToward efficient and comprehensive measurement of the alcohol pr a1180-11890 v293 aBackground: Although a number of measures of alcohol problems in college students have been studied, the psychometric development and validation of these scales have been limited, for the most part, to methods based on classical test theory. In this study, we conducted analyses based on item response theory to select a set of items for measuring the alcohol problem severity continuum in college students that balances comprehensiveness and efficiency and is free from significant gender bias., Method: We conducted Rasch model analyses of responses to the 48-item Young Adult Alcohol Consequences Questionnaire by 164 male and 176 female college students who drank on at least a weekly basis. An iterative process using item fit statistics, item severities, item discrimination parameters, model residuals, and analysis of differential item functioning by gender was used to pare the items down to those that best fit a Rasch model and that were most efficient in discriminating among levels of alcohol problems in the sample., Results: The process of iterative Rasch model analyses resulted in a final 24-item scale with the data fitting the unidimensional Rasch model very well. The scale showed excellent distributional properties, had items adequately matched to the severity of alcohol problems in the sample, covered a full range of problem severity, and appeared highly efficient in retaining all of the meaningful variance captured by the original set of 48 items., Conclusions: The use of Rasch model analyses to inform item selection produced a final scale that, in both its comprehensiveness and its efficiency, should be a useful tool for researchers studying alcohol problems in college students. To aid interpretation of raw scores, examples of the types of alcohol problems that are likely to be experienced across a range of selected scores are provided., (C)2005Research Society on AlcoholismAn important, sometimes controversial feature of all psychological phenomena is whether they are categorical or dimensional. A conceptual and psychometric framework is described for distinguishing whether the latent structure behind manifest categories (e.g., psychiatric diagnoses, attitude groups, or stages of development) is category-like or dimension-like. Being dimension-like requires (a) within-category heterogeneity and (b) between-category quantitative differences. Being category-like requires (a) within-category homogeneity and (b) between-category qualitative differences. The relation between this classification and abrupt versus smooth differences is discussed. Hybrid structures are possible. Being category-like is itself a matter of degree; the authors offer a formalized framework to determine this degree. Empirical applications to personality disorders, attitudes toward capital punishment, and stages of cognitive development illustrate the approach., (C) 2005 by the American Psychological AssociationThe authors conducted Rasch model ( G. Rasch, 1960) analyses of items from the Young Adult Alcohol Problems Screening Test (YAAPST; S. C. Hurlbut & K. J. Sher, 1992) to examine the relative severity and ordering of alcohol problems in 806 college students. Items appeared to measure a single dimension of alcohol problem severity, covering a broad range of the latent continuum. Items fit the Rasch model well, with less severe symptoms reliably preceding more severe symptoms in a potential progression toward increasing levels of problem severity. However, certain items did not index problem severity consistently across demographic subgroups. A shortened, alternative version of the YAAPST is proposed, and a norm table is provided that allows for a linking of total YAAPST scores to expected symptom expression., (C) 2004 by the American Psychological AssociationA didactic on latent growth curve modeling for ordinal outcomes is presented. The conceptual aspects of modeling growth with ordinal variables and the notion of threshold invariance are illustrated graphically using a hypothetical example. The ordinal growth model is described in terms of 3 nested models: (a) multivariate normality of the underlying continuous latent variables (yt) and its relationship with the observed ordinal response pattern (Yt), (b) threshold invariance over time, and (c) growth model for the continuous latent variable on a common scale. Algebraic implications of the model restrictions are derived, and practical aspects of fitting ordinal growth models are discussed with the help of an empirical example and Mx script ( M. C. Neale, S. M. Boker, G. Xie, & H. H. Maes, 1999). The necessary conditions for the identification of growth models with ordinal data and the methodological implications of the model of threshold invariance are discussed., (C) 2004 by the American Psychological AssociationRecent research points toward the viability of conceptualizing alcohol problems as arrayed along a continuum. Nevertheless, modern statistical techniques designed to scale multiple problems along a continuum (latent trait modeling; LTM) have rarely been applied to alcohol problems. This study applies LTM methods to data on 110 problems reported during in-person interviews of 1,348 middle-aged men (mean age = 43) from the general population. The results revealed a continuum of severity linking the 110 problems, ranging from heavy and abusive drinking, through tolerance and withdrawal, to serious complications of alcoholism. These results indicate that alcohol problems can be arrayed along a dimension of severity and emphasize the relevance of LTM to informing the conceptualization and assessment of alcohol problems., (C) 2004 by the American Psychological AssociationItem response theory (IRT) is supplanting classical test theory as the basis for measures development. This study demonstrated the utility of IRT for evaluating DSM-IV diagnostic criteria. Data on alcohol, cannabis, and cocaine symptoms from 372 adult clinical participants interviewed with the Composite International Diagnostic Interview-Expanded Substance Abuse Module (CIDI-SAM) were analyzed with Mplus ( B. Muthen & L. Muthen, 1998) and MULTILOG ( D. Thissen, 1991) software. Tolerance and legal problems criteria were dropped because of poor fit with a unidimensional model. Item response curves, test information curves, and testing of variously constrained models suggested that DSM-IV criteria in the CIDI-SAM discriminate between only impaired and less impaired cases and may not be useful to scale case severity. IRT can be used to study the construct validity of DSM-IV diagnoses and to identify diagnostic criteria with poor performance., (C) 2004 by the American Psychological AssociationThis study examined the psychometric characteristics of an index of substance use involvement using item response theory. The sample consisted of 292 men and 140 women who qualified for a Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; American Psychiatric Association, 1987) substance use disorder (SUD) diagnosis and 293 men and 445 women who did not qualify for a SUD diagnosis. The results indicated that men had a higher probability of endorsing substance use compared with women. The index significantly predicted health, psychiatric, and psychosocial disturbances as well as level of substance use behavior and severity of SUD after a 2-year follow-up. Finally, this index is a reliable and useful prognostic indicator of the risk for SUD and the medical and psychosocial sequelae of drug consumption., (C) 2002 by the American Psychological AssociationComparability, validity, and impact of loss of information of a computerized adaptive administration of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) were assessed in a sample of 140 Veterans Affairs hospital patients. The countdown method ( Butcher, Keller, & Bacon, 1985) was used to adaptively administer Scales L (Lie) and F (Frequency), the 10 clinical scales, and the 15 content scales. Participants completed the MMPI-2 twice, in 1 of 2 conditions: computerized conventional test-retest, or computerized conventional-computerized adaptive. Mean profiles and test-retest correlations across modalities were comparable. Correlations between MMPI-2 scales and criterion measures supported the validity of the countdown method, although some attenuation of validity was suggested for certain health-related items. Loss of information incurred with this mode of adaptive testing has minimal impact on test validity. Item and time savings were substantial., (C) 1999 by the American Psychological Association10aPsychometrics10aSubstance-Related Disorders1 aKahler, C W1 aStrong, D R1 aRead, J P1 aDe Boeck, P1 aWilson, M1 aActon, G S1 aPalfai, T P1 aWood, M D1 aMehta, P D1 aNeale, M C1 aFlay, B R1 aConklin, C A1 aClayton, R R1 aTiffany, S T1 aShiffman, S1 aKrueger, R F1 aNichol, P E1 aHicks, B M1 aMarkon, K E1 aPatrick, C J1 aIacono, William, G1 aMcGue, Matt1 aLangenbucher, J W1 aLabouvie, E1 aMartin, C S1 aSanjuan, P M1 aBavly, L1 aKirisci, L1 aChung, T1 aVanyukov, M1 aDunn, M1 aTarter, R1 aHandel, R W1 aBen-Porath, Y S1 aWatt, M uhttp://www.iacat.org/content/toward-efficient-and-comprehensive-measurement-alcohol-problems-continuum-college-students01434nas a2200133 4500008003900000245010900039210006900148300000900217490000700226520097600233100001601209700002401225856005101249 2005 d00aTrait Parameter Recovery Using Multidimensional Computerized Adaptive Testing in Reading and Mathematics0 aTrait Parameter Recovery Using Multidimensional Computerized Ada a3-250 v293 a

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

1 aLi, Yuan, H1 aSchafer, William, D uhttp://apm.sagepub.com/content/29/1/3.abstract01450nas a2200133 4500008004100000245012200041210006900163300001000232490001000242520092300252100001001175700001501185856011601200 2005 eng d00aValidation of a computerized adaptive testing version of the Schedule for Nonadaptive and Adaptive Personality (SNAP)0 aValidation of a computerized adaptive testing version of the Sch a28-430 v17(1)3 aThis is a validation study of a computerized adaptive (CAT) version of the Schedule for Nonadaptive and Adaptive Personality (SNAP) conducted with 413 undergraduates who completed the SNAP twice, 1 week apart. Participants were assigned randomly to 1 of 4 retest groups: (a) paper-and-pencil (P&P) SNAP, (b) CAT, (c) P&P/CAT, and (d) CAT/P&P. With number of items held constant, computerized administration had little effect on descriptive statistics, rank ordering of scores, reliability, and concurrent validity, but was preferred over P&P administration by most participants. CAT administration yielded somewhat lower precision and validity than P&P administration, but required 36% to 37% fewer items and 58% to 60% less time to complete. These results confirm not only key findings from previous CAT simulation studies of personality measures but extend them for the 1st time to a live assessment setting.1 aSimms1 aClark, L A uhttp://www.iacat.org/content/validation-computerized-adaptive-testing-version-schedule-nonadaptive-and-adaptive01451nas a2200133 4500008004100000245011400041210006900155300001000224490000700234520092000241100001501161700001501176856012601191 2005 eng d00aValidation of a computerized adaptive version of the Schedule of Non-Adaptive and Adaptive Personality (SNAP)0 aValidation of a computerized adaptive version of the Schedule of a28-430 v173 a This is a validation study of a computerized adaptive (CAT) version of the Schedule for Nonadaptive and Adaptive Personality (SNAP) conducted with 413 undergraduates who completed the SNAP twice, 1 week apart. Participants were assigned randomly to 1 of 4 retest groups: (a) paper-and-pencil (P&P) SNAP, (b) CAT, (c) P&P/CAT, and (d) CAT/P&P. With number of items held constant, computerized administration had little effect on descriptive statistics, rank ordering of scores, reliability, and concurrent validity, but was preferred over P&P administration by most participants. CAT administration yielded somewhat lower precision and validity than P&P administration, but required 36% to 37% fewer items and 58% to 60% less time to complete. These results confirm not only key findings from previous CAT simulation studies of personality measures but extend them for the 1st time to a live assessment setting. 1 aSimms, L J1 aClark, L J uhttp://www.iacat.org/content/validation-computerized-adaptive-version-schedule-non-adaptive-and-adaptive-personality-snap03707nas a2200481 4500008004100000245005200041210005200093300001200145490000700157520221100164653001902375653002902394653005802423653001002481653005302491653000902544653001102553653002502564653002602589653003302615653001102648653001002659653000902669653001602678653002402694653007402718653001802792653002902810653005802839653003102897653003202928653003602960653003202996100001503028700001603043700001603059700001603075700001003091700001403101700001803115700001503133856007703148 2004 eng d00aActivity outcome measurement for postacute care0 aActivity outcome measurement for postacute care aI49-1610 v423 aBACKGROUND: Efforts to evaluate the effectiveness of a broad range of postacute care services have been hindered by the lack of conceptually sound and comprehensive measures of outcomes. It is critical to determine a common underlying structure before employing current methods of item equating across outcome instruments for future item banking and computer-adaptive testing applications. OBJECTIVE: To investigate the factor structure, reliability, and scale properties of items underlying the Activity domains of the International Classification of Functioning, Disability and Health (ICF) for use in postacute care outcome measurement. METHODS: We developed a 41-item Activity Measure for Postacute Care (AM-PAC) that assessed an individual's execution of discrete daily tasks in his or her own environment across major content domains as defined by the ICF. We evaluated the reliability and discriminant validity of the prototype AM-PAC in 477 individuals in active rehabilitation programs across 4 rehabilitation settings using factor analyses, tests of item scaling, internal consistency reliability analyses, Rasch item response theory modeling, residual component analysis, and modified parallel analysis. RESULTS: Results from an initial exploratory factor analysis produced 3 distinct, interpretable factors that accounted for 72% of the variance: Applied Cognition (44%), Personal Care & Instrumental Activities (19%), and Physical & Movement Activities (9%); these 3 activity factors were verified by a confirmatory factor analysis. Scaling assumptions were met for each factor in the total sample and across diagnostic groups. Internal consistency reliability was high for the total sample (Cronbach alpha = 0.92 to 0.94), and for specific diagnostic groups (Cronbach alpha = 0.90 to 0.95). Rasch scaling, residual factor, differential item functioning, and modified parallel analyses supported the unidimensionality and goodness of fit of each unique activity domain. CONCLUSIONS: This 3-factor model of the AM-PAC can form the conceptual basis for common-item equating and computer-adaptive applications, leading to a comprehensive system of outcome instruments for postacute care settings.10a*Self Efficacy10a*Sickness Impact Profile10aActivities of Daily Living/*classification/psychology10aAdult10aAftercare/*standards/statistics & numerical data10aAged10aBoston10aCognition/physiology10aDisability Evaluation10aFactor Analysis, Statistical10aFemale10aHuman10aMale10aMiddle Aged10aMovement/physiology10aOutcome Assessment (Health Care)/*methods/statistics & numerical data10aPsychometrics10aQuestionnaires/standards10aRehabilitation/*standards/statistics & numerical data10aReproducibility of Results10aSensitivity and Specificity10aSupport, U.S. Gov't, Non-P.H.S.10aSupport, U.S. Gov't, P.H.S.1 aHaley, S M1 aCoster, W J1 aAndres, P L1 aLudlow, L H1 aNi, P1 aBond, T L1 aSinclair, S J1 aJette, A M uhttp://www.iacat.org/content/activity-outcome-measurement-postacute-care01341nas a2200145 4500008003900000245008200039210006900121300001200190490000700202520087300209100001601082700001901098700002101117856005701138 2004 d00aAdaptive Testing With Regression Trees in the Presence of Multidimensionality0 aAdaptive Testing With Regression Trees in the Presence of Multid a293-3160 v293 a

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

1 aYan, Duanli1 aLewis, Charles1 aStocking, Martha uhttp://jeb.sagepub.com/cgi/content/abstract/29/3/29302593nas a2200469 4500008004100000245007200041210006900113300001000182490000600192520108600198653002501284653001001309653001501319653002101334653002201355653005901377653007001436653003301506653001101539653001101550653001301561653000901574653002701583653002201610653005501632653001901687653001501706653006601721653001801787653003701805653004101842653003001883653001301913100001501926700001301941700001801954700001501972700001401987700001402001700001302015856009502028 2004 eng d00aComputerized adaptive measurement of depression: A simulation study0 aComputerized adaptive measurement of depression A simulation stu a13-230 v43 aBackground: Efficient, accurate instruments for measuring depression are increasingly importantin clinical practice. We developed a computerized adaptive version of the Beck DepressionInventory (BDI). We examined its efficiency and its usefulness in identifying Major DepressiveEpisodes (MDE) and in measuring depression severity.Methods: Subjects were 744 participants in research studies in which each subject completed boththe BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale.Results: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%,equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21items). The adaptive latent depression score correlated r = .92 with the BDI total score and thelatent depression score correlated more highly with the Hamilton (r = .74) than the BDI total scoredid (r = .70).Conclusions: Adaptive testing for depression may provide greatly increased efficiency withoutloss of accuracy in identifying MDE or in measuring depression severity.10a*Computer Simulation10aAdult10aAlgorithms10aArea Under Curve10aComparative Study10aDepressive Disorder/*diagnosis/epidemiology/psychology10aDiagnosis, Computer-Assisted/*methods/statistics & numerical data10aFactor Analysis, Statistical10aFemale10aHumans10aInternet10aMale10aMass Screening/methods10aPatient Selection10aPersonality Inventory/*statistics & numerical data10aPilot Projects10aPrevalence10aPsychiatric Status Rating Scales/*statistics & numerical data10aPsychometrics10aResearch Support, Non-U.S. Gov't10aResearch Support, U.S. Gov't, P.H.S.10aSeverity of Illness Index10aSoftware1 aGardner, W1 aShear, K1 aKelleher, K J1 aPajer, K A1 aMammen, O1 aBuysse, D1 aFrank, E uhttp://www.iacat.org/content/computerized-adaptive-measurement-depression-simulation-study00344nas a2200097 4500008004100000245003400041210003400075260005600109100001600165856006500181 2004 eng d00aComputerized adaptive testing0 aComputerized adaptive testing aEncyclopedia of social measurement. Academic Press.1 aSegall, D O uhttp://www.iacat.org/content/computerized-adaptive-testing-100512nas a2200109 4500008004100000245012200041210006900163260001700232100001200249700001700261856012400278 2004 eng d00aThe context effects of multidimensional CAT on the accuracy of multidimensional abilities and the item exposure rates0 acontext effects of multidimensional CAT on the accuracy of multi aSan Diego CA1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/context-effects-multidimensional-cat-accuracy-multidimensional-abilities-and-item-exposure01264nas a2200133 4500008004100000245007500041210006900116260000800185300001200193490000700205520080400212100001601016856009801032 2004 eng d00aA sharing item response theory model for computerized adaptive testing0 asharing item response theory model for computerized adaptive tes cWin a439-4600 v293 aA new sharing item response theory (SIRT) model is presented which explicitly models the effects of sharing item content between informants and testtakers. This model is used to construct adaptive item selection and scoring rules that provide increased precision and reduced score gains in instances where sharing occurs. The adaptive item selection rules are expressed as functions of the item’s exposure rate in addition to other commonly used properties (characterized by difficulty, discrimination, and guessing parameters). Based on the results of simulated item responses, the new item selection and scoring algorithms compare favorably to the Sympson-Hetter exposure control method. The new SIRT approach provides higher reliability and lower score gains in instances where sharing occurs.1 aSegall, D O uhttp://www.iacat.org/content/sharing-item-response-theory-model-computerized-adaptive-testing00433nas a2200121 4500008004100000245006600041210006600107300001200173490001000185100001300195700001500208856008800223 2004 eng d00aTest difficulty and stereotype threat on the GRE General Test0 aTest difficulty and stereotype threat on the GRE General Test a563-5970 v34(3)1 aStricker1 aBejar, I I uhttp://www.iacat.org/content/test-difficulty-and-stereotype-threat-gre-general-test00638nas a2200193 4500008004100000245009100041210006900132300000900201490000700210100001400217700001600231700001400247700001700261700002000278700001400298700001500312700001200327856010500339 2004 eng d00aValidating the German computerized adaptive test for anxiety on healthy sample (A-CAT)0 aValidating the German computerized adaptive test for anxiety on  a15150 v131 aBecker, J1 aWalter, O B1 aFliege, H1 aBjorner, J B1 aKocalevent, R D1 aSchmid, G1 aKlapp, B F1 aRose, M uhttp://www.iacat.org/content/validating-german-computerized-adaptive-test-anxiety-healthy-sample-cat00478nas a2200109 4500008004100000245009600041210006900137260001500206100001200221700001700233856011800250 2003 eng d00aAccuracy of reading and mathematics ability estimates under the shadow-test constraint MCAT0 aAccuracy of reading and mathematics ability estimates under the  aChicago IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/accuracy-reading-and-mathematics-ability-estimates-under-shadow-test-constraint-mcat00477nas a2200097 4500008004100000245012000041210006900161260001500230100001600245856011800261 2003 eng d00aAn adaptive exposure control algorithm for computerized adaptive testing using a sharing item response theory model0 aadaptive exposure control algorithm for computerized adaptive te aChicago IL1 aSegall, D O uhttp://www.iacat.org/content/adaptive-exposure-control-algorithm-computerized-adaptive-testing-using-sharing-item00418nas a2200097 4500008004100000245007500041210006900116260001500185100001600200856010400216 2003 eng d00aCalibrating CAT item pools and online pretest items using MCMC methods0 aCalibrating CAT item pools and online pretest items using MCMC m aChicago IL1 aSegall, D O uhttp://www.iacat.org/content/calibrating-cat-item-pools-and-online-pretest-items-using-mcmc-methods00483nas a2200109 4500008004100000245009300041210006900134260001500203100001700218700001600235856012200251 2003 eng d00aCalibrating CAT pools and online pretest items using marginal maximum likelihood methods0 aCalibrating CAT pools and online pretest items using marginal ma aChicago IL1 aPommerich, M1 aSegall, D O uhttp://www.iacat.org/content/calibrating-cat-pools-and-online-pretest-items-using-marginal-maximum-likelihood-methods00478nas a2200109 4500008004100000245007400041210006800115260005500183100001600238700001400254856010000268 2003 eng d00aCAT-ASVAB prototype Internet delivery system: Final report (FR-03-06)0 aCATASVAB prototype Internet delivery system Final report FR0306 aArlington VA: Human Resources Rsearch Organization1 aSticha, P J1 aBarber, G uhttp://www.iacat.org/content/cat-asvab-prototype-internet-delivery-system-final-report-fr-03-0600509nas a2200133 4500008004100000245008600041210006900127260001500196100001300211700001500224700001500239700001400254856010700268 2003 eng d00aComparison of multi-stage tests with computer adaptive and paper and pencil tests0 aComparison of multistage tests with computer adaptive and paper  aChicago IL1 aRotou, O1 aPatsula, L1 aSteffen, M1 aRizavi, S uhttp://www.iacat.org/content/comparison-multi-stage-tests-computer-adaptive-and-paper-and-pencil-tests01761nas a2200313 4500008004100000245007700041210006900118300001200187490000700199520083400206653002101040653001501061653001701076653001601093653003001109653001701139653001501156653002501171653002001196653001501216653002501231653001801256653000901274100001801283700001201301700001601313700001601329856010201345 2003 eng d00aComputerized adaptive rating scales for measuring managerial performance0 aComputerized adaptive rating scales for measuring managerial per a237-2460 v113 aComputerized adaptive rating scales (CARS) had been developed to measure contextual or citizenship performance. This rating format used a paired-comparison protocol, presenting pairs of behavioral statements scaled according to effectiveness levels, and an iterative item response theory algorithm to obtain estimates of ratees' citizenship performance (W. C. Borman et al, 2001). In the present research, we developed CARS to measure the entire managerial performance domain, including task and citizenship performance, thus addressing a major limitation of the earlier CARS. The paper describes this development effort, including an adjustment to the algorithm that reduces substantially the number of item pairs required to obtain almost as much precision in the performance estimates. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aAlgorithms10aAssociations10aCitizenship10aComputer Assisted Testing10aConstruction10aContextual10aItem Response Theory10aJob Performance10aManagement10aManagement Personnel10aRating Scales10aTest1 aSchneider, RJ1 aGoff, M1 aAnderson, S1 aBorman, W C uhttp://www.iacat.org/content/computerized-adaptive-rating-scales-measuring-managerial-performance00493nas a2200097 4500008004100000245013500041210006900176260001500245100001600260856011900276 2003 eng d00aCriterion item characteristic curve function for evaluating the differential weight procedure adjusted to on-line item calibration0 aCriterion item characteristic curve function for evaluating the  aChicago IL1 aSamejima, F uhttp://www.iacat.org/content/criterion-item-characteristic-curve-function-evaluating-differential-weight-procedure02792nas a2200121 4500008004100000245013500041210006900176300000900245490000700254520226900261100001502530856012502545 2003 eng d00aDevelopment, reliability, and validity of a computerized adaptive version of the Schedule for Nonadaptive and Adaptive Personality0 aDevelopment reliability and validity of a computerized adaptive  a34850 v633 aComputerized adaptive testing (CAT) and Item Response Theory (IRT) techniques were applied to the Schedule for Nonadaptive and Adaptive Personality (SNAP) to create a more efficient measure with little or no cost to test reliability or validity. The SNAP includes 15 factor analytically derived and relatively unidimensional traits relevant to personality disorder. IRT item parameters were calibrated on item responses from a sample of 3,995 participants who completed the traditional paper-and-pencil (P&P) SNAP in a variety of university, community, and patient settings. Computerized simulations were conducted to test various adaptive testing algorithms, and the results informed the construction of the CAT version of the SNAP (SNAP-CAT). A validation study of the SNAP-CAT was conducted on a sample of 413 undergraduates who completed the SNAP twice, separated by one week. Participants were randomly assigned to one of four groups who completed (1) a modified P&P version of the SNAP (SNAP-PP) twice (n = 106), (2) the SNAP-PP first and the SNAP-CAT second (n = 105), (3) the SNAP-CAT first and the SNAP-PP second (n = 102), and (4) the SNAP-CAT twice (n = 100). Results indicated that the SNAP-CAT was 58% and 60% faster than the traditional P&P version, at Times 1 and 2, respectively, and mean item savings across scales were 36% and 37%, respectively. These savings came with minimal cost to reliability or validity, and the two test forms were largely equivalent. Descriptive statistics, rank-ordering of scores, internal factor structure, and convergent/discriminant validity were highly comparable across testing modes and methods of scoring, and very few differences between forms replicated across testing sessions. In addition, participants overwhelmingly preferred the computerized version to the P&P version. However, several specific problems were identified for the Self-harm and Propriety scales of the SNAP-CAT that appeared to be broadly related to IRT calibration difficulties. Reasons for these anomalous findings are discussed, and follow-up studies are suggested. Despite these specific problems, the SNAP-CAT appears to be a viable alternative to the traditional P&P SNAP. (PsycINFO Database Record (c) 2003 APA, all rights reserved).1 aSimms, L J uhttp://www.iacat.org/content/development-reliability-and-validity-computerized-adaptive-version-schedule-nonadaptive-and00545nas 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-are00545nas 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-data00537nas a2200109 4500008004100000245014400041210006900185260001500254100001200269700001700281856012900298 2003 eng d00aIncreasing the homogeneity of CAT’s item-exposure rates by minimizing or maximizing varied target functions while assembling shadow tests0 aIncreasing the homogeneity of CAT s itemexposure rates by minimi aChicago IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/increasing-homogeneity-cat%E2%80%99s-item-exposure-rates-minimizing-or-maximizing-varied-target00520nas a2200169 4500008004100000245003700041210003700078260004900115300001400164653003400178100001800212700001300230700001700243700001200260700001500272856006300287 2003 eng d00aItem selection in polytomous CAT0 aItem selection in polytomous CAT aTokyo, JapanbPsychometric Society, Springer a207–21410acomputerized adaptive testing1 aVeldkamp, B P1 aOkada, A1 aShigenasu, K1 aKano, Y1 aMeulman, J uhttp://www.iacat.org/content/item-selection-polytomous-cat00452nas a2200145 4500008004100000245005100041210005100092260001500143100001500158700001400173700001200187700001500199700001500214856007700229 2003 eng d00aMaintaining scale in computer adaptive testing0 aMaintaining scale in computer adaptive testing aChicago IL1 aSmith, R L1 aRizavi, S1 aPaez, R1 aDamiano, M1 aHerbert, E uhttp://www.iacat.org/content/maintaining-scale-computer-adaptive-testing00489nas a2200109 4500008004100000245009900041210006900140260001600209100001200225700001700237856012500254 2003 eng d00aMultidimensional computerized adaptive testing in recovering reading and mathematics abilities0 aMultidimensional computerized adaptive testing in recovering rea aChicago, IL1 aLi, Y H1 aSchafer, W D uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-recovering-reading-and-mathematics-abilities01801nas a2200241 4500008004100000245009300041210006900134300001200203490000700215520098200222653001801204653002101222653003001243653001901273653004601292653001801338653002501356653001501381100001401396700001901410700001501429856011501444 2003 eng d00aThe relationship between item exposure and test overlap in computerized adaptive testing0 arelationship between item exposure and test overlap in computeri a129-1450 v403 aThe purpose of this article is to present an analytical derivation for the mathematical form of an average between-test overlap index as a function of the item exposure index, for fixed-length computerized adaptive tests (CATs). This algebraic relationship is used to investigate the simultaneous control of item exposure at both the item and test levels. The results indicate that, in fixed-length CATs, control of the average between-test overlap is achieved via the mean and variance of the item exposure rates of the items that constitute the CAT item pool. The mean of the item exposure rates is easily manipulated. Control over the variance of the item exposure rates can be achieved via the maximum item exposure rate (r-sub(max)). Therefore, item exposure control methods which implement a specification of r-sub(max) (e.g., J. B. Sympson and R. D. Hetter, 1985) provide the most direct control at both the item and test levels. (PsycINFO Database Record (c) 2005 APA )10a(Statistical)10aAdaptive Testing10aComputer Assisted Testing10aHuman Computer10aInteraction computerized adaptive testing10aItem Analysis10aItem Analysis (Test)10aTest Items1 aChen, S-Y1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/relationship-between-item-exposure-and-test-overlap-computerized-adaptive-testing00519nas a2200133 4500008004100000245009300041210006900134300001200203490000700215100001200222700001900234700001500253856011700268 2003 eng d00aThe relationship between item exposure and test overlap in computerized adaptive testing0 arelationship between item exposure and test overlap in computeri a129-1450 v401 aChen, S1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/relationship-between-item-exposure-and-test-overlap-computerized-adaptive-testing-000519nas a2200133 4500008004100000245009300041210006900134300001200203490000700215100001200222700001900234700001500253856011700268 2003 eng d00aThe relationship between item exposure and test overlap in computerized adaptive testing0 arelationship between item exposure and test overlap in computeri a129-1450 v401 aChen, S1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/relationship-between-item-exposure-and-test-overlap-computerized-adaptive-testing-101711nas a2200169 4500008004100000245015800041210006900199300001000268490000700278520105400285100001901339700001801358700001601376700001201392700001601404856012101420 2003 eng d00aSmall sample estimation in dichotomous item response models: Effect of priors based on judgmental information on the accuracy of item parameter estimates0 aSmall sample estimation in dichotomous item response models Effe a27-510 v273 aLarge item banks with properly calibrated test items are essential for ensuring the validity of computer-based tests. At the same time, item calibrations with small samples are desirable to minimize the amount of pretesting and limit item exposure. Bayesian estimation procedures show considerable promise with small examinee samples. The purposes of the study were (a) to examine how prior information for Bayesian item parameter estimation can be specified and (b) to investigate the relationship between sample size and the specification of prior information on the accuracy of item parameter estimates. The results of the simulation study were clear: Estimation of item response theory (IRT) model item parameters can be improved considerably. Improvements in the one-parameter model were modest; considerable improvements with the two- and three-parameter models were observed. Both the study of different forms of priors and ways to improve the judgmental data used in forming the priors appear to be promising directions for future research. 1 aSwaminathan, H1 aHambleton, RK1 aSireci, S G1 aXing, D1 aRizavi, S M uhttp://www.iacat.org/content/small-sample-estimation-dichotomous-item-response-models-effect-priors-based-judgmental00823nas a2200133 4500008004100000245005300041210005300094300001200147490000700159520041300166100001300579700001500592856008200607 2003 eng d00aStudent modeling and ab initio language learning0 aStudent modeling and ab initio language learning a519-5350 v313 aProvides examples of student modeling techniques that have been employed in computer-assisted language learning over the past decade. Describes two systems for learning German: "German Tutor" and "Geroline." Shows how a student model can support computerized adaptive language testing for diagnostic purposes in a Web-based language learning environment that does not rely on parsing technology. (Author/VWL)1 aHeift, T1 aSchulze, M uhttp://www.iacat.org/content/student-modeling-and-ab-initio-language-learning00527nas a2200121 4500008004100000245009600041210006900137260004600206100001100252700001300263700001600276856011300292 2002 eng d00aAdaptive testing without IRT in the presence of multidimensionality (Research Report 02-09)0 aAdaptive testing without IRT in the presence of multidimensional aPrinceton NJ: Educational Testing Service1 aYan, D1 aLewis, C1 aStocking, M uhttp://www.iacat.org/content/adaptive-testing-without-irt-presence-multidimensionality-research-report-02-0900441nas a2200109 4500008004100000245007500041210006900116260001900185100001500204700001300219856009900232 2002 eng d00aA comparison of computer mastery models when pool characteristics vary0 acomparison of computer mastery models when pool characteristics  aNew Orleans LA1 aSmith, R L1 aLewis, C uhttp://www.iacat.org/content/comparison-computer-mastery-models-when-pool-characteristics-vary00493nas a2200097 4500008004100000245012700041210006900168260002000237100001600257856012200273 2002 eng d00aConfirmatory item factor analysis using Markov chain Monte Carlo estimation with applications to online calibration in CAT0 aConfirmatory item factor analysis using Markov chain Monte Carlo aNew Orleans, LA1 aSegall, D O uhttp://www.iacat.org/content/confirmatory-item-factor-analysis-using-markov-chain-monte-carlo-estimation-applications00554nas a2200097 4500008003900000245013500039210006900174260007200243100001500315856012600330 2002 d00aDEVELOPMENT, RELIABILITY, AND VALIDITY OF A COMPUTERIZED ADAPTIVE VERSION OF THE SCHEDULE FOR NONADAPTIVE AND ADAPTIVE PERSONALITY0 aDEVELOPMENT RELIABILITY AND VALIDITY OF A COMPUTERIZED ADAPTIVE  aUnpublished Ph. D. dissertation, University of Iowa, Iowa City Iowa1 aSimms, L J uhttp://www.iacat.org/content/development-reliability-and-validity-computerized-adaptive-version-schedule-nonadaptive-an-001638nas 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-model01310nas a2200169 4500008004100000245009500041210006900136300001200205490000700217520070700224653003400931100001400965700001600979700001600995700001701011856011201028 2002 eng d00aEvaluation of selection procedures for computerized adaptive testing with polytomous items0 aEvaluation of selection procedures for computerized adaptive tes a393-4110 v263 aIn the present study, a procedure that has been used to select dichotomous items in computerized adaptive testing was applied to polytomous items. This procedure was designed to select the item with maximum weighted information. In a simulation study, the item information function was integrated over a fixed interval of ability values and the item with the maximum area was selected. This maximum interval information item selection procedure was compared to a maximum point information item selection procedure. Substantial differences between the two item selection procedures were not found when computerized adaptive tests were evaluated on bias and the root mean square of the ability estimate. 10acomputerized adaptive testing1 aRijn, P W1 aEggen, Theo1 aHemker, B T1 aSanders, P F uhttp://www.iacat.org/content/evaluation-selection-procedures-computerized-adaptive-testing-polytomous-items00547nas a2200145 4500008004100000245009500041210006900136300001200205490000700217100001400224700001600238700001600254700001700270856011400287 2002 eng d00aEvaluation of selection procedures for computerized adaptive testing with polytomous items0 aEvaluation of selection procedures for computerized adaptive tes a393-4110 v261 aRijn, P W1 aEggen, Theo1 aHemker, B T1 aSanders, P F uhttp://www.iacat.org/content/evaluation-selection-procedures-computerized-adaptive-testing-polytomous-items-000442nas 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-tests00520nas a2200133 4500008004100000245009700041210006900138260001900207100001500226700001100241700001300252700001100265856011000276 2002 eng d00aAn investigation of procedures for estimating error indexes in proficiency estimation in CAT0 ainvestigation of procedures for estimating error indexes in prof aNew Orleans LA1 aShyu, C -Y1 aFan, M1 aThompson1 aHsu, Y uhttp://www.iacat.org/content/investigation-procedures-estimating-error-indexes-proficiency-estimation-cat01183nas a2200133 4500008004100000245006200041210005900103300001200162490000700174520073400181653003400915100001600949856008400965 2002 eng d00aAn item response model for characterizing test compromise0 aitem response model for characterizing test compromise a163-1790 v273 aThis article presents an item response model for characterizing test-compromise that enables the estimation of item-preview and score-gain distributions observed in on-demand high-stakes testing programs. Model parameters and posterior distributions are estimated by Markov Chain Monte Carlo (MCMC) procedures. Results of a simulation study suggest that when at least some of the items taken by a small sample of test takers are known to be secure (uncompromised), the procedure can provide useful summaries of test-compromise and its impact on test scores. The article includes discussions of operational use of the proposed procedure, possible model violations and extensions, and application to computerized adaptive testing. 10acomputerized adaptive testing1 aSegall, D O uhttp://www.iacat.org/content/item-response-model-characterizing-test-compromise00454nas a2200133 4500008004100000245005900041210005900100260001900159100001500178700001400193700001200207700001300219856008800232 2002 eng d00aUpdated item parameter estimates using sparse CAT data0 aUpdated item parameter estimates using sparse CAT data aNew Orleans LA1 aSmith, R L1 aRizavi, S1 aPaez, R1 aRotou, O uhttp://www.iacat.org/content/updated-item-parameter-estimates-using-sparse-cat-data00454nas a2200097 4500008004100000245008100041210006900122260004200191100001900233856010400252 2001 eng d00aDetection of misfitting item-score patterns in computerized adaptive testing0 aDetection of misfitting itemscore patterns in computerized adapt aEnschede, The Netherlands: Febodruk B1 aStoop, E M L A uhttp://www.iacat.org/content/detection-misfitting-item-score-patterns-computerized-adaptive-testing00552nas a2200157 4500008004100000245008100041210006900122300001200191490000700203100002000210700001600230700001600246700001700262700001400279856010100293 2001 eng d00aDevelopment of an adaptive multimedia program to collect patient health data0 aDevelopment of an adaptive multimedia program to collect patient a320-3240 v211 aSutherland, L A1 aCampbell, M1 aOrnstein, K1 aWildemuth, B1 aLobach, D uhttp://www.iacat.org/content/development-adaptive-multimedia-program-collect-patient-health-data00457nas a2200097 4500008004100000245009000041210006900131260002500200100003300225856010100258 2001 eng d00aThe Development of STAR Early Literacy: A report of the School Renaissance Institute.0 aDevelopment of STAR Early Literacy A report of the School Renais aMadison, WI: Author.1 aSchool-Renaissance-Institute uhttp://www.iacat.org/content/development-star-early-literacy-report-school-renaissance-institute01969nas a2200193 4500008004100000245008600041210006900127300001000196490000700206520131400213653001401527653003001541653002501571653001101596653003601607653001401643100001501657856010301672 2001 eng d00aDevelopments in measurement of persons and items by means of item response models0 aDevelopments in measurement of persons and items by means of ite a65-940 v283 aThis paper starts with a general introduction into measurement of hypothetical constructs typical of the social and behavioral sciences. After the stages ranging from theory through operationalization and item domain to preliminary test or questionnaire have been treated, the general assumptions of item response theory are discussed. The family of parametric item response models for dichotomous items is introduced and it is explained how parameters for respondents and items are estimated from the scores collected from a sample of respondents who took the test or questionnaire. Next, the family of nonparametric item response models is explained, followed by the 3 classes of item response models for polytomous item scores (e.g., rating scale scores). Then, to what degree the mean item score and the unweighted sum of item scores for persons are useful for measuring items and persons in the context of item response theory is discussed. Methods for fitting parametric and nonparametric models to data are briefly discussed. Finally, the main applications of item response models are discussed, which include equating and item banking, computerized and adaptive testing, research into differential item functioning, person fit research, and cognitive modeling. (PsycINFO Database Record (c) 2005 APA )10aCognitive10aComputer Assisted Testing10aItem Response Theory10aModels10aNonparametric Statistical Tests10aProcesses1 aSijtsma, K uhttp://www.iacat.org/content/developments-measurement-persons-and-items-means-item-response-models00525nas 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-computerized00472nas 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-adaptive02101nas 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-using00574nas a2200133 4500008004100000245014400041210006900185260001500254100001500269700001100284700001300295700000900308856012300317 2001 eng d00aAn investigation of procedures for estimating error indexes in proficiency estimation in a realistic second-order equitable CAT environment0 ainvestigation of procedures for estimating error indexes in prof aSeattle WA1 aShyu, C -Y1 aFan, M1 aThompson1 aHsu. uhttp://www.iacat.org/content/investigation-procedures-estimating-error-indexes-proficiency-estimation-realistic-second00583nas a2200121 4500008004100000245015600041210006900197260002600266100001500292700001500307700002000322856011900342 2001 eng d00aItem and passage selection algorithm simulations for a computerized adaptive version of the verbal section of the Medical College Admission Test (MCAT)0 aItem and passage selection algorithm simulations for a computeri aMCAT Monograph Series1 aSmith, R W1 aPlake, B S1 ade Ayala, R. J. uhttp://www.iacat.org/content/item-and-passage-selection-algorithm-simulations-computerized-adaptive-version-verbal01465nas a2200253 4500008004100000245013900041210006900180260005000249300001200299520053700311653002100848653002500869653001200894653002900906653002200935653002700957653002600984653001501010653001601025100001501041700001601056700001701072856012201089 2001 eng d00aItem response theory applied to combinations of multiple-choice and constructed-response items--approximation methods for scale scores0 aItem response theory applied to combinations of multiplechoice a aMahwah, N.J. USAbLawrence Erlbaum Associates a289-3153 a(From the chapter) The authors develop approximate methods that replace the scoring tables with weighted linear combinations of the component scores. Topics discussed include: a linear approximation for the extension to combinations of scores; the generalization of two or more scores; potential applications of linear approximations to item response theory in computerized adaptive tests; and evaluation of the pattern-of-summed-scores, and Gaussian approximation, estimates of proficiency. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aItem Response Theory10aMethod)10aMultiple Choice (Testing10aScoring (Testing)10aStatistical Estimation10aStatistical Weighting10aTest Items10aTest Scores1 aThissen, D1 aNelson, L A1 aSwygert, K A uhttp://www.iacat.org/content/item-response-theory-applied-combinations-multiple-choice-and-constructed-response-items00489nas a2200097 4500008004100000245013100041210006900172260001500241100001600256856011900272 2001 eng d00aMeasuring test compromise in high-stakes computerized adaptive testing: A Bayesian Strategy for surrogate test-taker detection0 aMeasuring test compromise in highstakes computerized adaptive te aSeattle WA1 aSegall, D O uhttp://www.iacat.org/content/measuring-test-compromise-high-stakes-computerized-adaptive-testing-bayesian-strategy00576nas a2200121 4500008004100000245012500041210006900166260004600235100001800281700001500299700001600314856012400330 2001 eng d00aA method for building a realistic model of test taker behavior for computerized adaptive testing (Research Report 01-22)0 amethod for building a realistic model of test taker behavior for aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aSteffen, M1 aEignor, D R uhttp://www.iacat.org/content/method-building-realistic-model-test-taker-behavior-computerized-adaptive-testing-research00503nas a2200133 4500008004100000245007900041210006900120260002400189100001500213700001400228700001700242700001200259856009800271 2001 eng d00aMonitoring items for changes in performance in computerized adaptive tests0 aMonitoring items for changes in performance in computerized adap aSeattle, Washington1 aSmith, R L1 aWang, M M1 aWingersky, M1 aZhao, C uhttp://www.iacat.org/content/monitoring-items-changes-performance-computerized-adaptive-tests00435nas a2200121 4500008004100000245006800041210006400109260001500173100001600188700001500204700001600219856007800235 2001 eng d00aA monte carlo study of the feasibility of on-the-fly assessment0 amonte carlo study of the feasibility of onthefly assessment aSeattle WA1 aRevuelta, J1 aBejar, I I1 aStocking, M uhttp://www.iacat.org/content/monte-carlo-study-feasibility-fly-assessment00587nas a2200133 4500008004100000245013700041210006900178260001500247100001800262700001700280700001600297700001700313856012300330 2001 eng d00aNearest neighbors, simple strata, and probabilistic parameters: An empirical comparison of methods for item exposure control in CATs0 aNearest neighbors simple strata and probabilistic parameters An  aSeattle WA1 aParshall, C G1 aKromrey, J D1 aHarmes, J C1 aSentovich, C uhttp://www.iacat.org/content/nearest-neighbors-simple-strata-and-probabilistic-parameters-empirical-comparison-methods00521nas a2200121 4500008004100000245010800041210006900149260002400218100001100242700001300253700001200266856012100278 2001 eng d00aOn-line Calibration Using PARSCALE Item Specific Prior Method: Changing Test Population and Sample Size0 aOnline Calibration Using PARSCALE Item Specific Prior Method Cha aSeattle, Washington1 aGuo, F1 aStone, E1 aCruz, D uhttp://www.iacat.org/content/line-calibration-using-parscale-item-specific-prior-method-changing-test-population-and01348nas a2200181 4500008004100000245007300041210006900114260005600183300001200239520069300251653002100944653003000965653002200995653002001017100001601037700001701053856009601070 2001 eng d00aPractical issues in setting standards on computerized adaptive tests0 aPractical issues in setting standards on computerized adaptive t aMahwah, N.J. USAbLawrence Erlbaum Associates, Inc. a355-3693 a(From the chapter) Examples of setting standards on computerized adaptive tests (CATs) are hard to find. Some examples of CATs involving performance standards include the registered nurse exam and the Novell systems engineer exam. Although CATs do not require separate standard setting-methods, there are special issues to be addressed by test specialist who set performance standards on CATs. Setting standards on a CAT will typical require modifications on the procedures used with more traditional, fixed-form, paper-and -pencil examinations. The purpose of this chapter is to illustrate why CATs pose special challenges to the standard setter. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aComputer Assisted Testing10aPerformance Tests10aTesting Methods1 aSireci, S G1 aClauser, B E uhttp://www.iacat.org/content/practical-issues-setting-standards-computerized-adaptive-tests00560nas a2200133 4500008004100000245009400041210006900135260004600204100001300250700001500263700001500278700001800293856011500311 2001 eng d00aRefining a system for computerized adaptive testing pool creation (Research Report 01-18)0 aRefining a system for computerized adaptive testing pool creatio aPrinceton NJ: Educational Testing Service1 aWay, W D1 aSwanson, L1 aSteffen, M1 aStocking, M L uhttp://www.iacat.org/content/refining-system-computerized-adaptive-testing-pool-creation-research-report-01-1800451nas a2200121 4500008004100000245007000041210006900111260001500180100001300195700001200208700001600220856009300236 2001 eng d00aRefining a system for computerized adaptive testing pool creation0 aRefining a system for computerized adaptive testing pool creatio aSeattle WA1 aWay, W D1 aSwanson1 aStocking, M uhttp://www.iacat.org/content/refining-system-computerized-adaptive-testing-pool-creation00445nas a2200097 4500008004100000245008800041210006900129260002100198100001300219856011500232 2001 eng d00aTesting a computerized adaptive personality inventory using simulated response data0 aTesting a computerized adaptive personality inventory using simu aSan Francisco CA1 aSimms, L uhttp://www.iacat.org/content/testing-computerized-adaptive-personality-inventory-using-simulated-response-data00722nas a2200145 4500008004100000245020100041210006900242260005700311100001700368700001700385700001400402700002000416700001600436856012400452 2001 eng d00aTesting via the Internet: A literature review and analysis of issues for Department of Defense Internet testing of the Armed Services Vocational Aptitude Battery (ASVAB) in high schools (FR-01-12)0 aTesting via the Internet A literature review and analysis of iss aAlexandria VA: Human Resources Research Organization1 aMcBride, J R1 aPaddock, A F1 aWise, L L1 aStrickland, W J1 aWaters, B K uhttp://www.iacat.org/content/testing-internet-literature-review-and-analysis-issues-department-defense-internet-testing00376nas a2200121 4500008004100000245004600041210004500087300001000132490001000142100001400152700001600166856007200182 2001 eng d00aValidity issues in computer-based testing0 aValidity issues in computerbased testing a16-250 v20(3)1 aHuff, K L1 aSireci, S G uhttp://www.iacat.org/content/validity-issues-computer-based-testing02442nas a2200169 4500008004100000245012400041210007300165300001000238490000700248520174900255653003402004100002002038700001802058700002202076700002202098856015202120 2000 eng d00aAlgoritmo mixto mínima entropía-máxima información para la selección de ítems en un test adaptativo informatizado0 aAlgoritmo mixto mínima entropíamáxima información para la selecc a12-140 v123 aEl objetivo del estudio que presentamos es comparar la eficacia como estrat egia de selección de ítems de tres algo ritmos dife rentes: a) basado en máxima info rmación; b) basado en mínima entropía; y c) mixto mínima entropía en los ítems iniciales y máxima info rmación en el resto; bajo la hipótesis de que el algo ritmo mixto, puede dotar al TAI de mayor eficacia. Las simulaciones de procesos TAI se re a l i z a ron sobre un banco de 28 ítems de respuesta graduada calibrado según el modelo de Samejima, tomando como respuesta al TAI la respuesta ori ginal de los sujetos que fueron utilizados para la c a l i b ración. Los resultados iniciales mu e s t ran cómo el cri t e rio mixto es más eficaz que cualquiera de los otros dos tomados indep e n d i e n t e m e n t e. Dicha eficacia se maximiza cuando el algo ritmo de mínima entropía se re s t ri n ge a la selección de los pri m e ros ítems del TAI, ya que con las respuestas a estos pri m e ros ítems la estimación de q comienza a ser re l evante y el algo ritmo de máxima informaciónse optimiza.Item selection algo rithms in computeri zed adap t ive testing. The aim of this paper is to compare the efficacy of three different item selection algo rithms in computeri zed adap t ive testing (CAT). These algorithms are based as follows: the first one is based on Item Info rm ation, the second one on Entropy, and the last algo rithm is a mixture of the two previous ones. The CAT process was simulated using an emotional adjustment item bank. This item bank contains 28 graded items in six categories , calibrated using Samejima (1969) Graded Response Model. The initial results show that the mixed criterium algorithm performs better than the other ones.10acomputerized adaptive testing1 aDorronsoro, J R1 aSanta-Cruz, C1 aRubio Franco, V J1 aAguado García, D uhttp://www.iacat.org/content/algoritmo-mixto-m%C3%ADnima-entrop%C3%ADa-m%C3%A1xima-informaci%C3%B3n-para-la-selecci%C3%B3n-de-%C3%ADtems-en-un-test01587nas a2200241 4500008004100000245005800041210005800099300001200157490000600169520081000175653001400985653001400999653004801013653005701061653001101118653001801129653003101147653003701178100001301215700001701228700001601245856008401261 2000 eng d00aCAT administration of language placement examinations0 aCAT administration of language placement examinations a292-3020 v13 aThis article describes the development of a computerized adaptive test for Cegep de Jonquiere, a community college located in Quebec, Canada. Computerized language proficiency testing allows the simultaneous presentation of sound stimuli as the question is being presented to the test-taker. With a properly calibrated bank of items, the language proficiency test can be offered in an adaptive framework. By adapting the test to the test-taker's level of ability, an assessment can be made with significantly fewer items. We also describe our initial attempt to detect instances in which "cheating low" is occurring. In the "cheating low" situation, test-takers deliberately answer questions incorrectly, questions that they are fully capable of answering correctly had they been taking the test honestly.10a*Language10a*Software10aAptitude Tests/*statistics & numerical data10aEducational Measurement/*statistics & numerical data10aHumans10aPsychometrics10aReproducibility of Results10aResearch Support, Non-U.S. Gov't1 aStahl, J1 aBergstrom, B1 aGershon, RC uhttp://www.iacat.org/content/cat-administration-language-placement-examinations00562nas a2200133 4500008004100000245012400041210006900165260001900234100001300253700001200266700001400278700001500292856012100307 2000 eng d00aClassification accuracy and test security for a computerized adaptive mastery test calibrated with different IRT models0 aClassification accuracy and test security for a computerized ada aNew Orleans LA1 aRobin, F1 aXing, D1 aScrams, D1 aPotenza, M uhttp://www.iacat.org/content/classification-accuracy-and-test-security-computerized-adaptive-mastery-test-calibrated00484nas a2200133 4500008004100000245007600041210006900117300001100186490000700197100001500204700001600219700001700235856009800252 2000 eng d00aComputerized adaptive administration of the self-evaluation examination0 aComputerized adaptive administration of the selfevaluation exami a226-310 v681 aLaVelle, T1 aZaglaniczny1 aSpitzer, L E uhttp://www.iacat.org/content/computerized-adaptive-administration-self-evaluation-examination00587nam a2200181 4500008004100000245005800041210005500099260005100154100001100205700001400216700001600230700001600246700001400262700001500276700001700291700001500308856008200323 2000 eng d00aComputerized adaptive testing: A primer (2nd edition)0 aComputerized adaptive testing A primer 2nd edition aHillsdale, N. J. : Lawrence Erlbaum Associates1 aWainer1 aDorans, N1 aEignor, D R1 aFlaugher, R1 aGreen, BF1 aMislevy, R1 aSteinberg, L1 aThissen, D uhttp://www.iacat.org/content/computerized-adaptive-testing-primer-2nd-edition01598nas a2200157 4500008004100000245008200041210006900123300001100192490000700203520101400210653003401224653004001258100001601298700002401314856010201338 2000 eng d00aComputerized adaptive testing for classifying examinees into three categories0 aComputerized adaptive testing for classifying examinees into thr a713-340 v603 aThe objective of this study was to explore the possibilities for using computerized adaptive testing in situations in which examinees are to be classified into one of three categories.Testing algorithms with two different statistical computation procedures are described and evaluated. The first computation procedure is based on statistical testing and the other on statistical estimation. Item selection methods based on maximum information (MI) considering content and exposure control are considered. The measurement quality of the proposed testing algorithms is reported. The results of the study are that a reduction of at least 22% in the mean number of items can be expected in a computerized adaptive test (CAT) compared to an existing paper-and-pencil placement test. Furthermore, statistical testing is a promising alternative to statistical estimation. Finally, it is concluded that imposing constraints on the MI selection strategy does not negatively affect the quality of the testing algorithms10acomputerized adaptive testing10aComputerized classification testing1 aEggen, Theo1 aStraetmans, G J J M uhttp://www.iacat.org/content/computerized-adaptive-testing-classifying-examinees-three-categories02844nas a2200193 4500008004100000245013800041210006900179300000900248490000700257520208000264653003002344653002002374653005202394653002202446653001802468653002402486100001602510856012402526 2000 eng d00aThe development of a computerized version of Vandenberg's mental rotation test and the effect of visuo-spatial working memory loading0 adevelopment of a computerized version of Vandenbergs mental rota a39380 v603 aThis dissertation focused on the generation and evaluation of web-based versions of Vandenberg's Mental Rotation Test. Memory and spatial visualization theory were explored in relation to the addition of a visuo-spatial working memory component. Analysis of the data determined that there was a significant difference between scores on the MRT Computer and MRT Memory test. The addition of a visuo-spatial working memory component did significantly affect results at the .05 alpha level. Reliability and discrimination estimates were higher on the MRT Memory version. The computerization of the paper and pencil version on the MRT did not significantly effect scores but did effect the time required to complete the test. The population utilized in the quasi-experiment consisted of 107 university students from eight institutions in engineering graphics related courses. The subjects completed two researcher developed, Web-based versions of Vandenberg's Mental Rotation Test and the original paper and pencil version of the Mental Rotation Test. One version of the test included a visuo-spatial working memory loading. Significant contributions of this study included developing and evaluating computerized versions of Vandenberg's Mental Rotation Test. Previous versions of Vandenberg's Mental Rotation Test did not take advantage of the ability of the computer to incorporate an interaction factor, such as a visuo-spatial working memory loading, into the test. The addition of an interaction factor results in a more discriminate test which will lend itself well to computerized adaptive testing practices. Educators in engineering graphics related disciplines should strongly consider the use of spatial visualization tests to aid in establishing the effects of modern computer systems on fundamental design/drafting skills. Regular testing of spatial visualization skills will result assist in the creation of a more relevant curriculum. Computerized tests which are valid and reliable will assist in making this task feasible. (PsycINFO Database Record (c) 2005 APA )10aComputer Assisted Testing10aMental Rotation10aShort Term Memory computerized adaptive testing10aTest Construction10aTest Validity10aVisuospatial Memory1 aStrong, S D uhttp://www.iacat.org/content/development-computerized-version-vandenbergs-mental-rotation-test-and-effect-visuo-spatial03274nas a2200217 4500008004100000245020800041210007000249300001000319490000700329520241300336653002102749653002402770653003202794653001302826100001902839700001802858700001702876700001802893700001702911856012802928 2000 eng d00aDiagnostische programme in der Demenzfrüherkennung: Der Adaptive Figurenfolgen-Lerntest (ADAFI) [Diagnostic programs in the early detection of dementia: The Adaptive Figure Series Learning Test (ADAFI)]0 aDiagnostische programme in der Demenzfrüherkennung Der Adaptive  a16-290 v133 aZusammenfassung: Untersucht wurde die Eignung des computergestützten Adaptiven Figurenfolgen-Lerntests (ADAFI), zwischen gesunden älteren Menschen und älteren Menschen mit erhöhtem Demenzrisiko zu differenzieren. Der im ADAFI vorgelegte Aufgabentyp der fluiden Intelligenzdimension (logisches Auffüllen von Figurenfolgen) hat sich in mehreren Studien zur Erfassung des intellektuellen Leistungspotentials (kognitive Plastizität) älterer Menschen als günstig für die genannte Differenzierung erwiesen. Aufgrund seiner Konzeption als Diagnostisches Programm fängt der ADAFI allerdings einige Kritikpunkte an Vorgehensweisen in diesen bisherigen Arbeiten auf. Es konnte gezeigt werden, a) daß mit dem ADAFI deutliche Lokationsunterschiede zwischen den beiden Gruppen darstellbar sind, b) daß mit diesem Verfahren eine gute Vorhersage des mentalen Gesundheitsstatus der Probanden auf Einzelfallebene gelingt (Sensitivität: 80 %, Spezifität: 90 %), und c) daß die Vorhersageleistung statusdiagnostischer Tests zur Informationsverarbeitungsgeschwindigkeit und zum Arbeitsgedächtnis geringer ist. Die Ergebnisse weisen darauf hin, daß die plastizitätsorientierte Leistungserfassung mit dem ADAFI vielversprechend für die Frühdiagnostik dementieller Prozesse sein könnte.The aim of this study was to examine the ability of the computerized Adaptive Figure Series Learning Test (ADAFI) to differentiate among old subjects at risk for dementia and old healthy controls. Several studies on the subject of measuring the intellectual potential (cognitive plasticity) of old subjects have shown the usefulness of the fluid intelligence type of task used in the ADAFI (completion of figure series) for this differentiation. Because the ADAFI has been developed as a Diagnostic Program it is able to counter some critical issues in those studies. It was shown a) that distinct differences between both groups are revealed by the ADAFI, b) that the prediction of the cognitive health status of individual subjects is quite good (sensitivity: 80 %, specifity: 90 %), and c) that the prediction of the cognitive health status with tests of processing speed and working memory is worse than with the ADAFI. The results indicate that the ADAFI might be a promising plasticity-oriented tool for the measurement of cognitive decline in the elderly, and thus might be useful for the early detection of dementia.10aAdaptive Testing10aAt Risk Populations10aComputer Assisted Diagnosis10aDementia1 aSchreiber, M D1 aSchneider, RJ1 aSchweizer, A1 aBeckmann, J F1 aBaltissen, R uhttp://www.iacat.org/content/diagnostische-programme-der-demenzfr%C3%BCherkennung-der-adaptive-figurenfolgen-lerntest-adafi00548nas 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-test00571nas a2200133 4500008004100000245012200041210006900163260003100232100001600263700001600279700001400295700001500309856011300324 2000 eng d00aEstimating Item Parameters from Classical Indices for Item Pool Development with a Computerized Classification Test. 0 aEstimating Item Parameters from Classical Indices for Item Pool  aIowa City, IowabACT, Inc.1 aHuang, C -Y1 aKalohn, J C1 aLin, C -J1 aSpray, J A uhttp://www.iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized00589nas a2200133 4500008004100000245014500041210006900186260002600255100001600281700001600297700001400313700001300327856011500340 2000 eng d00aEstimating item parameters from classical indices for item pool development with a computerized classification test (Research Report 2000-4)0 aEstimating item parameters from classical indices for item pool  aIowa City IA: ACT Inc1 aHuang, C -Y1 aKalohn, J C1 aLin, C -J1 aSpray, J uhttp://www.iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized-100587nas 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-002407nas a2200193 4500008004100000245010700041210006900148300000900217490000700226520169400233653003201927653002501959653002001984653001802004653002602022653001402048100002602062856012502088 2000 eng d00aAn exploratory analysis of item parameters and characteristics that influence item level response time0 aexploratory analysis of item parameters and characteristics that a18120 v613 aThis research examines the relationship between item level response time and (1) item discrimination, (2) item difficulty, (3) word count, (4) item type, and (5) whether a figure is included in an item. Data are from the Graduate Management Admission Test, which is currently offered only as a computerized adaptive test. Analyses revealed significant differences in response time between the five item types: problem solving, data sufficiency, sentence correction, critical reasoning, and reading comprehension. For this reason, the planned pairwise and complex analyses were run within each item type. Pairwise curvilinear regression analyses explored the relationship between response time and item discrimination, item difficulty, and word count. Item difficulty significantly contributed to the prediction of response time for each item type; two of the relationships were significantly quadratic. Item discrimination significantly contributed to the prediction of response time for only two of the item types; one revealed a quadratic relationship and the other a cubic relationship. Word count had significant linear relationship with response time for all the item types except reading comprehension, for which there was no significant relationship. Multiple regression analyses using word count, item difficulty, and item discrimination predicted between 35.4% and 71.4% of the variability in item response time across item types. The results suggest that response time research should consider the type of item that is being administered and continue to explore curvilinear relationships between response time and its predictor variables. (PsycINFO Database Record (c) 2005 APA )10aItem Analysis (Statistical)10aItem Response Theory10aProblem Solving10aReaction Time10aReading Comprehension10aReasoning1 aSmith, Russell Winsor uhttp://www.iacat.org/content/exploratory-analysis-item-parameters-and-characteristics-influence-item-level-response-time00363nas a2200097 4500008004100000245005200041210005000093260002700143100001800170856007700188 2000 eng d00aA framework for comparing adaptive test designs0 aframework for comparing adaptive test designs aUnpublished manuscript1 aStocking, M L uhttp://www.iacat.org/content/framework-comparing-adaptive-test-designs-000512nas a2200109 4500008004100000245005500041210005000096260014700146100001500293700001500308856007900323 2000 eng d00aThe GRE computer adaptive test: Operational issues0 aGRE computer adaptive test Operational issues aW. J. van der Linden and C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice (pp. 75-99). Dordrecht, Netherlands: Kluwer.1 aMills, C N1 aSteffen, M uhttp://www.iacat.org/content/gre-computer-adaptive-test-operational-issues00617nas a2200121 4500008004100000245016600041210006900207260004700276100001800323700001300341700001500354856012600369 2000 eng d00aAn investigation of approaches to computerizing the GRE subject tests (GRE Board Professional Report No 93-08P; Educational Testing Service Research Report 00-4)0 ainvestigation of approaches to computerizing the GRE subject tes aPrinceton NJ: Educational Testing Service.1 aStocking, M L1 aSmith, R1 aSwanson, L uhttp://www.iacat.org/content/investigation-approaches-computerizing-gre-subject-tests-gre-board-professional-report-no-9301343nas a2200157 4500008004100000245006300041210006300104300001000167490000700177520083100184100002101015700001801036700002001054700002201074856008901096 2000 eng d00aItem selection algorithms in computerized adaptive testing0 aItem selection algorithms in computerized adaptive testing a12-140 v123 aStudied the efficacy of 3 different item selection algorithms in computerized adaptive testing. Ss were 395 university students (aged 20-25 yrs) in Spain. Ss were asked to submit answers via computer to 28 items of a personality questionnaire using item selection algorithms based on maximum item information, entropy, or mixed item-entropy algorithms. The results were evaluated according to ability of Ss to use item selection algorithms and number of questions. Initial results indicate that mixed criteria algorithms were more efficient than information or entropy algorithms for up to 15 questionnaire items, but that differences in efficiency decreased with increasing item number. Implications for developing computer adaptive testing methods are discussed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aGarcia, David, A1 aSanta Cruz, C1 aDorronsoro, J R1 aRubio Franco, V J uhttp://www.iacat.org/content/item-selection-algorithms-computerized-adaptive-testing00503nas a2200109 4500008004100000245005600041210005600097260013700153100001800290700001300308856007200321 2000 eng d00aMethods of controlling the exposure of items in CAT0 aMethods of controlling the exposure of items in CAT aW. J. van der Linden and C. A. W. Glas (eds.), Computerized adaptive testing: Theory and practice (pp. 163-182). Norwell MA: Kluwer.1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/methods-controlling-exposure-items-cat00472nas a2200097 4500008004100000245005200041210005200093260013500145100001600280856007800296 2000 eng d00aPrinciples of multidimensional adaptive testing0 aPrinciples of multidimensional adaptive testing aW. J. van der Linden and C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice (pp. 53-73). Norwell MA: Kluwer.1 aSegall, D O uhttp://www.iacat.org/content/principles-multidimensional-adaptive-testing00598nas a2200121 4500008004100000245002700041210002500068300001000093490000600103520029500109100002100404856005100425 2000 eng d00aA review of CAT review0 areview of CAT review a47-490 v33 aStudied the effects of answer review on results of a computerized adaptive test, the laboratory professional examination of the American Society of Clinical Pathologists. Results from 29,293 candidates show that candidates who changed answers were more likely to improve their scores. (SLD)1 aSekula-Wacura, R uhttp://www.iacat.org/content/review-cat-review00594nas a2200133 4500008004100000245013300041210006900174260003400243100000900277700001600286700001600302700001700318856012500335 2000 eng d00aA selection procedure for polytomous items in computerized adaptive testing (Measurement and Research Department Reports 2000-5)0 aselection procedure for polytomous items in computerized adaptiv aArnhem, The Netherlands: Cito1 aRijn1 aEggen, Theo1 aHemker, B T1 aSanders, P F uhttp://www.iacat.org/content/selection-procedure-polytomous-items-computerized-adaptive-testing-measurement-and-research00506nas a2200097 4500008004100000245014600041210006900187260001900256100001600275856011700291 2000 eng d00aSome considerations for improving accuracy of estimation of item characteristic curves in online calibration of computerized adaptive testing0 aSome considerations for improving accuracy of estimation of item aNew Orleans LA1 aSamejima, F uhttp://www.iacat.org/content/some-considerations-improving-accuracy-estimation-item-characteristic-curves-online00409nas a2200121 4500008004100000245005100041210005100092260002100143100001300164700001600177700001700193856007700210 1999 eng d00aCAT administration of language placement exams0 aCAT administration of language placement exams aMontreal, Canada1 aStahl, J1 aGershon, RC1 aBergstrom, B uhttp://www.iacat.org/content/cat-administration-language-placement-exams00517nas a2200109 4500008004100000245012200041210006900163260002300232100001800255700001500273856011900288 1999 eng d00aA comparison of testlet-based test designs for computerized adaptive testing (LSAC Computerized Testing Report 97-01)0 acomparison of testletbased test designs for computerized adaptiv aNewtown, PA: LSAC.1 aSchnipke, D L1 aReese, L M uhttp://www.iacat.org/content/comparison-testlet-based-test-designs-computerized-adaptive-testing-lsac-computerized00359nas a2200097 4500008004100000245005200041210005200093260002700145100001500172856007400187 1999 eng d00aComputerized adaptive testing in the Bundeswehr0 aComputerized adaptive testing in the Bundeswehr aUnpublished manuscript1 aStorm, E G uhttp://www.iacat.org/content/computerized-adaptive-testing-bundeswehr00492nas a2200133 4500008004100000245007400041210006700115260001300182100001600195700001300211700001300224700001400237856010700251 1999 eng d00aComputerized testing – Issues and applications (Mini-course manual)0 aComputerized testing Issues and applications Minicourse manual aMontreal1 aParshall, C1 aDavey, T1 aSpray, J1 aKalohn, J uhttp://www.iacat.org/content/computerized-testing-%E2%80%93-issues-and-applications-mini-course-manual00427nas a2200109 4500008004100000245006800041210006800109260002100177100001600198700001800214856008500232 1999 eng d00aDetecting items that have been memorized in the CAT environment0 aDetecting items that have been memorized in the CAT environment aMontreal, Canada1 aMcLeod, L D1 aSchinpke, D L uhttp://www.iacat.org/content/detecting-items-have-been-memorized-cat-environment00594nas a2200109 4500008004100000245011100041210006900152260010500221100001600326700001600342856012600358 1999 eng d00aDevelopment of the computerized adaptive testing version of the Armed Services Vocational Aptitude Battery0 aDevelopment of the computerized adaptive testing version of the  aF. Drasgow and J. Olson-Buchanan (Eds.). Innovations in computerized assessment. Mahwah NJ: Erlbaum.1 aSegall, D O1 aMoreno, K E uhttp://www.iacat.org/content/development-computerized-adaptive-testing-version-armed-services-vocational-aptitude-battery01684nas 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-test00603nas a2200157 4500008004100000245011600041210006900157300001200226490000700238100001400245700001100259700001600270700001700286700001900303856012300322 1999 eng d00aExaminee judgments of changes in item difficulty: Implications for item review in computerized adaptive testing0 aExaminee judgments of changes in item difficulty Implications fo a185-1980 v121 aWise, S L1 aFinney1 aEnders, C K1 aFreeman, S A1 aSeverance, D D uhttp://www.iacat.org/content/examinee-judgments-changes-item-difficulty-implications-item-review-computerized-adaptive00621nas a2200121 4500008004100000245011300041210006900154260011200223100001200335700001900347700001500366856011800381 1999 eng d00aExploring the relationship between item exposure rate and test overlap rate in computerized adaptive testing0 aExploring the relationship between item exposure rate and test o aPaper presented at the annual meeting of the National Council on Measurement in Education, Montreal, Canada1 aChen, S1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/exploring-relationship-between-item-exposure-rate-and-test-overlap-rate-computerized00574nas a2200121 4500008004100000245014700041210006900188260002700257100001400284700001900298700001500317856012000332 1999 eng d00aExploring the relationship between item exposure rate and test overlap rate in computerized adaptive testing (ACT Research Report series 99-5)0 aExploring the relationship between item exposure rate and test o aIowa City IA: ACT, Inc1 aChen, S-Y1 aAnkenmann, R D1 aSpray, J A uhttp://www.iacat.org/content/exploring-relationship-between-item-exposure-rate-and-test-overlap-rate-computerized-000386nas a2200109 4500008004100000245005600041210005600097260002100153100001100174700001500185856007600200 1999 eng d00aImpact of flawed items on ability estimation in CAT0 aImpact of flawed items on ability estimation in CAT aMontreal, Canada1 aLiu, M1 aSteffen, M uhttp://www.iacat.org/content/impact-flawed-items-ability-estimation-cat01885nas a2200145 4500008004100000020001100041245008200052210006900134260005300203520133100256100001501587700001801602700001601620856010301636 1999 eng d aSeries00aIncorporating content constraints into a multi-stage adaptive testlet design.0 aIncorporating content constraints into a multistage adaptive tes aPrinceton, NJ. USAbLaw School Admission Council3 aMost large-scale testing programs facing computerized adaptive testing (CAT) must face the challenge of maintaining extensive content requirements, but content constraints in computerized adaptive testing (CAT) can compromise the precision and efficiency that could be achieved by a pure maximum information adaptive testing algorithm. This simulation study first evaluated whether realistic content constraints could be met by carefully assembling testlets and appropriately selecting testlets for each test taker that, when combined, would meet the content requirements of the test and would be adapted to the test takers ability level. The second focus of the study was to compare the precision of the content-balanced testlet design with that achieved by the current paper-and-pencil version of the test through data simulation. The results reveal that constraints to control for item exposure, testlet overlap, and efficient pool utilization need to be incorporated into the testlet assembly algorithm. More refinement of the statistical constraints for testlet assembly is also necessary. However, even for this preliminary attempt at assembling content-balanced testlets, the two-stage computerized test simulated with these testlets performed quite well. (Contains 5 figures, 5 tables, and 12 references.) (Author/SLD)1 aReese, L M1 aSchnipke, D L1 aLuebke, S W uhttp://www.iacat.org/content/incorporating-content-constraints-multi-stage-adaptive-testlet-design00627nas a2200157 4500008004100000245011800041210006900159260002100228100001700249700001900266700001500285700001600300700001500316700001300331856012500344 1999 eng d00aLimiting answer review and change on computerized adaptive vocabulary tests: Psychometric and attitudinal results0 aLimiting answer review and change on computerized adaptive vocab aMontreal, Canada1 aVispoel, W P1 aHendrickson, A1 aBleiler, T1 aWidiatmo, H1 aShrairi, S1 aIhrig, D uhttp://www.iacat.org/content/limiting-answer-review-and-change-computerized-adaptive-vocabulary-tests-psychometric-and-000351nas a2200109 4500008004100000245004300041210004300084260002100127100001300148700001100161856006900172 1999 eng d00aMore efficient use of item inventories0 aMore efficient use of item inventories aMontreal, Canada1 aSmith, R1 aZhu, R uhttp://www.iacat.org/content/more-efficient-use-item-inventories00481nas a2200109 4500008004100000245009400041210006900135260001700204100001600221700001600237856011800253 1999 eng d00aReducing item exposure without reducing precision (much) in computerized adaptive testing0 aReducing item exposure without reducing precision much in comput aMontreal, CA1 aHolmes, R M1 aSegall, D O uhttp://www.iacat.org/content/reducing-item-exposure-without-reducing-precision-much-computerized-adaptive-testing00405nas a2200109 4500008004100000245005800041210005700099260002100156100001600177700001800193856008400211 1999 eng d00aResponse time feedback on computer-administered tests0 aResponse time feedback on computeradministered tests aMontreal, Canada1 aScrams, D J1 aSchnipke, D L uhttp://www.iacat.org/content/response-time-feedback-computer-administered-tests00284nas a2200097 4500008004100000245002700041210002600068260002100094100001500115856005600130 1999 eng d00aTest-taking strategies0 aTesttaking strategies aMontreal, Canada1 aSteffen, M uhttp://www.iacat.org/content/test-taking-strategies00405nas a2200109 4500008004100000245006000041210005900101260002100160100001500181700001300196856008600209 1999 eng d00aTest-taking strategies in computerized adaptive testing0 aTesttaking strategies in computerized adaptive testing aMontreal, Canada1 aSteffen, M1 aWay, W D uhttp://www.iacat.org/content/test-taking-strategies-computerized-adaptive-testing01190nas a2200157 4500008004100000245010900041210006900150300001200219490000700231520058300238653003400821100002300855700001600878700001800894856012000912 1999 eng d00aUsing response-time constraints to control for differential speededness in computerized adaptive testing0 aUsing responsetime constraints to control for differential speed a195-2100 v233 aAn item-selection algorithm is proposed for neutralizing the differential effects of time limits on computerized adaptive test scores. The method is based on a statistical model for distributions of examinees’ response times on items in a bank that is updated each time an item is administered. Predictions from the model are used as constraints in a 0-1 linear programming model for constrained adaptive testing that maximizes the accuracy of the trait estimator. The method is demonstrated empirically using an item bank from the Armed Services Vocational Aptitude Battery. 10acomputerized adaptive testing1 avan der Linden, WJ1 aScrams, D J1 aSchnipke, D L uhttp://www.iacat.org/content/using-response-time-constraints-control-differential-speededness-computerized-adaptive00348nas a2200121 4500008004100000245003300041210003300074260001700107100001100124700001300135700001600148856006200164 1998 eng d00aAdaptive testing without IRT0 aAdaptive testing without IRT aSan Diego CA1 aYan, D1 aLewis, C1 aStocking, M uhttp://www.iacat.org/content/adaptive-testing-without-irt00469nas a2200109 4500008004100000245009500041210006900136260001400205100001300219700001500232856011200247 1998 eng d00aApplication of an IRT ideal point model to computer adaptive assessment of job performance0 aApplication of an IRT ideal point model to computer adaptive ass aDallas TX1 aStark, S1 aDrasgow, F uhttp://www.iacat.org/content/application-irt-ideal-point-model-computer-adaptive-assessment-job-performance00687nas a2200169 4500008004100000020003000041245009600071210006900167260006400236100001900300700001700319700002100336700001300357700001700370700001500387856011500402 1998 eng d aETS Research Report 98-3800aComparability of paper-and-pencil and computer adaptive test scores on the GRE General Test0 aComparability of paperandpencil and computer adaptive test score aPrinceton, N.J.bEducational Testing ServicescAugust, 19981 aSchaeffer, G A1 aBridgeman, B1 aGolub-Smith, M L1 aLewis, C1 aPotenza, M T1 aSteffen, M uhttp://www.iacat.org/content/comparability-paper-and-pencil-and-computer-adaptive-test-scores-gre-general-test00729nas a2200157 4500008004100000245018900041210006900230260004700299100001700346700001700363700002100380700001300401700001700414700001500431856012500446 1998 eng d00aComparability of paper-and-pencil and computer adaptive test scores on the GRE General Test (GRE Board Professional Report No 95-08P; Educational Testing Service Research Report 98-38)0 aComparability of paperandpencil and computer adaptive test score aPrinceton, NJ: Educational Testing Service1 aSchaeffer, G1 aBridgeman, B1 aGolub-Smith, M L1 aLewis, C1 aPotenza, M T1 aSteffen, M uhttp://www.iacat.org/content/comparability-paper-and-pencil-and-computer-adaptive-test-scores-gre-general-test-gre-board00879nas a2200133 4500008004100000245006300041210006200104300001000166490000700176520043400183100002400617700001600641856008800657 1998 eng d00aComputerized adaptive testing: What it is and how it works0 aComputerized adaptive testing What it is and how it works a45-520 v383 aDescribes the workings of computerized adaptive testing (CAT). Focuses on the key concept of information and then discusses two important components of a CAT system: the calibrated item bank and the testing algorithm. Describes a CAT that was designed for making placement decisions on the basis of two typical test administrations and notes the most significant differences between traditional paper-based testing and CAT. (AEF)1 aStraetmans, G J J M1 aEggen, Theo uhttp://www.iacat.org/content/computerized-adaptive-testing-what-it-and-how-it-works01273nas a2200133 4500008004100000245008600041210006900127300001000196490000700206520078600213100001800999700001301017856010901030 1998 eng d00aControlling item exposure conditional on ability in computerized adaptive testing0 aControlling item exposure conditional on ability in computerized a57-750 v233 aThe interest in the application of large-scale adaptive testing for secure tests has served to focus attention on issues that arise when theoretical advances are made operational. One such issue is that of ensuring item and pool security in the continuous testing environment made possible by the computerized admin-istration of a test, as opposed to the more periodic testing environment typically used for linear paper-and-pencil tests. This article presents a new method of controlling the exposure rate of items conditional on ability level in this continuous testing environment. The properties of such conditional control on the exposure rates of items, when used in conjunction with a particular adaptive testing algorithm, are explored through studies with simulated data. 1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/controlling-item-exposure-conditional-ability-computerized-adaptive-testing00580nas a2200121 4500008004100000245009500041210006900136260009200205100001300297700001500310700001800325856011500343 1998 eng d00aDeveloping, maintaining, and renewing the item inventory to support computer-based testing0 aDeveloping maintaining and renewing the item inventory to suppor aComputer-Based Testing: Building the Foundation for Future Assessments, Philadelphia PA1 aWay, W D1 aSteffen, M1 aAnderson, G S uhttp://www.iacat.org/content/developing-maintaining-and-renewing-item-inventory-support-computer-based-testing00477nas 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-test00435nas 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-testing00380nas a2200097 4500008004100000245005200041210005000093260004600143100001800189856007500207 1998 eng d00aA framework for comparing adaptive test designs0 aframework for comparing adaptive test designs aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/framework-comparing-adaptive-test-designs00408nas a2200109 4500008004100000245006800041210006400109260001500173100001100188700001500199856008400214 1998 eng d00aThe impact of scoring flawed items on ability estimation in CAT0 aimpact of scoring flawed items on ability estimation in CAT aUrbana, IL1 aLiu, M1 aSteffen, M uhttp://www.iacat.org/content/impact-scoring-flawed-items-ability-estimation-cat00438nas a2200121 4500008004100000245006700041210006700108300001200175490000700187100001800194700001500212856008900227 1998 eng d00aOptimal design of item pools for computerized adaptive testing0 aOptimal design of item pools for computerized adaptive testing a271-2790 v221 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/optimal-design-item-pools-computerized-adaptive-testing00411nas a2200109 4500008004100000245006300041210006300104260001800167100001400185700001500199856008700214 1998 eng d00aPatterns of item exposure using a randomized CAT algorithm0 aPatterns of item exposure using a randomized CAT algorithm aSan Diego, CA1 aLunz, M E1 aStahl, J A uhttp://www.iacat.org/content/patterns-item-exposure-using-randomized-cat-algorithm01298nas a2200157 4500008004100000245007500041210006900116300001000185490000700195520076100202653003400963100001800997700001401015700001701029856009401046 1998 eng d00aSimulating the use of disclosed items in computerized adaptive testing0 aSimulating the use of disclosed items in computerized adaptive t a48-680 v353 aRegular use of questions previously made available to the public (i.e., disclosed items) may provide one way to meet the requirement for large numbers of questions in a continuous testing environment, that is, an environment in which testing is offered at test taker convenience throughout the year rather than on a few prespecified test dates. First it must be shown that such use has effects on test scores small enough to be acceptable. In this study simulations are used to explore the use of disclosed items under a worst-case scenario which assumes that disclosed items are always answered correctly. Some item pool and test designs were identified in which the use of disclosed items produces effects on test scores that may be viewed as negligible.10acomputerized adaptive testing1 aStocking, M L1 aWard, W C1 aPotenza, M T uhttp://www.iacat.org/content/simulating-use-disclosed-items-computerized-adaptive-testing00435nas a2200085 4500008004100000245010200041210006900143100001600212856012100228 1998 eng d00aSome considerations for eliminating biases in ability estimation in computerized adaptive testing0 aSome considerations for eliminating biases in ability estimation1 aSamejima, F uhttp://www.iacat.org/content/some-considerations-eliminating-biases-ability-estimation-computerized-adaptive-testing00677nas a2200121 4500008004100000245012000041210006900161260014400230100002300374700001600397700001800413856012400431 1998 eng d00aUsing response-time constraints to control for differential speededness in adaptive testing (Research Report 98-06)0 aUsing responsetime constraints to control for differential speed aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ1 aScrams, D J1 aSchnipke, D L uhttp://www.iacat.org/content/using-response-time-constraints-control-differential-speededness-adaptive-testing-research00584nas a2200145 4500008004100000245011400041210006900155260001200224100001400236700001700250700001600267700001600283700001900299856012000318 1997 eng d00aThe accuracy of examinee judgments of relative item difficulty: Implication for computerized adaptive testing0 aaccuracy of examinee judgments of relative item difficulty Impli aChicago1 aWise, S L1 aFreeman, S A1 aFinney, S J1 aEnders, C K1 aSeverance, D D uhttp://www.iacat.org/content/accuracy-examinee-judgments-relative-item-difficulty-implication-computerized-adaptive00368nas a2200109 4500008004100000245005300041210005000094300001200144490000700156100001800163856007700181 1997 eng d00aAn alternative method for scoring adaptive tests0 aalternative method for scoring adaptive tests a365-3890 v211 aStocking, M L uhttp://www.iacat.org/content/alternative-method-scoring-adaptive-tests-000364nas a2200097 4500008004100000245005400041210005400095260002100149100001600170856008000186 1997 eng d00aApplications of multidimensional adaptive testing0 aApplications of multidimensional adaptive testing aMontreal, Canada1 aSegall, D O uhttp://www.iacat.org/content/applications-multidimensional-adaptive-testing00521nas a2200121 4500008004100000245010200041210006900143260001800212100001500230700001800245700001600263856012000279 1997 eng d00aCalibration of CAT items administered online for classification: Assumption of local independence0 aCalibration of CAT items administered online for classification  aGatlinburg TN1 aSpray, J A1 aParshall, C G1 aHuang, C -H uhttp://www.iacat.org/content/calibration-cat-items-administered-online-classification-assumption-local-independence00451nas a2200109 4500008004100000245008100041210006900122260001600191100001800207700001500225856010100240 1997 eng d00aA comparison of testlet-based test designs for computerized adaptive testing0 acomparison of testletbased test designs for computerized adaptiv aChicago, IL1 aSchnipke, D L1 aReese, L M uhttp://www.iacat.org/content/comparison-testlet-based-test-designs-computerized-adaptive-testing01686nam a2200145 4500008004100000245006100041210006000102260006200162520115300224653003401377100001501411700001601426700001701442856008101459 1997 eng d00aComputerized adaptive testing: From inquiry to operation0 aComputerized adaptive testing From inquiry to operation aWashington, D.C., USAbAmerican Psychological Association3 a(from the cover) This book traces the development of computerized adaptive testing (CAT) from its origins in the 1960s to its integration with the Armed Services Vocational Aptitude Battery (ASVAB) in the 1990s. A paper-and-pencil version of the battery (P&P-ASVAB) has been used by the Defense Department since the 1970s to measure the abilities of applicants for military service. The test scores are used both for initial qualification and for classification into entry-level training opportunities. /// This volume provides the developmental history of the CAT-ASVAB through its various stages in the Joint-Service arena. Although the majority of the book concerns the myriad technical issues that were identified and resolved, information is provided on various political and funding support challenges that were successfully overcome in developing, testing, and implementing the battery into one of the nation's largest testing programs. The book provides useful information to professionals in the testing community and everyone interested in personnel assessment and evaluation. (PsycINFO Database Record (c) 2004 APA, all rights reserved).10acomputerized adaptive testing1 aSands, W A1 aWaters, B K1 aMcBride, J R uhttp://www.iacat.org/content/computerized-adaptive-testing-inquiry-operation00468nas a2200133 4500008004100000245006100041210006100102260002400163100001700187700001500204700001300219700001400232856008800246 1997 eng d00aComputerized adaptive testing through the World Wide Web0 aComputerized adaptive testing through the World Wide Web a(ERIC No. ED414536)1 aShermis, M D1 aMzumara, H1 aBrown, M1 aLillig, C uhttp://www.iacat.org/content/computerized-adaptive-testing-through-world-wide-web-000352nas a2200085 4500008004100000245006100041210006100102100001700163856008600180 1997 eng d00aComputerized adaptive testing through the World Wide Web0 aComputerized adaptive testing through the World Wide Web1 aShermis, M D uhttp://www.iacat.org/content/computerized-adaptive-testing-through-world-wide-web00500nas a2200121 4500008004100000245008900041210006900130260001500199100001700214700001500231700001500246856011700261 1997 eng d00aControlling test and computer anxiety: Test performance under CAT and SAT conditions0 aControlling test and computer anxiety Test performance under CAT aChicago IL1 aShermis, M D1 aMzumara, H1 aBublitz, S uhttp://www.iacat.org/content/controlling-test-and-computer-anxiety-test-performance-under-cat-and-sat-conditions00493nas a2200109 4500008004100000245003400041210003400075260017900109100001600288700001600304856006300320 1997 eng d00aCurrent and future challenges0 aCurrent and future challenges aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.). Computerized adaptive testing: From inquiry to operation (pp 257-269). Washington DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E uhttp://www.iacat.org/content/current-and-future-challenges00353nas a2200097 4500008004100000245005300041210005300094260001600147100001500163856007700178 1997 eng d00aDetecting misbehaving items in a CAT environment0 aDetecting misbehaving items in a CAT environment aChicago, IL1 aSwygert, K uhttp://www.iacat.org/content/detecting-misbehaving-items-cat-environment00406nas 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-asvab00578nas 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-reasoning00620nas 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-testing00390nas a2200121 4500008004100000245005000041210005000091300001000141490000600151100001700157700001800174856007600192 1997 eng d00aFlawed items in computerized adaptive testing0 aFlawed items in computerized adaptive testing a79-960 v41 aPotenza, M T1 aStocking, M L uhttp://www.iacat.org/content/flawed-items-computerized-adaptive-testing00536nas a2200121 4500008004100000245009400041210006900135260004600204100001500250700001800265700001600283856011500299 1997 eng d00aIncorporating content constraints into a multi-stage adaptive testlet design: LSAC report0 aIncorporating content constraints into a multistage adaptive tes aNewtown, PA: Law School Admission Council1 aReese, L M1 aSchnipke, D L1 aLuebke, S W uhttp://www.iacat.org/content/incorporating-content-constraints-multi-stage-adaptive-testlet-design-lsac-report00426nas a2200109 4500008004100000245007200041210006900113260001200182100001300194700001300207856009600220 1997 eng d00aIncorporating decision consistency into Bayesian sequential testing0 aIncorporating decision consistency into Bayesian sequential test aChicago1 aSmith, R1 aLewis, C uhttp://www.iacat.org/content/incorporating-decision-consistency-bayesian-sequential-testing00922nas a2200145 4500008004100000245003900041210003800080260006100118300001200179520047000191100001600661700001700677700001700694856006500711 1997 eng d00aItem exposure control in CAT-ASVAB0 aItem exposure control in CATASVAB aWashington D.C., USAbAmerican Psychological Association a141-1443 aDescribes the method used to control item exposure in computerized adaptive testing-Armed Services Vocational Aptitude Battery (CAT-ASVAB). The method described was developed specifically to ensure that CAT-ASVAB items were expose no more often than the items in the printers ASVAB's alternate forms, ensuring that CAT ASVAB is nor more vulnerable than printed ASVAB forms to comprise from item exposure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)1 aHetter, R D1 aSympson, J B1 aMcBride, J R uhttp://www.iacat.org/content/item-exposure-control-cat-asvab00543nas a2200121 4500008004100000245004100041210004100082260018000123100001600303700001600319700001600335856007000351 1997 eng d00aItem pool development and evaluation0 aItem pool development and evaluation aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 117-130). Washington DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aHetter, D H uhttp://www.iacat.org/content/item-pool-development-and-evaluation00412nas a2200121 4500008004100000245005400041210005400095260001500149100001600164700001600180700001800196856007600214 1997 eng d00aMaintaining a CAT item pool with operational data0 aMaintaining a CAT item pool with operational data aChicago IL1 aLevine, M L1 aSegall, D O1 aWilliams, B A uhttp://www.iacat.org/content/maintaining-cat-item-pool-operational-data00449nas a2200109 4500008004100000245008000041210006900121260001600190100001700206700001500223856010100238 1997 eng d00aMaintaining item and test security in a CAT environment: A simulation study0 aMaintaining item and test security in a CAT environment A simula aChicago IL)1 aPatsula, L N1 aSteffen, M uhttp://www.iacat.org/content/maintaining-item-and-test-security-cat-environment-simulation-study01318nas a2200265 4500008004100000245005500041210005400096300001200150490000600162520053000168653003800698653002000736653001400756653003500770653003100805653001100836653001900847653001800866653002800884100001300912700001500925700001700940700001400957856008100971 1997 eng d00aOn-line performance assessment using rating scales0 aOnline performance assessment using rating scales a173-1910 v13 aThe purpose of this paper is to report on the development of the on-line performance assessment instrument--the Assessment of Motor and Process Skills (AMPS). Issues that will be addressed in the paper include: (a) the establishment of the scoring rubric and its implementation in an extended Rasch model, (b) training of raters, (c) validation of the scoring rubric and procedures for monitoring the internal consistency of raters, and (d) technological implementation of the assessment instrument in a computerized program.10a*Outcome Assessment (Health Care)10a*Rehabilitation10a*Software10a*Task Performance and Analysis10aActivities of Daily Living10aHumans10aMicrocomputers10aPsychometrics10aPsychomotor Performance1 aStahl, J1 aShumway, R1 aBergstrom, B1 aFisher, A uhttp://www.iacat.org/content/line-performance-assessment-using-rating-scales00613nas a2200133 4500008004100000245005600041210005500097260018200152100001600334700001600350700001600366700001600382856008100398 1997 eng d00aPsychometric procedures for administering CAT-ASVAB0 aPsychometric procedures for administering CATASVAB aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 131-140). Washington D.C.: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aBloxom, B M1 aHetter, R D uhttp://www.iacat.org/content/psychometric-procedures-administering-cat-asvab00607nas a2200145 4500008004100000245012900041210006900170260001500239100002000254700002000274700001400294700001500308700001700323856012100340 1997 eng d00aRelationship of response latency to test design, examinee ability, and item difficulty in computer-based test administration0 aRelationship of response latency to test design examinee ability aChicago IL1 aSwanson, D., B.1 aFeatherman, C M1 aCase, A M1 aLuecht, RM1 aNungester, R uhttp://www.iacat.org/content/relationship-response-latency-test-design-examinee-ability-and-item-difficulty-computer00544nas a2200109 4500008004100000245005200041210005100093260018000144100001600324700001600340856007800356 1997 eng d00aReliability and construct validity of CAT-ASVAB0 aReliability and construct validity of CATASVAB aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.). Computerized adaptive testing: From inquiry to operation (pp. 169-179). Washington DC: American Psychological Association.1 aMoreno, K E1 aSegall, O D uhttp://www.iacat.org/content/reliability-and-construct-validity-cat-asvab01406nas a2200133 4500008004100000245008900041210006900130300001200199490000700211520089300218653003401111100001801145856010901163 1997 eng d00aRevising item responses in computerized adaptive tests: A comparison of three models0 aRevising item responses in computerized adaptive tests A compari a129-1420 v213 aInterest in the application of large-scale computerized adaptive testing has focused attention on issues that arise when theoretical advances are made operational. One such issue is that of the order in which exaniinees address questions within a test or separately timed test section. In linear testing, this order is entirely under the control of the examinee, who can look ahead at questions and return and revise answers to questions. Using simulation, this study investigated three models that permit restricted examinee control over revising previous answers in the context of adaptive testing. Even under a worstcase model of examinee revision behavior, two of the models of permitting item revisions worked well in preserving test fairness and accuracy. One model studied may also preserve some cognitive processing styles developed by examinees for a linear testing environment. 10acomputerized adaptive testing1 aStocking, M L uhttp://www.iacat.org/content/revising-item-responses-computerized-adaptive-tests-comparison-three-models00542nas a2200121 4500008004100000245009900041210006900140260004600209100001800255700001400273700001700287856011600304 1997 eng d00aSimulating the use of disclosed items in computerized adaptive testing (Research Report 97-10)0 aSimulating the use of disclosed items in computerized adaptive t aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aWard, W C1 aPotenza, M T uhttp://www.iacat.org/content/simulating-use-disclosed-items-computerized-adaptive-testing-research-report-97-1000608nas a2200133 4500008004100000245014700041210006900188260002600257100001500283700002200298700001600320700001200336856012600348 1997 eng d00aUnidimensional approximations for a computerized adaptive test when the item pool and latent space are multidimensional (Research Report 97-5)0 aUnidimensional approximations for a computerized adaptive test w aIowa City IA: ACT Inc1 aSpray, J A1 aAbdel-Fattah, A A1 aHuang, C -Y1 aLau, CA uhttp://www.iacat.org/content/unidimensional-approximations-computerized-adaptive-test-when-item-pool-and-latent-space-are00617nas a2200145 4500008004100000245005200041210005100093260016700144100001600311700001600327700002100343700001600364700001700380856007400397 1997 eng d00aValidation of the experimental CAT-ASVAB system0 aValidation of the experimental CATASVAB system aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation. Washington, DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aKieckhaefer, W F1 aVicino, F L1 aMcBride, J R uhttp://www.iacat.org/content/validation-experimental-cat-asvab-system00366nas a2200109 4500008004100000245005300041210005000094300001200144490000700156100001800163856007500181 1996 eng d00aAn alternative method for scoring adaptive tests0 aalternative method for scoring adaptive tests a365-3890 v211 aStocking, M L uhttp://www.iacat.org/content/alternative-method-scoring-adaptive-tests00534nas a2200121 4500008004100000245012700041210006900168300001200237490000700249100001500256700001700271856012400288 1996 eng d00aComparison of SPRT and sequential Bayes procedures for classifying examinees into two categories using a computerized test0 aComparison of SPRT and sequential Bayes procedures for classifyi a405-4140 v211 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/comparison-sprt-and-sequential-bayes-procedures-classifying-examinees-two-categories-using00484nas a2200133 4500008004100000245007400041210006900115300001000184490001000194100001700204700001700221700001400238856009800252 1996 eng d00aComputerized adaptive skill assessment in a statewide testing program0 aComputerized adaptive skill assessment in a statewide testing pr a49-670 v29(1)1 aShermis, M D1 aStemmer, P M1 aWebb, P M uhttp://www.iacat.org/content/computerized-adaptive-skill-assessment-statewide-testing-program00541nas a2200109 4500008004100000245012900041210006900170260003400239100001600273700002400289856011800313 1996 eng d00aComputerized adaptive testing for classifying examinees into three categories (Measurement and Research Department Rep 96-3)0 aComputerized adaptive testing for classifying examinees into thr aArnhem, The Netherlands: Cito1 aEggen, Theo1 aStraetmans, G J J M uhttp://www.iacat.org/content/computerized-adaptive-testing-classifying-examinees-three-categories-measurement-and00450nas a2200109 4500008004100000245008300041210006900124300001000193100001700203700001200220856010800232 1996 eng d00aComputerized adaptive testing for reading assessment and diagnostic assessment0 aComputerized adaptive testing for reading assessment and diagnos a18-201 aShermis, M D1 aet. al. uhttp://www.iacat.org/content/computerized-adaptive-testing-reading-assessment-and-diagnostic-assessment00439nas a2200109 4500008004100000245007200041210006900113260001600182100001600198700001800214856009700232 1996 eng d00aComputing scores for incomplete GRE General computer adaptive tests0 aComputing scores for incomplete GRE General computer adaptive te aNew York NY1 aSlater, S C1 aSchaffer, G A uhttp://www.iacat.org/content/computing-scores-incomplete-gre-general-computer-adaptive-tests00482nas 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-violated00543nas 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-testing00331nas a2200109 4500008004100000245003800041210003800079300001200117490000700129100001600136856006900152 1996 eng d00aMultidimensional adaptive testing0 aMultidimensional adaptive testing a331-3540 v611 aSegall, D O uhttp://www.iacat.org/content/multidimensional-adaptive-testing-000978nas a2200121 4500008004100000245003800041210003800079300001200117490000700129520063700136100001600773856006700789 1996 eng d00aMultidimensional adaptive testing0 aMultidimensional adaptive testing a331-3540 v613 aMaximum likelihood and Bayesian procedures for item selection and scoring of multidimensional adaptive tests are presented. A demonstration using simulated response data illustrates that multidimensional adaptive testing (MAT) can provide equal or higher reliabilities with about one-third fewer items than are required by one-dimensional adaptive testing (OAT). Furthermore, holding test-length constant across the MAT and OAT approaches, substantial improvements in reliability can be obtained from multidimensional assessment. A number of issues relating to the operational use of multidimensional adaptive testing are discussed.1 aSegall, D O uhttp://www.iacat.org/content/multidimensional-adaptive-testing00520nas a2200121 4500008004100000245010300041210006900144260001300213100002000226700001800246700001400264856012000278 1996 eng d00aNew algorithms for item selection and exposure and proficiency estimation under 1- and 2-PL models0 aNew algorithms for item selection and exposure and proficiency e aNew York1 aFeatherman, C M1 aSubhiyah, R G1 aHadadi, A uhttp://www.iacat.org/content/new-algorithms-item-selection-and-exposure-and-proficiency-estimation-under-1-and-2-pl00501nas a2200109 4500008004100000245009100041210006900132260004600201100001800247700001500265856011100280 1996 eng d00aOptimal design of item pools for computerized adaptive testing (Research Report 96-34)0 aOptimal design of item pools for computerized adaptive testing R aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/optimal-design-item-pools-computerized-adaptive-testing-research-report-96-3400432nas a2200121 4500008004100000245006600041210006500107300001200172490000600184100001000190700001800200856009200218 1996 eng d00aPractical issues in large-scale computerized adaptive testing0 aPractical issues in largescale computerized adaptive testing a287-3040 v91 aMills1 aStocking, M L uhttp://www.iacat.org/content/practical-issues-large-scale-computerized-adaptive-testing00494nas a2200097 4500008004100000245010200041210006900143260004600212100001800258856012000276 1996 eng d00aRevising item responses in computerized adaptive testing: A comparison of three models (RR-96-12)0 aRevising item responses in computerized adaptive testing A compa aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/revising-item-responses-computerized-adaptive-testing-comparison-three-models-rr-96-1200509nas a2200109 4500008004100000245012400041210006900165260001300234100001300247700001300260856012600273 1996 eng d00aA search procedure to determine sets of decision points when using testlet-based Bayesian sequential testing procedures0 asearch procedure to determine sets of decision points when using aNew York1 aSmith, R1 aLewis, C uhttp://www.iacat.org/content/search-procedure-determine-sets-decision-points-when-using-testlet-based-bayesian-sequential00515nas a2200121 4500008004100000245010200041210006900143260001400212100001200226700002200238700001500260856011800275 1996 eng d00aUsing unidimensional IRT models for dichotomous classification via CAT with multidimensional data0 aUsing unidimensional IRT models for dichotomous classification v aBoston MA1 aLau, CA1 aAbdel-Fattah, A A1 aSpray, J A uhttp://www.iacat.org/content/using-unidimensional-irt-models-dichotomous-classification-cat-multidimensional-data00421nas a2200109 4500008004100000245006700041210006500108260002100173100001500194700001300209856008900222 1995 eng d00aA Bayesian computerized mastery model with multiple cut scores0 aBayesian computerized mastery model with multiple cut scores aSan Francisco CA1 aSmith, R L1 aLewis, C uhttp://www.iacat.org/content/bayesian-computerized-mastery-model-multiple-cut-scores00447nas a2200109 4500008004100000245007900041210006900120260001800189100001600207700001800223856009600241 1995 eng d00aComparability studies for the GRE CAT General Test and the NCLEX using CAT0 aComparability studies for the GRE CAT General Test and the NCLEX aSan Francisco1 aEignor, D R1 aSchaffer, G A uhttp://www.iacat.org/content/comparability-studies-gre-cat-general-test-and-nclex-using-cat00542nas a2200121 4500008004100000245011400041210006900155260002100224100001500245700001800260700001800278856012400296 1995 eng d00aA comparison of classification agreement between adaptive and full-length test under the 1-PL and 2-PL models0 acomparison of classification agreement between adaptive and full aSan Francisco CA1 aLewis, M J1 aSubhiyah, R G1 aMorrison, C A uhttp://www.iacat.org/content/comparison-classification-agreement-between-adaptive-and-full-length-test-under-1-pl-and-200522nas a2200109 4500008004100000245012500041210006900166260002100235100001700256700001900273856012000292 1995 eng d00aA comparison of gender differences on paper-and-pencil and computer-adaptive versions of the Graduate Record Examination0 acomparison of gender differences on paperandpencil and computera aSan Francisco CA1 aBridgeman, B1 aSchaeffer, G A uhttp://www.iacat.org/content/comparison-gender-differences-paper-and-pencil-and-computer-adaptive-versions-graduate00445nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001400215856009400229 1995 eng d00aA comparison of item selection routines in linear and adaptive tests0 acomparison of item selection routines in linear and adaptive tes a227-2420 v321 aSchnipke1 aGreen, BF uhttp://www.iacat.org/content/comparison-item-selection-routines-linear-and-adaptive-tests00533nas a2200121 4500008004100000245011800041210006900159260001800228100001300246700001300259700001500272856012400287 1995 eng d00aA comparison of two IRT-based models for computerized mastery testing when item parameter estimates are uncertain0 acomparison of two IRTbased models for computerized mastery testi aSan Francisco1 aWay, W D1 aLewis, C1 aSmith, R L uhttp://www.iacat.org/content/comparison-two-irt-based-models-computerized-mastery-testing-when-item-parameter-estimates00533nas a2200109 4500008004100000245011000041210006900151260004700220100001800267700001300285856012500298 1995 eng d00aControlling item exposure conditional on ability in computerized adaptive testing (Research Report 95-25)0 aControlling item exposure conditional on ability in computerized aPrinceton NJ: Educational Testing Service.1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/controlling-item-exposure-conditional-ability-computerized-adaptive-testing-research-report00592nas 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-vs00402nas 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-scores00375nas 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-approach00401nas 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-samples00648nas a2200133 4500008004100000245017200041210006900213260004600282100001900328700001700347700001500364700001300379856012200392 1995 eng d00aThe introduction and comparability of the computer-adaptive GRE General Test (GRE Board Professional Report 88-08ap; Educational Testing Service Research Report 95-20)0 aintroduction and comparability of the computeradaptive GRE Gener aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M L1 aMills, C N1 aDurso, R uhttp://www.iacat.org/content/introduction-and-comparability-computer-adaptive-gre-general-test-gre-board-professional00506nas a2200121 4500008004100000245009100041210006900132260002100201100001600222700001300238700001700251856011600268 1995 eng d00aItem exposure rates for unconstrained and content-balanced computerized adaptive tests0 aItem exposure rates for unconstrained and contentbalanced comput aSan Francisco CA1 aMorrison, C1 aSubhiyah1 aNungester, R uhttp://www.iacat.org/content/item-exposure-rates-unconstrained-and-content-balanced-computerized-adaptive-tests00522nas a2200109 4500008004100000245010300041210006900144260004600213100001800259700001300277856012200290 1995 eng d00aA new method of controlling item exposure in computerized adaptive testing (Research Report 95-25)0 anew method of controlling item exposure in computerized adaptive aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aLewis, C uhttp://www.iacat.org/content/new-method-controlling-item-exposure-computerized-adaptive-testing-research-report-95-2500529nas a2200109 4500008004100000245010200041210006900143260004800212100001500260700001800275856012600293 1995 eng d00aPractical issues in large-scale high-stakes computerized adaptive testing (Research Report 95-23)0 aPractical issues in largescale highstakes computerized adaptive  aPrinceton, NJ: Educational Testing Service.1 aMills, C N1 aStocking, M L uhttp://www.iacat.org/content/practical-issues-large-scale-high-stakes-computerized-adaptive-testing-research-report-95-2300400nas a2200109 4500008004100000245005800041210005800099260001900157100001600176700001500192856008300207 1995 eng d00aSome new methods for content balancing adaptive tests0 aSome new methods for content balancing adaptive tests aMinneapolis MN1 aSegall, D O1 aDavey, T C uhttp://www.iacat.org/content/some-new-methods-content-balancing-adaptive-tests00550nas a2200133 4500008004100000245012000041210006900161300001400230490000700244100001600251700001500267700001800282856011600300 1995 eng d00aTheoretical results and item selection from multidimensional item bank in the Mokken IRT model for polytomous items0 aTheoretical results and item selection from multidimensional ite a337–3520 v191 aHemker, B T1 aSijtsma, K1 aMolenaar, I W uhttp://www.iacat.org/content/theoretical-results-and-item-selection-multidimensional-item-bank-mokken-irt-model00344nas a2200097 4500008004100000245003200041210003100073260006500104100001600169856006100185 1994 eng d00aCAT-GATB simulation studies0 aCATGATB simulation studies aSan Diego CA: Navy Personnel Research and Development Center1 aSegall, D O uhttp://www.iacat.org/content/cat-gatb-simulation-studies00480nas a2200133 4500008004100000245007400041210006900115300001200184490000700196100001600203700001600219700001600235856009500251 1994 eng d00aA comparison of item calibration media in computerized adaptive tests0 acomparison of item calibration media in computerized adaptive te a197-2040 v181 aHetter, R D1 aSegall, D O1 aBloxom, B M uhttp://www.iacat.org/content/comparison-item-calibration-media-computerized-adaptive-tests00464nas a2200121 4500008004500000245007600045210006900121490000700190100001600197700001600213700001600229856009700245 1994 Engldsh 00aA Comparison of Item Calibration Media in Computerized Adaptive Testing0 aComparison of Item Calibration Media in Computerized Adaptive Te0 v181 aHetter, R D1 aSegall, D O1 aBloxom, B M uhttp://www.iacat.org/content/comparison-item-calibration-media-computerized-adaptive-testing00426nas a2200109 4500008004100000245007100041210006900112300001000181490001100191100001500202856009900217 1994 eng d00aComputerized adaptive testing: Revolutionizing academic assessment0 aComputerized adaptive testing Revolutionizing academic assessmen a32-350 v65 (1)1 aSmittle, P uhttp://www.iacat.org/content/computerized-adaptive-testing-revolutionizing-academic-assessment00512nas a2200109 4500008004100000245013000041210006900171260001600240100001100256700001500267856012000282 1994 eng d00aThe effect of restricting ability distributions in the estimation of item difficulties: Implications for a CAT implementation0 aeffect of restricting ability distributions in the estimation of aNew Orleans1 aIto, K1 aSykes, R C uhttp://www.iacat.org/content/effect-restricting-ability-distributions-estimation-item-difficulties-implications-cat00477nas a2200121 4500008004100000245009200041210006900133300001200202490000600214100001500220700001400235856010600249 1994 eng d00aThe effect of review on the psychometric characteristics of computerized adaptive tests0 aeffect of review on the psychometric characteristics of computer a211-2220 v71 aStone, G E1 aLunz, M E uhttp://www.iacat.org/content/effect-review-psychometric-characteristics-computerized-adaptive-tests-000478nas a2200121 4500008004100000245009200041210006900133300001200202490000900214100001400223700001500237856010400252 1994 eng d00aThe effect of review on the psychometric characteristics of computerized adaptive tests0 aeffect of review on the psychometric characteristics of computer a211-2220 v7(3)1 aLunz, M E1 aStone, G E uhttp://www.iacat.org/content/effect-review-psychometric-characteristics-computerized-adaptive-tests01351nas a2200133 4500008004100000245009100041210006900132300001200201490000600213520086600219100001501085700001401100856010301114 1994 eng d00aThe effect of review on the psychometric characterstics of computerized adaptive tests0 aeffect of review on the psychometric characterstics of computeri a211-2220 v73 aExplored the effect of reviewing items and altering responses on examinee ability estimates, test precision, test information, decision confidence, and pass/fail status for computerized adaptive tests. Two different populations of examinees took different computerized certification examinations. For purposes of analysis, each population was divided into 3 ability groups (high, medium, and low). Ability measures before and after review were highly correlated, but slightly lower decision confidence was found after review. Pass/fail status was most affected for examinees with estimates close to the pass point. Decisions remained the same for 94% of the examinees. Test precision is only slightly affected by review, and the average information loss can be recovered by the addition of one item. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aStone, G E1 aLunz, M E uhttp://www.iacat.org/content/effect-review-psychometric-characterstics-computerized-adaptive-tests00481nas a2200097 4500008004100000245010700041210006900148260002900217100001500246856012200261 1994 eng d00aThe historical developments of fit and its assessment in the computerized adaptive testing environment0 ahistorical developments of fit and its assessment in the compute aChicago, IL USAc10/19941 aStone, G E uhttp://www.iacat.org/content/historical-developments-fit-and-its-assessment-computerized-adaptive-testing-environment00508nas a2200109 4500008004100000245012100041210006900162260001900231100001500250700001400265856011900279 1994 eng d00aItem calibration considerations: A comparison of item calibrations on written and computerized adaptive examinations0 aItem calibration considerations A comparison of item calibration aNew Orleans LA1 aStone, G E1 aLunz, M E uhttp://www.iacat.org/content/item-calibration-considerations-comparison-item-calibrations-written-and-computerized00497nas a2200133 4500008003900000245007500039210006900114260002000183100001600203700000900219700001300228700001800241856010400259 1994 d00aPinpointing PRAXIS I CAT characteristics through simulation procedures0 aPinpointing PRAXIS I CAT characteristics through simulation proc aNew Orleans, LA1 aEignor, D R1 aFolk1 aLi, M -Y1 aStocking, M L uhttp://www.iacat.org/content/pinpointing-praxis-i-cat-characteristics-through-simulation-procedures00446nas a2200109 4500008004100000245008200041210006900123260001900192100001700211700001500228856009300243 1994 eng d00aThe selection of test items for decision making with a computer adaptive test0 aselection of test items for decision making with a computer adap aNew Orleans LA1 aReckase, M D1 aSpray, J A uhttp://www.iacat.org/content/selection-test-items-decision-making-computer-adaptive-test00448nas a2200109 4500008004100000245008200041210006900123260001900192100001500211700001700226856009500243 1994 eng d00aThe selection of test items for decision making with a computer adaptive test0 aselection of test items for decision making with a computer adap aNew Orleans LA1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/selection-test-items-decision-making-computer-adaptive-test-000474nas a2200097 4500008004100000245009000041210006900131260004600200100001800246856011200264 1994 eng d00aThree practical issues for modern adaptive testing item pools (Research Report 94-5),0 aThree practical issues for modern adaptive testing item pools Re aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/three-practical-issues-modern-adaptive-testing-item-pools-research-report-94-500468nas a2200133 4500008004100000245007100041210006700112300001200179490000700191100001800198700001500216700001600231856008700247 1993 eng d00aThe application of an automated item selection method to real data0 aapplication of an automated item selection method to real data a167-1760 v171 aStocking, M L1 aSwanson, L1 aPearlman, M uhttp://www.iacat.org/content/application-automated-item-selection-method-real-data00568nas a2200133 4500008004100000245009600041210006900137260004600206100001600252700001800268700001300286700001500299856012000314 1993 eng d00aCase studies in computer adaptive test design through simulation (Research Report RR-93-56)0 aCase studies in computer adaptive test design through simulation aPrinceton NJ: Educational Testing Service1 aEignor, D R1 aStocking, M L1 aWay, W D1 aSteffen, M uhttp://www.iacat.org/content/case-studies-computer-adaptive-test-design-through-simulation-research-report-rr-93-5600568nas a2200133 4500008004100000245009700041210006900138260004600207100001600253700001300269700001600282700001500298856012100313 1993 eng d00aCase studies in computerized adaptive test design through simulation (Research Report 93-56)0 aCase studies in computerized adaptive test design through simula aPrinceton NJ: Educational Testing Service1 aEignor, D R1 aWay, W D1 aStocking, M1 aSteffen, M uhttp://www.iacat.org/content/case-studies-computerized-adaptive-test-design-through-simulation-research-report-93-5600490nas a2200097 4500008004100000245012400041210006900165100001500234700001700249856012600266 1993 eng d00aComparison of SPRT and sequential Bayes procedures for classifying examinees into two categories using an adaptive test0 aComparison of SPRT and sequential Bayes procedures for classifyi1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/comparison-sprt-and-sequential-bayes-procedures-classifying-examinees-two-categories-using-000334nas a2200109 4500008004100000245004100041210004000082300000900122490001100131100001500142856006700157 1993 eng d00aComputer adaptive testing: A new era0 aComputer adaptive testing A new era a8-100 v17 (1)1 aSmittle, P uhttp://www.iacat.org/content/computer-adaptive-testing-new-era00482nas a2200109 4500008004100000245009500041210006900136260002000205100001300225700001400238856012000252 1993 eng d00aComputerized adaptive testing in computer science: assessing student programming abilities0 aComputerized adaptive testing in computer science assessing stud aIndianapolis IN1 aSyang, A1 aDale, N B uhttp://www.iacat.org/content/computerized-adaptive-testing-computer-science-assessing-student-programming-abilities00494nas a2200097 4500008004100000245010000041210006900141260004600210100001800256856012200274 1993 eng d00aControlling item exposure rates in a realistic adaptive testing paradigm (Research Report 93-2)0 aControlling item exposure rates in a realistic adaptive testing  aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/controlling-item-exposure-rates-realistic-adaptive-testing-paradigm-research-report-93-200645nas a2200145 4500008004100000245014000041210006900181260004700250100001900297700001500316700001500331700001800346700001500364856012000379 1993 eng d00aField test of a computer-based GRE general test (GRE Board Technical Report 88-8; Educational Testing Service Research Rep No RR 93-07)0 aField test of a computerbased GRE general test GRE Board Technic aPrinceton NJ: Educational Testing Service.1 aSchaeffer, G A1 aReese, C M1 aSteffen, M1 aMcKinley, R L1 aMills, C N uhttp://www.iacat.org/content/field-test-computer-based-gre-general-test-gre-board-technical-report-88-8-educational00517nas a2200121 4500008004100000245008100041210006900122260004600191100001900237700001500256700002100271856010300292 1993 eng d00aIntroduction of a computer adaptive GRE General test (Research Report 93-57)0 aIntroduction of a computer adaptive GRE General test Research Re aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M1 aGolub-Smith, M L uhttp://www.iacat.org/content/introduction-computer-adaptive-gre-general-test-research-report-93-5700543nas a2200121 4500008004100000245009600041210006900137260005100206100001600257700001600273700001600289856011600305 1993 eng d00aItem Calibration: Medium-of-administration effect on computerized adaptive scores (TR-93-9)0 aItem Calibration Mediumofadministration effect on computerized a aNavy Personnel Research and Development Center1 aHetter, R D1 aBloxom, B M1 aSegall, D O uhttp://www.iacat.org/content/item-calibration-medium-administration-effect-computerized-adaptive-scores-tr-93-900549nas a2200121 4500008004100000245014600041210006900187300001200256490000700268100001400275700001500289856012300304 1993 eng d00aLinking the standard and advanced forms of the Ravens Progressive Matrices in both the paper-and-pencil and computer-adaptive-testing formats0 aLinking the standard and advanced forms of the Ravens Progressiv a905-9250 v531 aStyles, I1 aAndrich, D uhttp://www.iacat.org/content/linking-standard-and-advanced-forms-ravens-progressive-matrices-both-paper-and-pencil-and00445nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001500215856009300230 1993 eng d00aA method for severely constrained item selection in adaptive testing0 amethod for severely constrained item selection in adaptive testi a277-2920 v171 aStocking1 aSwanson, L uhttp://www.iacat.org/content/method-severely-constrained-item-selection-adaptive-testing00456nas a2200121 4500008004500000245007300045210006900118300001200187490000700199100001800206700001500224856009500239 1993 Engldsh 00aA Method for Severely Constrained Item Selection in Adaptive Testing0 aMethod for Severely Constrained Item Selection in Adaptive Testi a277-2920 v171 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/method-severely-constrained-item-selection-adaptive-testing-100448nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001300202700001500215856009600230 1993 eng d00aA model and heuristic for solving very large item selection problems0 amodel and heuristic for solving very large item selection proble a151-1660 v171 aStocking1 aSwanson, L uhttp://www.iacat.org/content/model-and-heuristic-solving-very-large-item-selection-problems00326nas a2200097 4500008004100000245004100041210004100082260001700123100001800140856007000158 1993 eng d00aModern computerized adaptive testing0 aModern computerized adaptive testing aPrinceton NJ1 aStocking, M L uhttp://www.iacat.org/content/modern-computerized-adaptive-testing00491nas a2200097 4500008004100000245010200041210006900143260004100212100001500253856012500268 1993 eng d00aMultiple-category classification using a sequential probability ratio test (Research report 93-7)0 aMultiplecategory classification using a sequential probability r aIowa City: American College Testing.1 aSpray, J A uhttp://www.iacat.org/content/multiple-category-classification-using-sequential-probability-ratio-test-research-report-9300526nas a2200121 4500008004100000245011500041210006900156260001200225100001800237700001700255700001400272856011800286 1993 eng d00aA simulated comparison of testlets and a content balancing procedure for an adaptive certification examination0 asimulated comparison of testlets and a content balancing procedu aAtlanta1 aReshetar, R A1 aNorcini, J J1 aShea, J A uhttp://www.iacat.org/content/simulated-comparison-testlets-and-content-balancing-procedure-adaptive-certification00563nas a2200121 4500008004100000245014400041210006900185260001200254100001800266700001700284700001400301856012600315 1993 eng d00aA simulated comparison of two content balancing and maximum information item selection procedures for an adaptive certification examination0 asimulated comparison of two content balancing and maximum inform aAtlanta1 aReshetar, R A1 aNorcini, J J1 aShea, J A uhttp://www.iacat.org/content/simulated-comparison-two-content-balancing-and-maximum-information-item-selection-procedures00434nas a2200097 4500008004100000245008800041210006900129260001700198100001300215856010800228 1993 eng d00aSome initial experiments with adaptive survey designs for structured questionnaires0 aSome initial experiments with adaptive survey designs for struct aCambridge MA1 aSingh, J uhttp://www.iacat.org/content/some-initial-experiments-adaptive-survey-designs-structured-questionnaires00487nas a2200121 4500008004100000245008400041210006900125260001500194100001400209700001500223700002400238856010300262 1993 eng d00aTest targeting and precision before and after review on computer-adaptive tests0 aTest targeting and precision before and after review on computer aAtlanta GA1 aLunz, M E1 aStahl, J A1 aBergstrom, Betty, A uhttp://www.iacat.org/content/test-targeting-and-precision-and-after-review-computer-adaptive-tests00410nas a2200097 4500008004100000245006900041210006900110100002400179700001500203856009400218 1992 eng d00aAssessing existing item bank depth for computer adaptive testing0 aAssessing existing item bank depth for computer adaptive testing1 aBergstrom, Betty, A1 aStahl, J A uhttp://www.iacat.org/content/assessing-existing-item-bank-depth-computer-adaptive-testing00306nas a2200121 4500008004100000245002400041210002300065300001000088490000600098100001100104700001600115856005300131 1992 eng d00aCAT-ASVAB precision0 aCATASVAB precision a22-260 v11 aMoreno1 aSegall, D O uhttp://www.iacat.org/content/cat-asvab-precision00412nas a2200121 4500008004100000245006100041210006100102300001000163490000700173100001200180700001300192856008500205 1992 eng d00aComputerized mastery testing with nonequivalent testlets0 aComputerized mastery testing with nonequivalent testlets a65-760 v161 aSheehan1 aLewis, C uhttp://www.iacat.org/content/computerized-mastery-testing-nonequivalent-testlets00421nas a2200121 4500008004500000245006100045210006100106300001000167490000700177100001500184700001300199856008700212 1992 Engldsh 00aComputerized Mastery Testing With Nonequivalent Testlets0 aComputerized Mastery Testing With Nonequivalent Testlets a65-760 v161 aSheehan, K1 aLewis, C uhttp://www.iacat.org/content/computerized-mastery-testing-nonequivalent-testlets-000577nas a2200109 4500008004400000245016300044210007200207490001400279100001300293700001600306856014500322 1992 Frendh 00aLe testing adaptatif avec interprétation critérielle, une expérience de praticabilité du TAM pour l’évaluation sommative des apprentissages au Québec.0 aLe testing adaptatif avec interprétation critérielle une expérie0 v15-1 et 21 aAuger, R1 aSeguin, S P uhttp://www.iacat.org/content/le-testing-adaptatif-avec-interpr%C3%A9tation-crit%C3%A9rielle-une-exp%C3%A9rience-de-praticabilit%C3%A9-du-tam00494nas a2200109 4500008004100000245007300041210006900114260007300183100001800256700001500274856009500289 1992 eng d00aA method for severely constrained item selection in adaptive testing0 amethod for severely constrained item selection in adaptive testi aEducational Testing Service Research Report (RR-92-37): Princeton NJ1 aStocking, M L1 aSwanson, L uhttp://www.iacat.org/content/method-severely-constrained-item-selection-adaptive-testing-000547nas a2200121 4500008004100000245010100041210006900142260004600211100001800257700001500275700001600290856011900306 1991 eng d00aAutomatic item selection (AIS) methods in the ETS testing environment (Research Memorandum 91-5)0 aAutomatic item selection AIS methods in the ETS testing environm aPrinceton NJ: Educational Testing Service1 aStocking, M L1 aSwanson, L1 aPearlman, M uhttp://www.iacat.org/content/automatic-item-selection-ais-methods-ets-testing-environment-research-memorandum-91-500535nas a2200133 4500008004100000245007400041210006900115260006600184100001500250700001400265700001600279700001300295856009300308 1991 eng d00aCollected works on the legal aspects of computerized adaptive testing0 aCollected works on the legal aspects of computerized adaptive te aChicago, IL: National Council of State Boards of Nursing, Inc1 aStenson, H1 aGraves, P1 aGardiner, J1 aDally, L uhttp://www.iacat.org/content/collected-works-legal-aspects-computerized-adaptive-testing00385nas a2200133 4500008004100000245004600041210003800087300001200125490000700137100001600144700001100160700001500171856006500186 1991 eng d00aOn the reliability of testlet-based tests0 areliability of testletbased tests a237-2470 v281 aSireci, S G1 aWainer1 aThissen, D uhttp://www.iacat.org/content/reliability-testlet-based-tests00507nas a2200133 4500008004100000245009100041210006900132300001200201490000700213100001300220700001600233700001600249856010800265 1990 eng d00aAdaptive designs for Likert-type data: An approach for implementing marketing research0 aAdaptive designs for Likerttype data An approach for implementin a304-3210 v271 aSingh, J1 aHowell, R D1 aRhoads, G K uhttp://www.iacat.org/content/adaptive-designs-likert-type-data-approach-implementing-marketing-research00515nam a2200169 4500008003900000245005100039210004700090260002600137100001100163700001600174700001600190700001400206700001700220700001700237700001500254856007600269 1990 d00aComputerized adaptive testing: A primer (Eds.)0 aComputerized adaptive testing A primer Eds aHillsdale NJ: Erlbaum1 aWainer1 aDorans, N J1 aFlaugher, R1 aGreen, BF1 aMislevy, R J1 aSteinberg, L1 aThissen, D uhttp://www.iacat.org/content/computerized-adaptive-testing-primer-eds-200483nas a2200157 4500008004100000245002200041210002200063260009900085100001100184700001600195700001400211700001700225700001700242700001500259856005100274 1990 eng d00aFuture challenges0 aFuture challenges aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 233-272). Hillsdale NJ: Erlbaum.1 aWainer1 aDorans, N J1 aGreen, BF1 aMislevy, R J1 aSteinberg, L1 aThissen, D uhttp://www.iacat.org/content/future-challenges00452nas a2200121 4500008004100000245006800041210006700109260001700176100001700193700001500210700001500225856009000240 1990 eng d00aMusicCAT: An adaptive testing program to assess musical ability0 aMusicCAT An adaptive testing program to assess musical ability aSan Diego CA1 aVispoel, W P1 aCoffman, D1 aScriven, D uhttp://www.iacat.org/content/musiccat-adaptive-testing-program-assess-musical-ability00455nas a2200121 4500008004500000245007300045210006900118300001200187490000700199100001300206700001500219856009900234 1990 Engldsh 00aUsing Bayesian Decision Theory to Design a Computerized Mastery Test0 aUsing Bayesian Decision Theory to Design a Computerized Mastery  a367-3860 v141 aLewis, C1 aSheehan, K uhttp://www.iacat.org/content/using-bayesian-decision-theory-design-computerized-mastery-test-100446nas a2200121 4500008004100000245007300041210006900114300001200183490000700195100001000202700001500212856009700227 1990 eng d00aUsing Bayesian decision theory to design a computerized mastery test0 aUsing Bayesian decision theory to design a computerized mastery  a367-3860 v141 aLewis1 aSheehan, K uhttp://www.iacat.org/content/using-bayesian-decision-theory-design-computerized-mastery-test00373nas a2200121 4500008004100000245001300041210001300054260009900067100001700166700001500183700001100198856004200209 1990 eng d00aValidity0 aValidity aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 187-231). Hillsdale NJ: Erlbaum.1 aSteinberg, L1 aThissen, D1 aWainer uhttp://www.iacat.org/content/validity00544nas a2200097 4500008004100000245013000041210006900171260006800240100001600308856012200324 1990 eng d00aValidity study in multidimensional latent space and efficient computerized adaptive testing (Final Report R01-1069-11-004-91)0 aValidity study in multidimensional latent space and efficient co aKnoxville TN: University of Tennessee, Department of Psychology1 aSamejima, F uhttp://www.iacat.org/content/validity-study-multidimensional-latent-space-and-efficient-computerized-adaptive-testing00393nam a2200097 4500008004100000245005400041210005100095260005300146100001700199856007900216 1989 eng d00aAn applied study on computerized adaptive testing0 aapplied study on computerized adaptive testing aAmsterdam, The Netherlands: Swets and Zeitlinger1 aSchoonman, W uhttp://www.iacat.org/content/applied-study-computerized-adaptive-testing-001763nas a2200133 4500008004100000245005400041210005100095260005500146300000800201520129200209653003401501100001701535856007701552 1989 eng d00aAn applied study on computerized adaptive testing0 aapplied study on computerized adaptive testing aGroningen, The NetherlandsbUniversity of Groingen a1853 a(from the cover) The rapid development and falling prices of powerful personal computers, in combination with new test theories, will have a large impact on psychological testing. One of the new possibilities is computerized adaptive testing. During the test administration each item is chosen to be appropriate for the person being tested. The test becomes tailor-made, resolving some of the problems with classical paper-and-pencil tests. In this way individual differences can be measured with higher efficiency and reliability. Scores on other meaningful variables, such as response time, can be obtained easily using computers. /// In this book a study on computerized adaptive testing is described. The study took place at Dutch Railways in an applied setting and served practical goals. Topics discussed include the construction of computerized tests, the use of response time, the choice of algorithms and the implications of using a latent trait model. After running a number of simulations and calibrating the item banks, an experiment was carried out. In the experiment a pretest was administered to a sample of over 300 applicants, followed by an adaptive test. In addition, a survey concerning the attitudes of testees towards computerized testing formed part of the design.10acomputerized adaptive testing1 aSchoonman, W uhttp://www.iacat.org/content/applied-study-computerized-adaptive-testing01130nas a2200157 4500008004100000245010500041210006900146300001200215490000600227520055900233100001500792700001600807700001500823700001000838856012400848 1989 eng d00aComparisons of paper-administered, computer-administered and computerized adaptive achievement tests0 aComparisons of paperadministered computeradministered and comput a311-3260 v53 aThis research study was designed to compare student achievement scores from three different testing methods: paper-administered testing, computer-administered testing, and computerized adaptive testing. The three testing formats were developed from the California Assessment Program (CAP) item banks for grades three and six. The paper-administered and the computer-administered tests were identical in item content, format, and sequence. The computerized adaptive test was a tailored or adaptive sequence of the items in the computer-administered test. 1 aOlson, J B1 aMaynes, D D1 aSlawson, D1 aHo, K uhttp://www.iacat.org/content/comparisons-paper-administered-computer-administered-and-computerized-adaptive-achievement01449nas a2200157 4500008004100000245007900041210006900120300001000189490000600199520090200205653003401107100002001141700001701161700001701178856009601195 1989 eng d00aA real-data simulation of computerized adaptive administration of the MMPI0 arealdata simulation of computerized adaptive administration of t a18-220 v13 aA real-data simulation of computerized adaptive administration of the MMPI was conducted with data obtained from two personnel-selection samples and two clinical samples. A modification of the countdown method was tested to determine the usefulness, in terms of item administration savings, of several different test administration procedures. Substantial item administration savings were achieved for all four samples, though the clinical samples required administration of more items to achieve accurate classification and/or full-scale scores than did the personnel-selection samples. The use of normative item endorsement frequencies was found to be as effective as sample-specific frequencies for the determination of item administration order. The role of computerized adaptive testing in the future of personality assessment is discussed., (C) 1989 by the American Psychological Association10acomputerized adaptive testing1 aBen-Porath, Y S1 aSlutske, W S1 aButcher, J N uhttp://www.iacat.org/content/real-data-simulation-computerized-adaptive-administration-mmpi00357nas a2200109 4500008004100000245004800041210004700089300001000136490001000146100001500156856007600171 1989 eng d00aTesting software review: MicroCAT Version 30 aTesting software review MicroCAT Version 3 a33-380 v8 (3)1 aStone, C A uhttp://www.iacat.org/content/testing-software-review-microcat-version-300482nas a2200133 4500008004100000245007600041210006900117300001200186490000700198100001500205700001700220700001600237856009500253 1989 eng d00aTrace lines for testlets: A use of multiple-categorical-response models0 aTrace lines for testlets A use of multiplecategoricalresponse mo a247-2600 v261 aThissen, D1 aSteinberg, L1 aMooney, J A uhttp://www.iacat.org/content/trace-lines-testlets-use-multiple-categorical-response-models00524nas a2200133 4500008004100000245009300041210006900134260001500203100002000218700001600238700001700254700001700271856010200288 1988 eng d00aA comparison of two methods for the adaptive administration of the MMPI-2 content scales0 acomparison of two methods for the adaptive administration of the aAtlanta GA1 aBen-Porath, Y S1 aWaller, N G1 aSlutske, W S1 aButcher, J N uhttp://www.iacat.org/content/comparison-two-methods-adaptive-administration-mmpi-2-content-scales00442nas a2200097 4500008004100000245008900041210006900130100001800199700001300217856011400230 1988 eng d00aComputerized adaptive testing program at Miami-Dade Community College, South Campous0 aComputerized adaptive testing program at MiamiDade Community Col1 aSchinoff, R B1 aStead, L uhttp://www.iacat.org/content/computerized-adaptive-testing-program-miami-dade-community-college-south-campous00337nas a2200121 4500008004100000245003300041210003300074300001200107490000600119100001300125700001500138856006200153 1988 eng d00aComputerized mastery testing0 aComputerized mastery testing a283-2860 v21 aLewis, C1 aSheehan, K uhttp://www.iacat.org/content/computerized-mastery-testing00540nas a2200109 4500008004100000245011600041210006900157260005300226100001400279700001700293856012000310 1988 eng d00aThe development and evaluation of a microcomputerized adaptive placement testing system for college mathematics0 adevelopment and evaluation of a microcomputerized adaptive place a1986 (San Francisco CA) and 1987 (Washington DC)1 aHsu, T -C1 aShermis, M D uhttp://www.iacat.org/content/development-and-evaluation-microcomputerized-adaptive-placement-testing-system-college00489nas a2200097 4500008004100000245007700041210006900118260009100187100001600278856009700294 1988 eng d00aA procedure for scoring incomplete adaptive tests in high stakes testing0 aprocedure for scoring incomplete adaptive tests in high stakes t aUnpublished manuscript. San Diego, CA: Navy Personnel Research and Development Center1 aSegall, D O uhttp://www.iacat.org/content/procedure-scoring-incomplete-adaptive-tests-high-stakes-testing00437nas a2200121 4500008004100000245005900041210005600100260002200156100001700178700002000195700001700215856008300232 1988 eng d00aA real-data simulation of adaptive MMPI administration0 arealdata simulation of adaptive MMPI administration aSt. Petersburg FL1 aSlutske, W S1 aBen-Porath, Y S1 aButcher, J N uhttp://www.iacat.org/content/real-data-simulation-adaptive-mmpi-administration00622nas a2200145 4500008004100000245011100041210006900152260005400221100001400275700001700289700001400306700001600320700001700336856012300353 1988 eng d00aRefinement of the Computerized Adaptive Screening Test (CAST) (Final Report, Contract No MDA203 06-C-0373)0 aRefinement of the Computerized Adaptive Screening Test CAST Fina aWashington, DC: American Institutes for Research.1 aWise, L L1 aMcHenry, J J1 aChia, W J1 aSzenas, P L1 aMcBride, J R uhttp://www.iacat.org/content/refinement-computerized-adaptive-screening-test-cast-final-report-contract-no-mda203-06-c00428nas a2200097 4500008004100000245007000041210006400111260004600175100001800221856009100239 1988 eng d00aScale drift in on-line calibration (Research Report RR-88-28-ONR)0 aScale drift in online calibration Research Report RR8828ONR aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/scale-drift-line-calibration-research-report-rr-88-28-onr00427nas a2200097 4500008004100000245006900041210006400110260004900174100001800223856008800241 1988 eng d00aScale drift in on-line calibration (Tech Rep. No. ERIC ED389710)0 aScale drift in online calibration Tech Rep No ERIC ED389710 aEducational Testing Service, Princeton, N.J.1 aStocking, M L uhttp://www.iacat.org/content/scale-drift-line-calibration-tech-rep-no-eric-ed38971000480nas a2200097 4500008004100000245009200041210006900133260004600202100001800248856011600266 1988 eng d00aSome considerations in maintaining adaptive test item pools (Research Report 88-33-ONR)0 aSome considerations in maintaining adaptive test item pools Rese aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/some-considerations-maintaining-adaptive-test-item-pools-research-report-88-33-onr00485nas a2200097 4500008004100000245009400041210006900135260004900204100001800253856011600271 1988 eng d00aSome considerations in maintaining adaptive test item pools (Tech Rep. No. ERIC ED391814)0 aSome considerations in maintaining adaptive test item pools Tech aEducational Testing Service, Princeton, N.J.1 aStocking, M L uhttp://www.iacat.org/content/some-considerations-maintaining-adaptive-test-item-pools-tech-rep-no-eric-ed39181400620nas 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-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-project00425nas a2200109 4500008004100000245007100041210006900112300001200181490000700193100001800200856009700218 1987 eng d00aTwo simulated feasibility studies in computerized adaptive testing0 aTwo simulated feasibility studies in computerized adaptive testi a263-2770 v361 aStocking, M L uhttp://www.iacat.org/content/two-simulated-feasibility-studies-computerized-adaptive-testing00566nas a2200133 4500008004100000245012100041210006900162260002100231100001500252700001600267700001500283700001000298856012400308 1986 eng d00aComparison and equating of paper-administered, computer-administered, and computerized adaptive tests of achievement0 aComparison and equating of paperadministered computeradministere aSan Francisco CA1 aOlsen, J B1 aMaynes, D D1 aSlawson, D1 aHo, K uhttp://www.iacat.org/content/comparison-and-equating-paper-administered-computer-administered-and-computerized-adaptive00386nas a2200097 4500008004100000245006300041210006000104260002100164100001700185856008600202 1986 eng d00aA computer-adaptive placement test for college mathematics0 acomputeradaptive placement test for college mathematics aSan Francisco CA1 aShermis, M D uhttp://www.iacat.org/content/computer-adaptive-placement-test-college-mathematics00483nas a2200097 4500008004100000245011800041210006900159260002000228100001500248856012200263 1986 eng d00aMeasuring up in an individualized way with CAT-ASVAB: Considerations in the development of adaptive testing pools0 aMeasuring up in an individualized way with CATASVAB Consideratio aSan Franciso CA1 aSchartz, M uhttp://www.iacat.org/content/measuring-individualized-way-cat-asvab-considerations-development-adaptive-testing-pools00479nas a2200121 4500008004100000245008600041210006900127300001000196490000700206100001700213700001600230856011100246 1985 Eng d00aControlling item exposure conditional on ability in computerized adaptive testing0 aControlling item exposure conditional on ability in computerized a57-750 v231 aSympson, J B1 aHetter, R D uhttp://www.iacat.org/content/controlling-item-exposure-conditional-ability-computerized-adaptive-testing-000572nas a2200109 4500008004100000245006900041210006800110260015600178100001700334700001600351856009500367 1985 eng d00aControlling item-exposure rates in computerized adaptive testing0 aControlling itemexposure rates in computerized adaptive testing aProceedings of the 27th annual meeting of the Military Testing Association (pp. 973-977). San Diego CA: Navy Personnel Research and Development Center.1 aSympson, J B1 aHetter, R D uhttp://www.iacat.org/content/controlling-item-exposure-rates-computerized-adaptive-testing00489nas 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-tests00380nam a2200097 4500008004100000245005600041210005500097260003000152100001600182856008400198 1985 eng d00aSequential analysis: Tests and confidence intervals0 aSequential analysis Tests and confidence intervals aNew York: Springer-Verlag1 aSiegmund, D uhttp://www.iacat.org/content/sequential-analysis-tests-and-confidence-intervals00383nas a2200097 4500008004100000245006400041210006300105100001700168700001600185856008400201 1985 eng d00aValidity of adaptive testing: A summary of research results0 aValidity of adaptive testing A summary of research results1 aSympson, J B1 aMoreno, K E uhttp://www.iacat.org/content/validity-adaptive-testing-summary-research-results00510nas a2200109 4500008004100000245011600041210006900157100001600226700001600242700002100258856012100279 1985 eng d00aA validity study of the computerized adaptive testing version of the Armed Services Vocational Aptitude Battery0 avalidity study of the computerized adaptive testing version of t1 aMoreno, K E1 aSegall, D O1 aKieckhaefer, W F uhttp://www.iacat.org/content/validity-study-computerized-adaptive-testing-version-armed-services-vocational-aptitude00397nas a2200109 4500008004100000245006500041210006500106300000600171490000600177100001700183856008700200 1984 eng d00aComputerized adaptive testing in the Maryland Public Schools0 aComputerized adaptive testing in the Maryland Public Schools a10 v11 aStevenson, J uhttp://www.iacat.org/content/computerized-adaptive-testing-maryland-public-schools00540nas a2200133 4500008004100000245007700041210006900118260006500187100001200252700001400264700001500278700001500293856009800308 1984 eng d00aMicrocomputer network for computerized adaptive testing (CAT) (TR-84-33)0 aMicrocomputer network for computerized adaptive testing CAT TR84 aSan Diego CA: Navy Personnel Research and Development Center1 aQuan, B1 aPark, T A1 aSandahl, G1 aWolfe, J H uhttp://www.iacat.org/content/microcomputer-network-computerized-adaptive-testing-cat-tr-84-3300500nas a2200121 4500008004100000245009200041210006900133260001900202100001700221700001400238700001300252856011300265 1984 eng d00aPredictive validity of computerized adaptive testing in a military training environment0 aPredictive validity of computerized adaptive testing in a milita aNew Orleans LA1 aSympson, J B1 aWeiss, DJ1 aRee, M J uhttp://www.iacat.org/content/predictive-validity-computerized-adaptive-testing-military-training-environment00436nas a2200109 4500008004100000245007700041210006900118260001900187100001500206700001700221856008800238 1984 eng d00aThe selection of items for decision making with a computer adaptive test0 aselection of items for decision making with a computer adaptive  aNew Orleans LA1 aSpray, J A1 aReckase, M D uhttp://www.iacat.org/content/selection-items-decision-making-computer-adaptive-test00460nas a2200097 4500008004100000245008200041210006900123260004600192100001800238856010600256 1984 eng d00aTwo simulated feasibility studies in computerized adaptive testing (RR-84-15)0 aTwo simulated feasibility studies in computerized adaptive testi aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/two-simulated-feasibility-studies-computerized-adaptive-testing-rr-84-1500451nas a2200121 4500008004100000245007800041210006900119300001000188490000700198100001500205700001400220856009500234 1983 eng d00aAn application of computerized adaptive testing in U. S. Army recruiting.0 aapplication of computerized adaptive testing in U S Army recruit a87-890 v101 aSands, W A1 aGade, P A uhttp://www.iacat.org/content/application-computerized-adaptive-testing-u-s-army-recruiting00593nas a2200109 4500008004100000245006500041210006100106260019200167100001700359700001700376856009000393 1982 eng d00aThe computerized adaptive testing system development project0 acomputerized adaptive testing system development project aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference (pp. 342-349). Minneapolis: University of Minnesota, Department of Psychology.1 aMcBride, J R1 aSympson, J B uhttp://www.iacat.org/content/computerized-adaptive-testing-system-development-project00679nas a2200109 4500008004100000245010300041210006900144260020000213100001700413700001300430856012600443 1982 eng d00aItem Calibrations for Computerized Adaptive Testing (CAT) Experimental Item Pools Adaptive Testing0 aItem Calibrations for Computerized Adaptive Testing CAT Experime aD. J. Weiss (Ed.). Proceedings of the 1982 Computerized Adaptive Testing Conference (pp. 290-294). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSympson, J B1 aHartmann uhttp://www.iacat.org/content/item-calibrations-computerized-adaptive-testing-cat-experimental-item-pools-adaptive-testing00619nas a2200121 4500008004100000245012000041210006900161260010000230100001700330700001400347700001300361856012300374 1982 eng d00aPredictive validity of conventional and adaptive tests in an Air Force training environment (Report AFHRL-TR-81-40)0 aPredictive validity of conventional and adaptive tests in an Air aBrooks Air Force Base TX: Air Force Human Resources Laboratory, Manpower and Personnel Division1 aSympson, J B1 aWeiss, DJ1 aRee, M J uhttp://www.iacat.org/content/predictive-validity-conventional-and-adaptive-tests-air-force-training-environment-report00602nas a2200109 4500008004100000245005800041210005800099260022200157100001400379700001800393856008100411 1982 eng d00aRobustness of adaptive testing to multidimensionality0 aRobustness of adaptive testing to multidimensionality aD. J. Weiss (Ed.), Proceedings of the 1982 Item Response Theory and Computerized Adaptive Testing Conference. Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program. {PDF file, 1.1 aWeiss, DJ1 aSuhadolnik, D uhttp://www.iacat.org/content/robustness-adaptive-testing-multidimensionality00468nas a2200121 4500008004100000245004000041210004000081260011500121100001600236700001400252700001300266856006700279 1981 eng d00aAdaptive testing without a computer0 aAdaptive testing without a computer aCatalog of Selected Documents in Psychology, Nov 1981, 11, 74-75 (Ms. No. 2350). AFHRL Technical Report 80-66.1 aFriedman, D1 aSteinberg1 aRee, M J uhttp://www.iacat.org/content/adaptive-testing-without-computer00417nas 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-administration00595nas a2200109 4500008004100000245006600041210006400107260019800171100001600369700001600385856008400401 1980 eng d00aA validity study of an adaptive test of reading comprehension0 avalidity study of an adaptive test of reading comprehension aD. J. Weiss (Ed.), Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 57-67). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aHornke, L F1 aSauter, M B uhttp://www.iacat.org/content/validity-study-adaptive-test-reading-comprehension00506nas a2200121 4500008004100000245010500041210006900146300000900215490000700224100001600231700001500247856012200262 1979 eng d00aA comparison of a standard and a computerized adaptive paradigm in Bekesy fixed-frequency audiometry0 acomparison of a standard and a computerized adaptive paradigm in a1-220 v191 aHarris, J D1 aSmith, P F uhttp://www.iacat.org/content/comparison-standard-and-computerized-adaptive-paradigm-bekesy-fixed-frequency-audiometry00449nas a2200097 4500008004100000245009200041210006900133260001900202100001700221856011300238 1979 eng d00aCriterion-related validity of conventional and adaptive tests in a military environment0 aCriterionrelated validity of conventional and adaptive tests in  aMinneapolis MN1 aSympson, J B uhttp://www.iacat.org/content/criterion-related-validity-conventional-and-adaptive-tests-military-environment00512nas a2200133 4500008004100000245009100041210006900132300001200201490000700213100001600220700001600236700001600252856011000268 1978 eng d00aCombining auditory and visual stimuli in the adaptive testing of speech discrimination0 aCombining auditory and visual stimuli in the adaptive testing of a115-1220 v431 aSteele, J A1 aBinnie, C A1 aCooper, W A uhttp://www.iacat.org/content/combining-auditory-and-visual-stimuli-adaptive-testing-speech-discrimination00485nas a2200133 4500008004100000245007400041210006900115300001200184490000700196100001700203700001400220700001500234856010200249 1978 eng d00aComputer-assisted tailored testing: Examinee reactions and evaluation0 aComputerassisted tailored testing Examinee reactions and evaluat a265-2730 v381 aSchmidt, F L1 aUrry, V W1 aGugel, J F uhttp://www.iacat.org/content/computer-assisted-tailored-testing-examinee-reactions-and-evaluation00453nas a2200133 4500008004100000245006100041210006000102300001200162490000600174100002000180700001300200700001500213856009100228 1978 eng d00aComputerized adaptive testing: Principles and directions0 aComputerized adaptive testing Principles and directions a319-3290 v21 aKreitzberg, C B1 aStocking1 aSwanson, L uhttp://www.iacat.org/content/computerized-adaptive-testing-principles-and-directions-000466nas a2200109 4500008004100000245005200041210005000093260011600143300001000259100001700269856007000286 1978 eng d00aA model for testing with multidimensional items0 amodel for testing with multidimensional items aMinneapolis, MN. USAbUniversity of Minnesota, Department of Psychology, Psychometrics Methods Programc06/1978 a82-981 aSympson, J B uhttp://www.iacat.org/content/model-testing-multidimensional-items00403nas a2200133 4500008003900000245004900039210004700088300001200135490000700147100001300154700001500167700001400182856007300196 1978 d00aA stratified adaptive test of verbal ability0 astratified adaptive test of verbal ability a229-2380 v261 aShiba, S1 aNoguchi, H1 aHaebra, T uhttp://www.iacat.org/content/stratified-adaptive-test-verbal-ability00589nam a2200121 4500008004100000024005800041050003600099245007700135210006900212260007300281100001900354856009400373 1977 eng d aDissertation abstracts International, 1978, 38, 4993B aUniversity Microfims No.78-450300aA computer adaptive approach to the measurement of personality variables0 acomputer adaptive approach to the measurement of personality var aUnpublished doctoral dissertation, University of Maryland, Baltimore1 aSapinkopf, R C uhttp://www.iacat.org/content/computer-adaptive-approach-measurement-personality-variables01595nas a2200133 4500008004100000245010600041210006900147300001200216490000700228520106500235100001701300700001801317856012601335 1977 eng d00aA computer simulation study of tailored testing strategies for objective-based instructional programs0 acomputer simulation study of tailored testing strategies for obj a139-1580 v373 aOne possible way of reducing the amount of time spent testing in . objective-based instructional programs would involve the implementation of a tailored testing strategy. Our purpose was to provide some additional data on the effectiveness of various tailored testing strategies for different testing situations. The three factors of a tailored testing strategy under study with various hypothetical distributions of abilities across two learning hierarchies were test length, mastery cutting score, and starting point. Overall, our simulation results indicate that it is possible to obtain a reduction of more than 50% in testing time without any loss in decision-making accuracy, when compared to a conventional testing procedure, by implementing a tailored testing strategy. In addition, our study of starting points revealed that it was generally best to begin testing in the middle of the learning hierarchy. Finally we observed a 40% reduction in errors of classification as the number of items for testing each objective was increased from one to five.1 aSpineti, J P1 aHambleton, RK uhttp://www.iacat.org/content/computer-simulation-study-tailored-testing-strategies-objective-based-instructional-programs00572nas a2200121 4500008004100000245008700041210006900128260009400197100001700291700001400308700001500322856011300337 1977 eng d00aComputer-assisted tailored testing: Examinee reactions and evaluation (PB-276 748)0 aComputerassisted tailored testing Examinee reactions and evaluat aWashington DC: U. S. Civil Service Commission, Personnel Research and Development Center.1 aSchmidt, F L1 aUrry, V W1 aGugel, J F uhttp://www.iacat.org/content/computer-assisted-tailored-testing-examinee-reactions-and-evaluation-pb-276-74800530nas 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-testing00516nas a2200097 4500008004100000245005200041210005000093260018600143100001700329856007200346 1977 eng d00aA model for testing with multidimensional items0 amodel for testing with multidimensional items aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSympson, J B uhttp://www.iacat.org/content/model-testing-multidimensional-items-000554nas a2200097 4500008003900000245006400039210006400103260018600167100001300353856009000366 1977 d00aOperational Considerations in Implementing Tailored Testing0 aOperational Considerations in Implementing Tailored Testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSegal, H uhttp://www.iacat.org/content/operational-considerations-implementing-tailored-testing00374nas a2200109 4500008004100000245005800041210005600099300001200155490000600167100001600173856007500189 1977 En d00aA Use of the Information Function in Tailored Testing0 aUse of the Information Function in Tailored Testing a233-2470 v11 aSamejima, F uhttp://www.iacat.org/content/use-information-function-tailored-testing00554nas 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-procedure00463nas 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-procedure00546nas a2200097 4500008004100000245007400041210006900115260015200184100001600336856009600352 1976 eng d00aThe graded response model of latent trait theory and tailored testing0 agraded response model of latent trait theory and tailored testin aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 5-17). Washington DC: U.S. Government Printing Office.1 aSamejima, F uhttp://www.iacat.org/content/graded-response-model-latent-trait-theory-and-tailored-testing00515nas a2200109 4500008004100000245005200041210005200093260015600145100001700301700001400318856007300332 1976 eng d00aItem parameterization procedures for the future0 aItem parameterization procedures for the future aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 107-112.). Washington DC: U.S. Government Printing Office.1 aSchmidt, F L1 aUrry, V W uhttp://www.iacat.org/content/item-parameterization-procedures-future00435nas a2200097 4500008004100000245009000041210006900131260001400200100001600214856010700230 1975 eng d00aBehavior of the maximum likelihood estimate in a simulated tailored testing situation0 aBehavior of the maximum likelihood estimate in a simulated tailo aIowa City1 aSamejima, F uhttp://www.iacat.org/content/behavior-maximum-likelihood-estimate-simulated-tailored-testing-situation00574nas 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-testing00334nas a2200097 4500008004100000245003600041210003200077260004600109100001800155856006300173 1969 eng d00aShort tailored tests (RB-69-63)0 aShort tailored tests RB6963 aPrinceton NJ: Educational Testing Service1 aStocking, M L uhttp://www.iacat.org/content/short-tailored-tests-rb-69-6300411nas a2200109 4500008004100000245005500041210005100096260004500147100001600192700001500208856007800223 1968 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aTallahassee FL: Florida State University1 aHansen, D N1 aSchwarz, G uhttp://www.iacat.org/content/investigation-computer-based-science-testing00439nas a2200109 4500008004100000245005500041210005100096260007100147100001600218700001500234856008000249 1968 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aTallahassee: Institute of Human Learning, Florida State University1 aHansen, D N1 aSchwarz, G uhttp://www.iacat.org/content/investigation-computer-based-science-testing-000510nas 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-18800451nas 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-test00453nam a2200109 4500008004100000245008000041210006900121260003700190100001300227700001300240856009000253 1915 eng d00aA method of measuring the development of the intelligence of young children0 amethod of measuring the development of the intelligence of young aChicago: Chicago Medical Book Co1 aBinet, A1 aSimon, T uhttp://www.iacat.org/content/method-measuring-development-intelligence-young-children00396nas a2200121 4500008004400000245005300044210005300097300000900150490000700159100001300166700001300179856008200192 1908 Frendh 00aLe development de lintelligence chez les enfants0 aLe development de lintelligence chez les enfants a1-940 v141 aBinet, A1 aSimon, T uhttp://www.iacat.org/content/le-development-de-lintelligence-chez-les-enfants00464nas a2200121 4500008004400000245007500044210006900119300001200188490000700200100001300207700001800220856010400238 1905 Frendh 00aMthode nouvelle pour le diagnostic du niveau intellectuel des anormaux0 aMthode nouvelle pour le diagnostic du niveau intellectuel des an a191-2440 v111 aBinet, A1 aSimon, Th., A uhttp://www.iacat.org/content/mthode-nouvelle-pour-le-diagnostic-du-niveau-intellectuel-des-anormaux00487nas a2200133 4500008004000000245006900040210006500109260006300174100001200237700001500249700001500264700001600279856005800295 0 engd00aMicrocomputer network for computer­ized adaptive testing (CAT) 0 aMicrocomputer network for computer ized adaptive testing CAT bSan Diego: Navy Personnel Research and Development Center.1 aQuan, B1 aPark, T.A.1 aSandahl, G1 aWolfe, J.H. uhttps://apps.dtic.mil/dtic/tr/fulltext/u2/a140256.pdf