01308nas a2200133 4500008003900000245003900039210003500078300001000113490000700123520095700130100001901087700002301106856004501129 2020 d00aA Blocked-CAT Procedure for CD-CAT0 aBlockedCAT Procedure for CDCAT a49-640 v443 aThis article introduces a blocked-design procedure for cognitive diagnosis computerized adaptive testing (CD-CAT), which allows examinees to review items and change their answers during test administration. Four blocking versions of the new procedure were proposed. In addition, the impact of several factors, namely, item quality, generating model, block size, and test length, on the classification rates was investigated. Three popular item selection indices in CD-CAT were used and their efficiency compared using the new procedure. An additional study was carried out to examine the potential benefit of item review. The results showed that the new procedure is promising in that allowing item review resulted only in a small loss in attribute classification accuracy under some conditions. Moreover, using a blocked-design CD-CAT is beneficial to the extent that it alleviates the negative impact of test anxiety on examinees’ true performance.1 aKaplan, Mehmet1 ade la Torre, Jimmy uhttps://doi.org/10.1177/014662161983550000452nas a2200133 4500008004500000022001400045245007200059210006900131300000900200490000600209100002300215700002000238856006000258 2020 Engldsh a2165-659200aThree Measures of Test Adaptation Based on Optimal Test Information0 aThree Measures of Test Adaptation Based on Optimal Test Informat a1-190 v81 aKingsbury, Gage, G1 aWise, Steven, L uhttp://iacat.org/jcat/index.php/jcat/article/view/80/3700452nas a2200133 4500008004500000022001400045245007200059210006900131300000900200490000600209100002300215700002000238856006000258 2020 Engldsh a2165-659200aThree Measures of Test Adaptation Based on Optimal Test Information0 aThree Measures of Test Adaptation Based on Optimal Test Informat a1-190 v81 aKingsbury, Gage, G1 aWise, Steven, L uhttp://iacat.org/jcat/index.php/jcat/article/view/80/3701989nas a2200133 4500008003900000245006800039210006800107300001000175490000700185520158200192100001701774700001901791856004501810 2019 d00aAdaptive Testing With a Hierarchical Item Response Theory Model0 aAdaptive Testing With a Hierarchical Item Response Theory Model a51-670 v433 aThe hierarchical item response theory (H-IRT) model is very flexible and allows a general factor and subfactors within an overall structure of two or more levels. When an H-IRT model with a large number of dimensions is used for an adaptive test, the computational burden associated with interim scoring and selection of subsequent items is heavy. An alternative approach for any high-dimension adaptive test is to reduce dimensionality for interim scoring and item selection and then revert to full dimensionality for final score reporting, thereby significantly reducing the computational burden. This study compared the accuracy and efficiency of final scoring for multidimensional, local multidimensional, and unidimensional item selection and interim scoring methods, using both simulated and real item pools. The simulation study was conducted under 10 conditions (i.e., five test lengths and two H-IRT models) with a simulated sample of 10,000 students. The study with the real item pool was conducted using item parameters from an actual 45-item adaptive test with a simulated sample of 10,000 students. Results indicate that the theta estimations provided by the local multidimensional and unidimensional item selection and interim scoring methods were relatively as accurate as the theta estimation provided by the multidimensional item selection and interim scoring method, especially during the real item pool study. In addition, the multidimensional method required the longest computation time and the unidimensional method required the shortest computation time.1 aWang, Wenhao1 aKingston, Neal uhttps://doi.org/10.1177/014662161876571400579nas a2200169 4500008004500000245007100045210006900116300000900185490000600194653003100200653002000231653005100251100001800302700001400320700001500334856006000349 2019 Engldsh 00aHow Adaptive Is an Adaptive Test: Are All Adaptive Tests Adaptive?0 aHow Adaptive Is an Adaptive Test Are All Adaptive Tests Adaptive a1-140 v710acomputerized adaptive test10amultistage test10astatistical indicators of amount of adaptation1 aReckase, Mark1 aJu, Unhee1 aKim, Sewon uhttp://iacat.org/jcat/index.php/jcat/article/view/69/3400419nas a2200133 4500008004500000245005400045210005400099300001000153490000600163100001800169700001700187700001700204856006400221 2018 Engldsh 00aAdaptive Item Selection Under Matroid Constraints0 aAdaptive Item Selection Under Matroid Constraints a15-360 v61 aBengs, Daniel1 aBrefeld, Ulf1 aKröhne, Ulf uhttp://www.iacat.org/jcat/index.php/jcat/article/view/64/3200560nas a2200145 4500008003900000245008100039210006900120100002400189700002200213700001600235700001900251700002300270700002500293856009600318 2018 d00aMeasuring patient-reported outcomes adaptively: Multidimensionality matters!0 aMeasuring patientreported outcomes adaptively Multidimensionalit1 aPaap, Muirne, C. S.1 aKroeze, Karel, A.1 aGlas, C A W1 aTerwee, C., B.1 avan der Palen, Job1 aVeldkamp, Bernard, P uhttp://iacat.org/measuring-patient-reported-outcomes-adaptively-multidimensionality-matters01396nas a2200133 4500008003900000245007900039210006900118300001200187490000700199520096200206100001401168700001701182856006301199 2018 d00aA Top-Down Approach to Designing the Computerized Adaptive Multistage Test0 aTopDown Approach to Designing the Computerized Adaptive Multista a243-2630 v553 aAbstract The top-down approach to designing a multistage test is relatively understudied in the literature and underused in research and practice. This study introduced a route-based top-down design approach that directly sets design parameters at the test level and utilizes the advanced automated test assembly algorithm seeking global optimality. The design process in this approach consists of five sub-processes: (1) route mapping, (2) setting objectives, (3) setting constraints, (4) routing error control, and (5) test assembly. Results from a simulation study confirmed that the assembly, measurement and routing results of the top-down design eclipsed those of the bottom-up design. Additionally, the top-down design approach provided unique insights into design decisions that could be used to refine the test. Regardless of these advantages, it is recommended applying both top-down and bottom-up approaches in a complementary manner in practice.1 aLuo, Xiao1 aKim, Doyoung uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1217401179nas a2200157 4500008003900000245008400039210006900123300001200192490000700204520068700211100002000898700001600918700001800934700002200952856004700974 2017 d00aThe Development of MST Test Information for the Prediction of Test Performances0 aDevelopment of MST Test Information for the Prediction of Test P a570-5860 v773 aThe current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the validity of the proposed method in both measurement precision and classification accuracy. The results indicate that the MST test information effectively predicted the performance of MST. In addition, the results of the current study highlighted the relationship among the test construction, MST design factors, and MST performance.1 aPark, Ryoungsun1 aKim, Jiseon1 aChung, Hyewon1 aDodd, Barbara, G. uhttp://dx.doi.org/10.1177/001316441666296001541nas a2200157 4500008003900000022001400039245009700053210006900150300001400219490000700233520104800240100001901288700001601307700001901323856004101342 2017 d a1745-398400aDual-Objective Item Selection Criteria in Cognitive Diagnostic Computerized Adaptive Testing0 aDualObjective Item Selection Criteria in Cognitive Diagnostic Co a165–1830 v543 aThe development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery status and overall test performance. The new procedure is based on the Jensen-Shannon (JS) divergence, a symmetrized version of the Kullback-Leibler divergence. We show that the JS divergence resolves the noncomparability problem of the dual information index and has close relationships with Shannon entropy, mutual information, and Fisher information. The performance of the JS divergence is evaluated in simulation studies in comparison with the methods available in the literature. Results suggest that the JS divergence achieves parallel or more precise recovery of latent trait variables compared to the existing methods and maintains practical advantages in computation and item pool usage.1 aKang, Hyeon-Ah1 aZhang, Susu1 aChang, Hua-Hua uhttp://dx.doi.org/10.1111/jedm.1213901714nas a2200157 4500008004100000245007500041210006900116260005500185520116600240653000801406653002401414653001201438100002001450700001501470856007101485 2017 eng d00aFrom Blueprints to Systems: An Integrated Approach to Adaptive Testing0 aFrom Blueprints to Systems An Integrated Approach to Adaptive Te aNiigata, JapanbNiigata Seiryo Universityc08/20173 a
For years, test blueprints have told test developers how many items and what types of items will be included in a test. Adaptive testing adopted this approach from paper testing, and it is reasonably useful. Unfortunately, 'how many items and what types of items' are not all the elements one should consider when choosing items for an adaptive test. To fill in gaps, practitioners have developed tools to allow an adaptive test to behave appropriately (i.e. examining exposure control, content balancing, item drift procedures, etc.). Each of these tools involves the use of a separate process external to the primary item selection process.
The use of these subsidiary processes makes item selection less optimal and makes it difficult to prioritize aspects of selection. This discussion describes systems-based adaptive testing. This approach uses metadata concerning items, test takers and test elements to select items. These elements are weighted by the stakeholders to shape an expanded blueprint designed for adaptive testing.
10aCAT10aintegrated approach10aKeynote1 aKingsbury, Gage1 aZara, Tony uhttps://drive.google.com/open?id=1CBaAfH4ES7XivmvrMjPeKyFCsFZOpQMJ00592nas a2200169 4500008003900000022001400039245011200053210006900165300001600234490000700250100002400257700002200281700002500303700002300328700002500351856004600376 2017 d a1573-264900aItem usage in a multidimensional computerized adaptive test (MCAT) measuring health-related quality of life0 aItem usage in a multidimensional computerized adaptive test MCAT a2909–29180 v261 aPaap, Muirne, C. S.1 aKroeze, Karel, A.1 aTerwee, Caroline, B.1 avan der Palen, Job1 aVeldkamp, Bernard, P uhttps://doi.org/10.1007/s11136-017-1624-303876nas 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 aThe 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.
10amst10aMultidisciplined10aproficiency1 aStraat, Hendrik1 aGroen, Maaike1 aZijlstra, Wobbe1 aKeizer-Mittelhaëuser, Marie-Anne1 aLamoré, Michel uhttps://drive.google.com/open?id=1C5ys178p_Wl9eemQuIsI56IxDTck2z8P02579nas a2200157 4500008004100000245011700041210006900158260005500227520193000282653001102212653001902223653002702242100001802269700001902287856011502306 2017 eng d00aA New Cognitive Diagnostic Computerized Adaptive Testing for Simultaneously Diagnosing Skills and Misconceptions0 aNew Cognitive Diagnostic Computerized Adaptive Testing for Simul aNiigata, JapanbNiigata Seiryo Universityc08/20173 aIn education diagnoses, diagnosing misconceptions is important as well as diagnosing skills. However, traditional cognitive diagnostic computerized adaptive testing (CD-CAT) is usually developed to diagnose skills. This study aims to propose a new CD-CAT that can simultaneously diagnose skills and misconceptions. The proposed CD-CAT is based on a recently published new CDM, called the simultaneously identifying skills and misconceptions (SISM) model (Kuo, Chen, & de la Torre, in press). A new item selection algorithm is also proposed in the proposed CD-CAT for achieving high adaptive testing performance. In simulation studies, we compare our new item selection algorithm with three existing item selection methods, including the Kullback–Leibler (KL) and posterior-weighted KL (PWKL) proposed by Cheng (2009) and the modified PWKL (MPWKL) proposed by Kaplan, de la Torre, and Barrada (2015). The results show that our proposed CD-CAT can efficiently diagnose skills and misconceptions; the accuracy of our new item selection algorithm is close to the MPWKL but less computational burden; and our new item selection algorithm outperforms the KL and PWKL methods on diagnosing skills and misconceptions.
References
Cheng, Y. (2009). When cognitive diagnosis meets computerized adaptive testing: CD-CAT. Psychometrika, 74(4), 619–632. doi: 10.1007/s11336-009-9123-2
Kaplan, M., de la Torre, J., & Barrada, J. R. (2015). New item selection methods for cognitive diagnosis computerized adaptive testing. Applied Psychological Measurement, 39(3), 167–188. doi:10.1177/0146621614554650
Kuo, B.-C., Chen, C.-H., & de la Torre, J. (in press). A cognitive diagnosis model for identifying coexisting skills and misconceptions. Applied Psychological Measurement.
10aCD-CAT10aMisconceptions10aSimultaneous diagnosis1 aKuo, Bor-Chen1 aChen, Chun-Hua uhttp://iacat.org/new-cognitive-diagnostic-computerized-adaptive-testing-simultaneously-diagnosing-skills-and-001828nas a2200169 4500008003900000020001400039245009100053210006900144260001500213300001400228490000700242520131200249100001401561700001701575700002101592856004501613 2017 d a0146-621600aProjection-Based Stopping Rules for Computerized Adaptive Testing in Licensure Testing0 aProjectionBased Stopping Rules for Computerized Adaptive Testing c2018/06/01 a275 - 2900 v423 aThe confidence interval (CI) stopping rule is commonly used in licensure settings to make classification decisions with fewer items in computerized adaptive testing (CAT). However, it tends to be less efficient in the near-cut regions of the ? scale, as the CI often fails to be narrow enough for an early termination decision prior to reaching the maximum test length. To solve this problem, this study proposed the projection-based stopping rules that base the termination decisions on the algorithmically projected range of the final ? estimate at the hypothetical completion of the CAT. A simulation study and an empirical study were conducted to show the advantages of the projection-based rules over the CI rule, in which the projection-based rules reduced the test length without jeopardizing critical psychometric qualities of the test, such as the ? and classification precision. Operationally, these rules do not require additional regularization parameters, because the projection is simply a hypothetical extension of the current test within the existing CAT environment. Because these new rules are specifically designed to address the decreased efficiency in the near-cut regions as opposed to for the entire scale, the authors recommend using them in conjunction with the CI rule in practice.1 aLuo, Xiao1 aKim, Doyoung1 aDickison, Philip uhttps://doi.org/10.1177/014662161772679001269nas a2200301 4500008003900000022001400039245021000053210006900263260000800332300001600340490000700356520033300363100001600696700001300712700001400725700001900739700001600758700001500774700001500789700001500804700002000819700001400839700001400853700001800867700001200885700002400897856004600921 2017 d a1573-264900aThe validation of a computer-adaptive test (CAT) for assessing health-related quality of life in children and adolescents in a clinical sample: study design, methods and first results of the Kids-CAT study0 avalidation of a computeradaptive test CAT for assessing healthre cMay a1105–11170 v263 aRecently, we developed a computer-adaptive test (CAT) for assessing health-related quality of life (HRQoL) in children and adolescents: the Kids-CAT. It measures five generic HRQoL dimensions. The aims of this article were (1) to present the study design and (2) to investigate its psychometric properties in a clinical setting.1 aBarthel, D.1 aOtto, C.1 aNolte, S.1 aMeyrose, A.-K.1 aFischer, F.1 aDevine, J.1 aWalter, O.1 aMierke, A.1 aFischer, K., I.1 aThyen, U.1 aKlein, M.1 aAnkermann, T.1 aRose, M1 aRavens-Sieberer, U. uhttps://doi.org/10.1007/s11136-016-1437-900723nas a2200205 4500008004500000022001500045245013200060210006900192300000900261490000600270653002100276653003000297653003000327653001600357653002300373100002100396700002000417700002000437856006000457 2016 Engldsh a2165-6592 00aEffect of Imprecise Parameter Estimation on Ability Estimation in a Multistage Test in an Automatic Item Generation Context 0 aEffect of Imprecise Parameter Estimation on Ability Estimation i a1-180 v410aAdaptive Testing10aautomatic item generation10aerrors in item parameters10aitem clones10amultistage testing1 aColvin, Kimberly1 aKeller, Lisa, A1 aRobin, Frederic uhttp://iacat.org/jcat/index.php/jcat/article/view/59/2701299nas a2200145 4500008003900000022001400039245009100053210006900144300001300213490000700226520083800233100002101071700002001092856004101112 2016 d a1745-398400aModeling Student Test-Taking Motivation in the Context of an Adaptive Achievement Test0 aModeling Student TestTaking Motivation in the Context of an Adap a86–1050 v533 aThis study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior. Test taker behavior was found to be inconsistent with these models, with the exception of the effort-moderated model. Effort-moderated scoring was found to both yield scores that were more accurate than those found under traditional scoring, and exhibit improved person fit statistics. In addition, an effort-guided adaptive test was proposed and shown by a simulation study to alleviate item difficulty mistargeting caused by unmotivated test taking.1 aWise, Steven, L.1 aKingsbury, Gage uhttp://dx.doi.org/10.1111/jedm.1210201438nas a2200133 4500008003900000245013200039210006900171300001200240490000700252520095400259100001901213700001901232856005301251 2016 d00aParameter Drift Detection in Multidimensional Computerized Adaptive Testing Based on Informational Distance/Divergence Measures0 aParameter Drift Detection in Multidimensional Computerized Adapt a534-5500 v403 aAn informational distance/divergence-based approach is proposed to detect the presence of parameter drift in multidimensional computerized adaptive testing (MCAT). The study presents significance testing procedures for identifying changes in multidimensional item response functions (MIRFs) over time based on informational distance/divergence measures that capture the discrepancy between two probability functions. To approximate the MIRFs from the observed response data, the k-nearest neighbors algorithm is used with the random search method. A simulation study suggests that the distance/divergence-based drift measures perform effectively in identifying the instances of parameter drift in MCAT. They showed moderate power with small samples of 500 examinees and excellent power when the sample size was as large as 1,000. The proposed drift measures also adequately controlled for Type I error at the nominal level under the null hypothesis.1 aKang, Hyeon-Ah1 aChang, Hua-Hua uhttp://apm.sagepub.com/content/40/7/534.abstract01723nas a2200145 4500008003900000245015500039210006900194300001000263490000700273520118100280100001701461700002701478700002001505856005201525 2016 d00aStochastic Curtailment of Questionnaires for Three-Level Classification: Shortening the CES-D for Assessing Low, Moderate, and High Risk of Depression0 aStochastic Curtailment of Questionnaires for ThreeLevel Classifi a22-360 v403 aIn clinical assessment, efficient screeners are needed to ensure low respondent burden. In this article, Stochastic Curtailment (SC), a method for efficient computerized testing for classification into two classes for observable outcomes, was extended to three classes. In a post hoc simulation study using the item scores on the Center for Epidemiologic Studies–Depression Scale (CES-D) of a large sample, three versions of SC, SC via Empirical Proportions (SC-EP), SC via Simple Ordinal Regression (SC-SOR), and SC via Multiple Ordinal Regression (SC-MOR) were compared at both respondent burden and classification accuracy. All methods were applied under the regular item order of the CES-D and under an ordering that was optimal in terms of the predictive power of the items. Under the regular item ordering, the three methods were equally accurate, but SC-SOR and SC-MOR needed less items. Under the optimal ordering, additional gains in efficiency were found, but SC-MOR suffered from capitalization on chance substantially. It was concluded that SC-SOR is an efficient and accurate method for clinical screening. Strengths and weaknesses of the methods are discussed.1 aSmits, Niels1 aFinkelman, Matthew, D.1 aKelderman, Henk uhttp://apm.sagepub.com/content/40/1/22.abstract01559nas 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.1206401505nas a2200157 4500008003900000022001400039245008900053210006900142300001200211490000700223520101800230100001701248700001501265700002601280856004101306 2015 d a1745-398400aA Comparison of IRT Proficiency Estimation Methods Under Adaptive Multistage Testing0 aComparison of IRT Proficiency Estimation Methods Under Adaptive a70–790 v523 aThis inquiry is an investigation of item response theory (IRT) proficiency estimators’ accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two assembly conditions in each module, such as difficulty level and module length. For each panel, we investigated the accuracy of examinees’ proficiency levels derived from seven IRT proficiency estimators. The choice of Bayesian (prior) versus non-Bayesian (no prior) estimators was of more practical significance than the choice of number-correct versus item-pattern scoring estimators. The Bayesian estimators were slightly more efficient than the non-Bayesian estimators, resulting in smaller overall error. Possible score changes caused by the use of different proficiency estimators would be nonnegligible, particularly for low- and high-performing examinees.1 aKim, Sooyeon1 aMoses, Tim1 aYoo, Hanwook, (Henry) uhttp://dx.doi.org/10.1111/jedm.1206301071nas a2200133 4500008003900000245006600039210006600105490000700171520062900178100001400807700001900821700001700840856008000857 2015 d00aEvaluating Content Alignment in Computerized Adaptive Testing0 aEvaluating Content Alignment in Computerized Adaptive Testing0 v343 aThe alignment between a test and the content domain it measures represents key evidence for the validation of test score inferences. Although procedures have been developed for evaluating the content alignment of linear tests, these procedures are not readily applicable to computerized adaptive tests (CATs), which require large item pools and do not use fixed test forms. This article describes the decisions made in the development of CATs that influence and might threaten content alignment. It outlines a process for evaluating alignment that is sensitive to these threats and gives an empirical example of the process.1 aWise, S L1 aKingsbury, G G1 aWebb, N., L. uhttp://iacat.org/evaluating-content-alignment-computerized-adaptive-testing01415nas a2200169 4500008003900000245007000039210006900109300001400178490000700192520091000199100001901109700002101128700001601149700001201165700001401177856005401191 2015 d00aInvestigation of Response Changes in the GRE Revised General Test0 aInvestigation of Response Changes in the GRE Revised General Tes a1002-10200 v753 aResearch on examinees’ response changes on multiple-choice tests over the past 80 years has yielded some consistent findings, including that most examinees make score gains by changing answers. This study expands the research on response changes by focusing on a high-stakes admissions test—the Verbal Reasoning and Quantitative Reasoning measures of the GRE revised General Test. We analyzed data from 8,538 examinees for Quantitative and 9,140 for Verbal sections who took the GRE revised General Test in 12 countries. The analyses yielded findings consistent with prior research. In addition, as examinees’ ability increases, the benefit of response changing increases. The study yielded significant implications for both test agencies and test takers. Computer adaptive tests often do not allow the test takers to review and revise. Findings from this study confirm the benefit of such features.1 aLiu, Ou, Lydia1 aBridgeman, Brent1 aGu, Lixiong1 aXu, Jun1 aKong, Nan uhttp://epm.sagepub.com/content/75/6/1002.abstract01510nas a2200145 4500008003900000245008500039210006900124300001200193490000700205520103200212100001901244700002301263700002501286856005301311 2015 d00aNew Item Selection Methods for Cognitive Diagnosis Computerized Adaptive Testing0 aNew Item Selection Methods for Cognitive Diagnosis Computerized a167-1880 v393 aThis article introduces two new item selection methods, the modified posterior-weighted Kullback–Leibler index (MPWKL) and the generalized deterministic inputs, noisy “and” gate (G-DINA) model discrimination index (GDI), that can be used in cognitive diagnosis computerized adaptive testing. The efficiency of the new methods is compared with the posterior-weighted Kullback–Leibler (PWKL) item selection index using a simulation study in the context of the G-DINA model. The impact of item quality, generating models, and test termination rules on attribute classification accuracy or test length is also investigated. The results of the study show that the MPWKL and GDI perform very similarly, and have higher correct attribute classification rates or shorter mean test lengths compared with the PWKL. In addition, the GDI has the shortest implementation time among the three indices. The proportion of item usage with respect to the required attributes across the different conditions is also tracked and discussed.1 aKaplan, Mehmet1 ade la Torre, Jimmy1 aBarrada, Juan Ramón uhttp://apm.sagepub.com/content/39/3/167.abstract00532nas a2200145 4500008004500000245013100045210006900176300001000245490000600255100001900261700001100280700001600291700001500307856006400322 2014 Engldsh 00aCognitive Diagnostic Models and Computerized Adaptive Testing: Two New Item-Selection Methods That Incorporate Response Times0 aCognitive Diagnostic Models and Computerized Adaptive Testing Tw a59-760 v21 aFinkelman, M D1 aKim, W1 aWeissman, A1 aCook, R.J. uhttp://www.iacat.org/jcat/index.php/jcat/article/view/43/2101617nas 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 aWith 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.1205201425nas a2200157 4500008003900000245009200039210006900131300001200200490000700212520092000219100002001139700001601159700001801175700002101193856005301214 2014 d00aEnhancing Pool Utilization in Constructing the Multistage Test Using Mixed-Format Tests0 aEnhancing Pool Utilization in Constructing the Multistage Test U a268-2800 v383 aThis study investigated a new pool utilization method of constructing multistage tests (MST) using the mixed-format test based on the generalized partial credit model (GPCM). MST simulations of a classification test were performed to evaluate the MST design. A linear programming (LP) model was applied to perform MST reassemblies based on the initial MST construction. Three subsequent MST reassemblies were performed. For each reassembly, three test unit replacement ratios (TRRs; 0.22, 0.44, and 0.66) were investigated. The conditions of the three passing rates (30%, 50%, and 70%) were also considered in the classification testing. The results demonstrated that various MST reassembly conditions increased the overall pool utilization rates, while maintaining the desired MST construction. All MST testing conditions performed equally well in terms of the precision of the classification decision.
1 aPark, Ryoungsun1 aKim, Jiseon1 aChung, Hyewon1 aDodd, Barbara, G uhttp://apm.sagepub.com/content/38/4/268.abstract01676nas a2200145 4500008003900000245012600039210006900165300001200234490000700246520115400253100002601407700002201433700002201455856005301477 2014 d00aStratified Item Selection and Exposure Control in Unidimensional Adaptive Testing in the Presence of Two-Dimensional Data0 aStratified Item Selection and Exposure Control in Unidimensional a563-5760 v383 aIt is not uncommon to use unidimensional item response theory models to estimate ability in multidimensional data with computerized adaptive testing (CAT). The current Monte Carlo study investigated the penalty of this model misspecification in CAT implementations using different item selection methods and exposure control strategies. Three item selection methods—maximum information (MAXI), a-stratification (STRA), and a-stratification with b-blocking (STRB) with and without Sympson–Hetter (SH) exposure control strategy—were investigated. Calibrating multidimensional items as unidimensional items resulted in inaccurate item parameter estimates. Therefore, MAXI performed better than STRA and STRB in estimating the ability parameters. However, all three methods had relatively large standard errors. SH exposure control had no impact on the number of overexposed items. Existing unidimensional CAT implementations might consider using MAXI only if recalibration as multidimensional model is too expensive. Otherwise, building a CAT pool by calibrating multidimensional data as unidimensional is not recommended.
1 aKalinowski, Kevin, E.1 aNatesan, Prathiba1 aHenson, Robin, K. uhttp://apm.sagepub.com/content/38/7/563.abstract00529nas a2200145 4500008004100000245009500041210006900136300001000205490000600215100001900221700001100240700001000251700001300261856010900274 2013 en d00aItem Ordering in Stochastically Curtailed Health Questionnaires With an Observable Outcome0 aItem Ordering in Stochastically Curtailed Health Questionnaires a38-660 v11 aFinkelman, M D1 aKim, W1 aHe, Y1 aLai, A M uhttp://iacat.org/content/item-ordering-stochastically-curtailed-health-questionnaires-observable-outcome00512nas a2200121 4500008004100000245009900041210006900140260002300209100001200232700001500244700001500259856011600274 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://iacat.org/content/reporting-differentiated-literacy-results-pisa-using-multidimensional-adaptive-testing01659nas a2200097 4500008004500000245007600045210006900121520126100190100001601451856009401467 2012 Engldsh 00aComputerized Adaptive Testing for Student Selection to Higher Education0 aComputerized Adaptive Testing for Student Selection to Higher Ed3 aThe purpose of the present study is to discuss applicability of computerized adaptive testing format as an alternative for current student selection examinations to higher education in Turkey. In the study, first problems associated with current student selection system are given. These problems exerts pressure on students that results in test anxiety, produce measurement experiences that can be criticized, and lessen credibility of student selection system. Next, computerized adaptive test are introduced and advantages they provide are presented. Then results of a study that used two research designs (simulation and live testing) were presented. Results revealed that (i) computerized adaptive format provided a reduction up to 80% in the number of items given to students compared to paper and pencil format of student selection examination, (ii) ability estimations have high reliabilities. Correlations between ability estimations obtained from simulation and traditional format were higher than 0.80. At the end of the study solutions provided by computerized adaptive testing implementation to the current problems were discussed. Also some issues for application of CAT format for student selection examinations in Turkey are given.
1 aKalender, I uhttp://iacat.org/content/computerized-adaptive-testing-student-selection-higher-education00541nas a2200181 4500008004500000245006300045210006300108300001400171490000700185100002300192700002000215700002200235700001700257700001600274700001800290700002100308856003000329 2012 Engldsh 00aDevelopment of a computerized adaptive test for depression0 aDevelopment of a computerized adaptive test for depression a1105-11120 v691 aGibbons, Robert, D1 aWeiss, David, J1 aPilkonis, Paul, A1 aFrank, Ellen1 aMoore, Tara1 aKim, Jong Bae1 aKupfer, David, J uWWW.ARCHGENPSYCHIATRY.COM01556nas a2200169 4500008003900000245012400039210006900163300001000232490000700242520099400249100001901243700001801262700001801280700001601298700002001314856005201334 2012 d00aAn Empirical Evaluation of the Slip Correction in the Four Parameter Logistic Models With Computerized Adaptive Testing0 aEmpirical Evaluation of the Slip Correction in the Four Paramete a75-870 v363 aIn a selected response test, aberrant responses such as careless errors and lucky guesses might cause error in ability estimation because these responses do not actually reflect the knowledge that examinees possess. In a computerized adaptive test (CAT), these aberrant responses could further cause serious estimation error due to dynamic item administration. To enhance the robust performance of CAT against aberrant responses, Barton and Lord proposed the four-parameter logistic (4PL) item response theory (IRT) model. However, most studies relevant to the 4PL IRT model were conducted based on simulation experiments. This study attempts to investigate the performance of the 4PL IRT model as a slip-correction mechanism with an empirical experiment. The results showed that the 4PL IRT model could not only reduce the problematic underestimation of the examinees’ ability introduced by careless mistakes in practical situations but also improve measurement efficiency.
1 aYen, Yung-Chin1 aHo, Rong-Guey1 aLaio, Wen-Wei1 aChen, Li-Ju1 aKuo, Ching-Chin uhttp://apm.sagepub.com/content/36/2/75.abstract01421nas a2200157 4500008003900000245008000039210006900119300001200188490000700200520092800207100001601135700001801151700002101169700002001190856005301210 2012 d00aPanel Design Variations in the Multistage Test Using the Mixed-Format Tests0 aPanel Design Variations in the Multistage Test Using the MixedFo a574-5880 v723 aThis study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized adaptive test (CAT) conditions provided baseline comparisons. Three passing rate conditions were also included. The various MST conditions using mixed-format tests were constructed properly and performed well. When the levels of TIFs at the first stage were higher, the simulations produced a greater number of correct classifications. CAT with the randomesque-10 procedure yielded comparable results to the MST with increased levels of TIFs. Finally, all MST conditions achieved better test security results compared with CAT’s maximum information conditions.
1 aKim, Jiseon1 aChung, Hyewon1 aDodd, Barbara, G1 aPark, Ryoungsun uhttp://epm.sagepub.com/content/72/4/574.abstract01629nas a2200145 4500008004100000245005200041210005000093260001200143520119300155653000801348653001601356653002001372100002301392856006801415 2011 eng d00aContinuous Testing (an avenue for CAT research)0 aContinuous Testing an avenue for CAT research c10/20113 aPublishing an Adaptive Test
Problems with Publishing
Research Questions
Development of adaptive tests used in K-12 settings requires the creation of stable measurement scales to measure the growth of individual students from one grade to the next, and to measure change in groups from one year to the next. Accountability systems
like No Child Left Behind require stable measurement scales so that accountability has meaning across time. This study examined the stability of the measurement scales used with the Measures of Academic Progress. Difficulty estimates for test questions from the reading and mathematics scales were examined over a period ranging from 7 to 22 years. Results showed high correlations between item difficulty estimates from the time at which they where originally calibrated and the current calibration. The average drift in item difficulty estimates was less than .01 standard deviations. The average impact of change in item difficulty estimates was less than the smallest reported difference on the score scale for two actual tests. The findings of the study indicate that an IRT scale can be stable enough to allow consistent measurement of student achievement.
The purpose of the present study is to compare ability estimations obtained from computerized adaptive testing (CAT) procedure with the paper and pencil test administration results of Student Selection Examination (SSE) science subtest considering different ability estimation methods and test termination rules. There are two phases in the present study. In the first phase, a post-hoc simulation was conducted to find out relationships between examinee ability levels estimated by CAT and paper and pencil test versions of the SSE. Maximum Likelihood Estimation and Expected A Posteriori were used as ability estimation method. Test termination rules were standard error threshold and fixed number of items. Second phase was actualized by implementing a CAT administration to a group of examinees to investigate performance of CAT administration in an environment other than simulated administration. Findings of post-hoc simulations indicated CAT could be implemented by using Expected A Posteriori estimation method with standard error threshold value of 0.30 or higher for SSE. Correlation between ability estimates obtained by CAT and real SSE was found to be 0.95. Mean of number of items given to examinees by CAT is 18.4. Correlation between live CAT and real SSE ability estimations was 0.74. Number of items used for CAT administration is approximately 50% of the items in paper and pencil SSE science subtest. Results indicated that CAT for SSE science subtest provided ability estimations with higher reliability with fewer items compared to paper and pencil format.
1 aKalender, I uhttp://iacat.org/content/effects-different-computerized-adaptive-testing-strategies-recovery-ability00534nas a2200121 4500008004100000245011800041210006900159653000800228653002400236653001100260100002000271856012100291 2011 eng d00aHigh-throughput Health Status Measurement using CAT in the Era of Personal Genomics: Opportunities and Challenges0 aHighthroughput Health Status Measurement using CAT in the Era of10aCAT10ahealth applications10aPROMIS1 aKrishnan, Eswar uhttp://iacat.org/content/high-throughput-health-status-measurement-using-cat-era-personal-genomics-opportunities-and00764nas a2200157 4500008004500000245008000045210006900125490000700194520022700201100001500428700001600443700001700459700001600476700001500492856009900507 2011 Engldsh 00aA new adaptive testing algorithm for shortening health literacy assessments0 anew adaptive testing algorithm for shortening health literacy as0 v113 a
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3178473/?tool=pmcentrez1 aKandula, S1 aAncker, J S1 aKaufman, D R1 aCurrie, L M1 aQing, Z -T uhttp://iacat.org/content/new-adaptive-testing-algorithm-shortening-health-literacy-assessments00372nas a2200109 4500008004100000245004800041210004800089300001200137100001600149700002700165856007000192 2010 eng d00aDetecting Person Misfit in Adaptive Testing0 aDetecting Person Misfit in Adaptive Testing a315-3291 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/detecting-person-misfit-adaptive-testing02219nas a2200289 4500008004100000020004600041245010800087210006900195250001500264300001200279490000700291520131000298100001801608700001701626700001801643700001401661700001401675700001801689700001401707700001701721700001501738700001301753700001401766700001601780700001301796856012001809 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://iacat.org/content/development-computerized-adaptive-testing-cat-eortc-qlq-c30-physical-functioning-dimension01507nas a2200217 4500008004100000245008100041210006900122300001200191490000700203520078900210653001100999653003401010653002201044653003501066653002101101653002101122100001901143700001401162700001601176856009701192 2010 eng d00aItem Selection and Hypothesis Testing for the Adaptive Measurement of Change0 aItem Selection and Hypothesis Testing for the Adaptive Measureme a238-2540 v343 a
Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC framework. This study introduced a new item selection criterion and two new test statistics for detecting change with AMC that were specifically designed for the paradigm of hypothesis testing. In two simulation sets, the new methods for detecting significant change improved on existing procedures by demonstrating better adherence to Type I error rates and substantially better power for detecting relatively small change.
10achange10acomputerized adaptive testing10aindividual change10aKullback–Leibler information10alikelihood ratio10ameasuring change1 aFinkelman, M D1 aWeiss, DJ1 aKim-Kang, G uhttp://iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change-001915nas a2200109 4500008004100000245010800041210006900149260009700218520135200315100001901667856011901686 2009 eng d00aAdaptive item calibration: A process for estimating item parameters within a computerized adaptive test0 aAdaptive item calibration A process for estimating item paramete aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aThe characteristics of an adaptive test change the characteristics of the field testing that is necessary to add items to an existing measurement scale. The process used to add field-test items to the adaptive test might lead to scale drift or disrupt the test by administering items of inappropriate difficulty. The current study makes use of the transitivity of examinee and item in item response theory to describe a process for adaptive item calibration. In this process an item is successively administered to examinees whose ability levels match the performance of a given field-test item. By treating the item as if it were taking an adaptive test, examinees can be selected who provide the most information about the item at its momentary difficulty level. This should provide a more efficient procedure for estimating item parameters. The process is described within the context of the one-parameter logistic IRT model. The process is then simulated to identify whether it can be more accurate and efficient than random presentation of field-test items to examinees. Results indicated that adaptive item calibration might provide a viable approach to item calibration within the context of an adaptive test. It might be most useful for expanding item pools in settings with small sample sizes or needs for large numbers of items.1 aKingsbury, G G uhttp://iacat.org/content/adaptive-item-calibration-process-estimating-item-parameters-within-computerized-adaptive00586nas a2200121 4500008004100000245010000041210006900141260009700210100001600307700001500323700001500338856011100353 2009 eng d00aAdequacy of an item pool measuring proficiency in English language to implement a CAT procedure0 aAdequacy of an item pool measuring proficiency in English langua aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aKarino, C A1 aCosta, D R1 aLaros, J A uhttp://iacat.org/content/adequacy-item-pool-measuring-proficiency-english-language-implement-cat-procedure00591nas a2200133 4500008004100000245008600041210006900127260009700196100001500293700001600308700001700324700001700341856009900358 2009 eng d00aA comparison of three methods of item selection for computerized adaptive testing0 acomparison of three methods of item selection for computerized a aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aCosta, D R1 aKarino, C A1 aMoura, F A S1 aAndrade, D F uhttp://iacat.org/content/comparison-three-methods-item-selection-computerized-adaptive-testing01889nas a2200157 4500008004100000245007800041210006900119260009700188520126000285100001801545700001801563700002001581700001701601700001601618856009701634 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://iacat.org/content/criterion-related-validity-innovative-cat-based-personality-measure01659nas a2200145 4500008004100000245004900041210004800090260009700138520115900235100001301394700001101407700001401418700001101432856007001443 2009 eng d00aDeveloping item variants: An empirical study0 aDeveloping item variants An empirical study aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.3 aLarge-scale standardized test have been widely used for educational and licensure testing. In computerized adaptive testing (CAT), one of the practical concerns for maintaining large-scale assessments is to ensure adequate numbers of high-quality items that are required for item pool functioning. Developing items at specific difficulty levels and for certain areas of test plans is a wellknown challenge. The purpose of this study was to investigate strategies for varying items that can effectively generate items at targeted difficulty levels and specific test plan areas. Each variant item generation model was developed by decomposing selected source items possessing ideal measurement properties and targeting the desirable content domains. 341 variant items were generated from 72 source items. Data were collected from six pretest periods. Items were calibrated using the Rasch model. Initial results indicate that variant items showed desirable measurement properties. Additionally, compared to an average of approximately 60% of the items passing pretest criteria, an average of 84% of the variant items passed the pretest criteria. 1 aWendt, A1 aKao, S1 aGorham, J1 aWoo, A uhttp://iacat.org/content/developing-item-variants-empirical-study02745nas a2200409 4500008004100000020004600041245009400087210006900181250001500250260000800265300001200273490000700285520144500292653001501737653002001752653003101772653003001803653002001833653001901853653002601872653001101898653001101909653000901920653001601929653002601945653003701971653003002008653004402038653001802082653002002100653002802120100002002148700002302168700001602191700001702207856011102224 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://iacat.org/content/development-and-preliminary-testing-computerized-adaptive-assessment-chronic-pain02877nas a2200493 4500008004100000020004100041245014100082210006900223250001500292260000800307300001100315490000700326520125100333653003001584653001001614653000901624653004601633653003301679653001101712653003101723653001101754653000901765653003301774653001601807653002401823653004601847653005501893653005501948653004602003653001902049653003102068653001402099100001602113700001502129700001302144700001402157700001502171700001702186700001502203700001702218700001502235700001302250856012002263 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://iacat.org/content/development-item-bank-assessment-depression-persons-mental-illnesses-and-physical-diseases02366nas a2200217 4500008004100000020002200041245010800063210006900171250001500240260001000255300001200265490000700277520166400284100001401948700001401962700001601976700001201992700001702004700001502021856011202036 2009 Eng d a1049-8931 (Print)00aEvaluation of a computer-adaptive test for the assessment of depression (D-CAT) in clinical application0 aEvaluation of a computeradaptive test for the assessment of depr a2009/02/06 cFeb 4 a233-2360 v183 aIn the past, a German Computerized Adaptive Test, based on Item Response Theory (IRT), was developed for purposes of assessing the construct depression [Computer-adaptive test for depression (D-CAT)]. This study aims at testing the feasibility and validity of the real computer-adaptive application.The D-CAT, supplied by a bank of 64 items, was administered on personal digital assistants (PDAs) to 423 consecutive patients suffering from psychosomatic and other medical conditions (78 with depression). Items were adaptively administered until a predetermined reliability (r >/= 0.90) was attained. For validation purposes, the Hospital Anxiety and Depression Scale (HADS), the Centre for Epidemiological Studies Depression (CES-D) scale, and the Beck Depression Inventory (BDI) were administered. Another sample of 114 patients was evaluated using standardized diagnostic interviews [Composite International Diagnostic Interview (CIDI)].The D-CAT was quickly completed (mean 74 seconds), well accepted by the patients and reliable after an average administration of only six items. In 95% of the cases, 10 items or less were needed for a reliable score estimate. Correlations between the D-CAT and the HADS, CES-D, and BDI ranged between r = 0.68 and r = 0.77. The D-CAT distinguished between diagnostic groups as well as established questionnaires do.The D-CAT proved an efficient, well accepted and reliable tool. Discriminative power was comparable to other depression measures, whereby the CAT is shorter and more precise. Item usage raises questions of balancing the item selection for content in the future. Copyright (c) 2009 John Wiley & Sons, Ltd.1 aFliege, H1 aBecker, J1 aWalter, O B1 aRose, M1 aBjorner, J B1 aKlapp, B F uhttp://iacat.org/content/evaluation-computer-adaptive-test-assessment-depression-d-cat-clinical-application02747nas a2200433 4500008004100000020004600041245012800087210006900215250001500284300001200299490000700311520139300318653003401711653001501745653001001760653000901770653002201779653002501801653001101826653001101837653000901848653001601857653001501873653003801888653001901926653003101945653002801976653004802004653002202052100002002074700001202094700001402106700001602120700001402136700001702150700001502167700001502182856011602197 2009 eng d a1878-5921 (Electronic)0895-4356 (Linking)00aAn evaluation of patient-reported outcomes found computerized adaptive testing was efficient in assessing stress perception0 aevaluation of patientreported outcomes found computerized adapti a2008/07/22 a278-2870 v623 aOBJECTIVES: This study aimed to develop and evaluate a first computerized adaptive test (CAT) for the measurement of stress perception (Stress-CAT), in terms of the two dimensions: exposure to stress and stress reaction. STUDY DESIGN AND SETTING: Item response theory modeling was performed using a two-parameter model (Generalized Partial Credit Model). The evaluation of the Stress-CAT comprised a simulation study and real clinical application. A total of 1,092 psychosomatic patients (N1) were studied. Two hundred simulees (N2) were generated for a simulated response data set. Then the Stress-CAT was given to n=116 inpatients, (N3) together with established stress questionnaires as validity criteria. RESULTS: The final banks included n=38 stress exposure items and n=31 stress reaction items. In the first simulation study, CAT scores could be estimated with a high measurement precision (SE<0.32; rho>0.90) using 7.0+/-2.3 (M+/-SD) stress reaction items and 11.6+/-1.7 stress exposure items. The second simulation study reanalyzed real patients data (N1) and showed an average use of items of 5.6+/-2.1 for the dimension stress reaction and 10.0+/-4.9 for the dimension stress exposure. Convergent validity showed significantly high correlations. CONCLUSIONS: The Stress-CAT is short and precise, potentially lowering the response burden of patients in clinical decision making.10a*Diagnosis, Computer-Assisted10aAdolescent10aAdult10aAged10aAged, 80 and over10aConfidence Intervals10aFemale10aHumans10aMale10aMiddle Aged10aPerception10aQuality of Health Care/*standards10aQuestionnaires10aReproducibility of Results10aSickness Impact Profile10aStress, Psychological/*diagnosis/psychology10aTreatment Outcome1 aKocalevent, R D1 aRose, M1 aBecker, J1 aWalter, O B1 aFliege, H1 aBjorner, J B1 aKleiber, D1 aKlapp, B F uhttp://iacat.org/content/evaluation-patient-reported-outcomes-found-computerized-adaptive-testing-was-efficient00629nas a2200181 4500008004100000245006000041210005700101260009700158100001200255700001100267700001600278700001500294700001300309700001600322700001300338700001600351856008000367 2009 eng d00aFeatures of J-CAT (Japanese Computerized Adaptive Test)0 aFeatures of JCAT Japanese Computerized Adaptive Test aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aImai, S1 aIto, S1 aNakamura, Y1 aKikuchi, K1 aAkagi, Y1 aNakasono, H1 aHonda, A1 aHiramura, T uhttp://iacat.org/content/features-j-cat-japanese-computerized-adaptive-test00552nas a2200121 4500008004100000245008100041210006900122260009700191100001700288700001400305700001600319856009500335 2009 eng d00aItem selection and hypothesis testing for the adaptive measurement of change0 aItem selection and hypothesis testing for the adaptive measureme aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aFinkelman, M1 aWeiss, DJ1 aKim-Kang, G uhttp://iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change02900nas a2200289 4500008004100000020004100041245011100082210006900193250001500262260000800277300001400285490000700299520193300306653002702239653003802266653004102304653001902345653001102364653001402375653003102389100001502420700001302435700001202448700001602460700001302476856012102489 2009 eng d a0315-162X (Print)0315-162X (Linking)00aProgress in assessing physical function in arthritis: PROMIS short forms and computerized adaptive testing0 aProgress in assessing physical function in arthritis PROMIS shor a2009/09/10 cSep a2061-20660 v363 aOBJECTIVE: Assessing self-reported physical function/disability with the Health Assessment Questionnaire Disability Index (HAQ) and other instruments has become central in arthritis research. Item response theory (IRT) and computerized adaptive testing (CAT) techniques can increase reliability and statistical power. IRT-based instruments can improve measurement precision substantially over a wider range of disease severity. These modern methods were applied and the magnitude of improvement was estimated. METHODS: A 199-item physical function/disability item bank was developed by distilling 1865 items to 124, including Legacy Health Assessment Questionnaire (HAQ) and Physical Function-10 items, and improving precision through qualitative and quantitative evaluation in over 21,000 subjects, which included about 1500 patients with rheumatoid arthritis and osteoarthritis. Four new instruments, (A) Patient-Reported Outcomes Measurement Information (PROMIS) HAQ, which evolved from the original (Legacy) HAQ; (B) "best" PROMIS 10; (C) 20-item static (short) forms; and (D) simulated PROMIS CAT, which sequentially selected the most informative item, were compared with the HAQ. RESULTS: Online and mailed administration modes yielded similar item and domain scores. The HAQ and PROMIS HAQ 20-item scales yielded greater information content versus other scales in patients with more severe disease. The "best" PROMIS 20-item scale outperformed the other 20-item static forms over a broad range of 4 standard deviations. The 10-item simulated PROMIS CAT outperformed all other forms. CONCLUSION: Improved items and instruments yielded better information. The PROMIS HAQ is currently available and considered validated. The new PROMIS short forms, after validation, are likely to represent further improvement. CAT-based physical function/disability assessment offers superior performance over static forms of equal length.10a*Disability Evaluation10a*Outcome Assessment (Health Care)10aArthritis/diagnosis/*physiopathology10aHealth Surveys10aHumans10aPrognosis10aReproducibility of Results1 aFries, J F1 aCella, D1 aRose, M1 aKrishnan, E1 aBruce, B uhttp://iacat.org/content/progress-assessing-physical-function-arthritis-promis-short-forms-and-computerized-adaptive00371nas a2200121 4500008004100000245004600041210004600087300001000133490000800143100001600151700001400167856006800181 2008 eng d00aAdaptive measurement of individual change0 aAdaptive measurement of individual change a49-580 v2161 aKim-Kang, G1 aWeiss, DJ uhttp://iacat.org/content/adaptive-measurement-individual-change01113nas a2200133 4500008003900000245011000039210006900149300001200218490000700230520065500237100001700892700001700909856005300926 2008 d00aComputer-Based and Paper-and-Pencil Administration Mode Effects on a Statewide End-of-Course English Test0 aComputerBased and PaperandPencil Administration Mode Effects on a554-5700 v683 aThe current study compared student performance between paper-and-pencil testing (PPT) and computer-based testing (CBT) on a large-scale statewide end-of-course English examination. Analyses were conducted at both the item and test levels. The overall results suggest that scores obtained from PPT and CBT were comparable. However, at the content domain level, a rather large difference in the reading comprehension section suggests that reading comprehension test may be more affected by the test administration mode. Results from the confirmatory factor analysis suggest that the administration mode did not alter the construct of the test.
1 aKim, Do-Hong1 aHuynh, Huynh uhttp://epm.sagepub.com/content/68/4/554.abstract03309nas a2200433 4500008004100000020004600041245007700087210006900164250001500233260001100248300001200259490000700271520203200278653002702310653003002337653002102367653001002388653000902398653001502407653003602422653002102458653004402479653002402523653001102547653001102558653001302569653000902582653001602591653003002607653003002637653003102667100001502698700001302713700001502726700001402741700001502755700001402770856009102784 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://iacat.org/content/computerized-adaptive-testing-back-pain-validation-cat-5d-qol00678nas a2200157 4500008004100000245017700041210006900218260003100287100001600318700001200334700001300346700001500359700001400374700001300388856011900401 2008 eng d00aDeveloping a progressive approach to using the GAIN in order to reduce the duration and cost of assessment with the GAIN short screener, Quick and computer adaptive testing0 aDeveloping a progressive approach to using the GAIN in order to aWashington D.C., USAc20081 aDennis, M L1 aFunk, R1 aTitus, J1 aRiley, B B1 aHosman, S1 aKinne, S uhttp://iacat.org/content/developing-progressive-approach-using-gain-order-reduce-duration-and-cost-assessment-gain02386nas a2200205 4500008004100000020001400041245008800055210006900143300001400212490000700226520173800233100001401971700001401985700002001999700001702019700001202036700001602048700001502064856010102079 2008 eng d a1520-639400aFunctioning and validity of a computerized adaptive test to measure anxiety (A CAT)0 aFunctioning and validity of a computerized adaptive test to meas aE182-E1940 v253 aBackground: The aim of this study was to evaluate the Computerized Adaptive Test to measure anxiety (A-CAT), a patient-reported outcome questionnaire that uses computerized adaptive testing to measure anxiety. Methods: The A-CAT builds on an item bank of 50 items that has been built using conventional item analyses and item response theory analyses. The A-CAT was administered on Personal Digital Assistants to n=357 patients diagnosed and treated at the department of Psychosomatic Medicine and Psychotherapy, Charité Berlin, Germany. For validation purposes, two subgroups of patients (n=110 and 125) answered the A-CAT along with established anxiety and depression questionnaires. Results: The A-CAT was fast to complete (on average in 2 min, 38 s) and a precise item response theory based CAT score (reliability>.9) could be estimated after 4–41 items. On average, the CAT displayed 6 items (SD=4.2). Convergent validity of the A-CAT was supported by correlations to existing tools (Hospital Anxiety and Depression Scale-A, Beck Anxiety Inventory, Berliner Stimmungs-Fragebogen A/D, and State Trait Anxiety Inventory: r=.56–.66); discriminant validity between diagnostic groups was higher for the A-CAT than for other anxiety measures. Conclusions: The German A-CAT is an efficient, reliable, and valid tool for assessing anxiety in patients suffering from anxiety disorders and other conditions with significant potential for initial assessment and long-term treatment monitoring. Future research directions are to explore content balancing of the item selection algorithm of the CAT, to norm the tool to a healthy sample, and to develop practical cutoff scores. Depression and Anxiety, 2008. © 2008 Wiley-Liss, Inc.1 aBecker, J1 aFliege, H1 aKocalevent, R D1 aBjorner, J B1 aRose, M1 aWalter, O B1 aKlapp, B F uhttp://iacat.org/content/functioning-and-validity-computerized-adaptive-test-measure-anxiety-cat02190nas a2200145 4500008004100000245009900041210006900140300001000209490000800219520163900227653003401866100001901900700001601919856010901935 2008 eng d00aICAT: An adaptive testing procedure for the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure for the identification of idi a40-480 v2163 aTraditional adaptive tests provide an efficient method for estimating student achievements levels, by adjusting the characteristicsof the test questions to match the performance of each student. These traditional adaptive tests are not designed to identify diosyncraticknowledge patterns. As students move through their education, they learn content in any number of different ways related to their learning style and cognitive development. This may result in a student having different achievement levels from one content area to another within a domain of content. This study investigates whether such idiosyncratic knowledge patterns exist. It discusses the differences between idiosyncratic knowledge patterns and multidimensionality. Finally, it proposes an adaptive testing procedure that can be used to identify a student’s areas of strength and weakness more efficiently than current adaptive testing approaches. The findings of the study indicate that a fairly large number of students may have test results that are influenced by their idiosyncratic knowledge patterns. The findings suggest that these patterns persist across time for a large number of students, and that the differences in student performance between content areas within a subject domain are large enough to allow them to be useful in instruction. Given the existence of idiosyncratic patterns of knowledge, the proposed testing procedure may enable us to provide more useful information to teachers. It should also allow us to differentiate between idiosyncratic patterns or knowledge, and important mutidimensionality in the testing data.
10acomputerized adaptive testing1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/icat-adaptive-testing-procedure-identification-idiosyncratic-knowledge-patterns00500nas a2200121 4500008004100000245009900041210006900140300001200209490001100221100001900232700001600251856011100267 2008 eng d00aICAT: An adaptive testing procedure for the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure for the identification of idi a40–480 v216(1)1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/icat-adaptive-testing-procedure-identification-idiosyncratic-knowledge-patterns-003052nas a2200205 4500008004100000020002700041245012200068210006900190250001500259260001100274300000800285490000600293520234600299100001502645700001402660700001402674700002102688700001502709856012202724 2008 Eng d a1471-2474 (Electronic)00aAn initial application of computerized adaptive testing (CAT) for measuring disability in patients with low back pain0 ainitial application of computerized adaptive testing CAT for mea a2008/12/20 cDec 18 a1660 v93 aABSTRACT: BACKGROUND: Recent approaches to outcome measurement involving Computerized Adaptive Testing (CAT) offer an approach for measuring disability in low back pain (LBP) in a way that can reduce the burden upon patient and professional. The aim of this study was to explore the potential of CAT in LBP for measuring disability as defined in the International Classification of Functioning, Disability and Health (ICF) which includes impairments, activity limitation, and participation restriction. METHODS: 266 patients with low back pain answered questions from a range of widely used questionnaires. An exploratory factor analysis (EFA) was used to identify disability dimensions which were then subjected to Rasch analysis. Reliability was tested by internal consistency and person separation index (PSI). Discriminant validity of disability levels were evaluated by Spearman correlation coefficient (r), intraclass correlation coefficient [ICC(2,1)] and the Bland-Altman approach. A CAT was developed for each dimension, and the results checked against simulated and real applications from a further 133 patients. RESULTS: Factor analytic techniques identified two dimensions named "body functions" and "activity-participation". After deletion of some items for failure to fit the Rasch model, the remaining items were mostly free of Differential Item Functioning (DIF) for age and gender. Reliability exceeded 0.90 for both dimensions. The disability levels generated using all items and those obtained from the real CAT application were highly correlated (i.e. >0.97 for both dimensions). On average, 19 and 14 items were needed to estimate the precise disability levels using the initial CAT for the first and second dimension. However, a marginal increase in the standard error of the estimate across successive iterations substantially reduced the number of items required to make an estimate. CONCLUSIONS: Using a combination approach of EFA and Rasch analysis this study has shown that it is possible to calibrate items onto a single metric in a way that can be used to provide the basis of a CAT application. Thus there is an opportunity to obtain a wide variety of information to evaluate the biopsychosocial model in its more complex forms, without necessarily increasing the burden of information collection for patients.1 aElhan, A H1 aOztuna, D1 aKutlay, S1 aKucukdeveci, A A1 aTennant, A uhttp://iacat.org/content/initial-application-computerized-adaptive-testing-cat-measuring-disability-patients-low-back03153nas a2200493 4500008004100000020002200041245008900063210006900152250001500221260000800236300001000244490000700254520169600261653003401957653002001991653001502011653001002026653000902036653002602045653003202071653003102103653001102134653001102145653000902156653003202165653001602197653002902213653004402242653002902286653003102315653003102346653001702377100001702394700001402411700001602425700001302441700001702454700002202471700001702493700001402510700001402524700001702538856010402555 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://iacat.org/content/using-computerized-adaptive-testing-reduce-burden-mental-health-assessment00569nas a2200109 4500008004100000245010200041210006900143260009700212100001600309700001400325856012000339 2007 eng d00aComparison of computerized adaptive testing and classical methods for measuring individual change0 aComparison of computerized adaptive testing and classical method aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aKim-Kang, G1 aWeiss, DJ uhttp://iacat.org/content/comparison-computerized-adaptive-testing-and-classical-methods-measuring-individual-change00595nas a2200169 4500008004100000245009100041210006900132300001200201490000700213100001600220700001400236700001700250700001400267700001500281700001200296856011700308 2007 eng d00aDevelopment and evaluation of a computer adaptive test for “Anxiety” (Anxiety-CAT)0 aDevelopment and evaluation of a computer adaptive test for Anxie a143-1550 v161 aWalter, O B1 aBecker, J1 aBjorner, J B1 aFliege, H1 aKlapp, B F1 aRose, M uhttp://iacat.org/content/development-and-evaluation-computer-adaptive-test-%E2%80%9Canxiety%E2%80%9D-anxiety-cat00571nas a2200109 4500008004100000245010400041210006900145260009700214100001900311700001600330856011500346 2007 eng d00aICAT: An adaptive testing procedure to allow the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure to allow the identification o aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/icat-adaptive-testing-procedure-allow-identification-idiosyncratic-knowledge-patterns02128nas a2200181 4500008004100000020001300041245013400054210006900188300001200257490000700269520147700276100001601753700001501769700001401784700001601798700001401814856011801828 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://iacat.org/content/evaluation-patient-reported-outcomes-found-computerized-adaptive-testing-was-efficient-000447nas a2200121 4500008003900000245009000039210006900129300001200198490000700210100002200217700002000239856006600259 2005 d00aConstructing a Computerized Adaptive Test for University Applicants With Disabilities0 aConstructing a Computerized Adaptive Test for University Applica a381-4050 v181 aMoshinsky, Avital1 aKazin, Cathrael uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1804_300533nas a2200169 4500008004100000245006700041210006300108300001600171490000700187100001400194700001400208700001600222700001700238700001500255700001200270856008100282 2005 eng d00aDevelopment of a computer-adaptive test for depression (D-CAT)0 aDevelopment of a computeradaptive test for depression DCAT a2277–22910 v141 aFliege, H1 aBecker, J1 aWalter, O B1 aBjorner, J B1 aKlapp, B F1 aRose, M uhttp://iacat.org/content/development-computer-adaptive-test-depression-d-cat10197nas a2200553 4500008004100000245016300041210006900204300001400273490000700287520862500294653001808919653003208937100001608969700001608985700001409001700001609015700001409031700001509045700001609060700001409076700001509090700001509105700001409120700001709134700001709151700001709168700001609185700001709201700001609218700001509234700001609249700001709265700002309282700001609305700002209321700001609343700001609359700001709375700001309392700001509405700001309420700001609433700001209449700001409461700001609475700002009491700001209511856012009523 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://iacat.org/content/toward-efficient-and-comprehensive-measurement-alcohol-problems-continuum-college-students00536nas a2200121 4500008004100000020003800041245007000079210006500149260007200214100001600286700002700302856008500329 2005 eng d aComputerized Testing Report 97-1400aThe use of person-fit statistics in computerized adaptive testing0 ause of personfit statistics in computerized adaptive testing aNewton, PA. USAbLaw School Administration CouncilcSeptember, 20051 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/use-person-fit-statistics-computerized-adaptive-testing00411nas a2200109 4500008004100000245006300041210006300104260001700167100001900184700001400203856008400217 2004 eng d00aComputer adaptive testing and the No Child Left Behind Act0 aComputer adaptive testing and the No Child Left Behind Act aSan Diego CA1 aKingsbury, G G1 aHauser, C uhttp://iacat.org/content/computer-adaptive-testing-and-no-child-left-behind-act02589nas a2200469 4500008004100000245007200041210006900113300001000182490000600192520108600198653002501284653001001309653001501319653002101334653002201355653005901377653007001436653003301506653001101539653001101550653001301561653000901574653002701583653002201610653005501632653001901687653001501706653006601721653001801787653003701805653004101842653003001883653001301913100001501926700001301941700001801954700001501972700001401987700001402001700001302015856009102028 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://iacat.org/content/computerized-adaptive-measurement-depression-simulation-study00507nas a2200133 4500008004100000245005100041210005100092260009900143100001700242700001600259700001400275700000800289856007600297 2004 eng d00aComputerized adaptive testing and item banking0 aComputerized adaptive testing and item banking aP. M. Fayers and R. D. Hays (Eds.) Assessing Quality of Life. Oxford: Oxford University Press.1 aBjorner, J B1 aKosinski, M1 aWare, J E1 aJr. uhttp://iacat.org/content/computerized-adaptive-testing-and-item-banking01251nas a2200157 4500008003900000245006400039210006300103300001200166490000700178520076400185100002500949700002200974700002200996700002201018856005301040 2004 d00aComputerized Adaptive Testing With Multiple-Form Structures0 aComputerized Adaptive Testing With MultipleForm Structures a147-1640 v283 aA multiple-form structure (MFS) is an orderedcollection or network of testlets (i.e., sets of items).An examinee’s progression through the networkof testlets is dictated by the correctness of anexaminee’s answers, thereby adapting the test tohis or her trait level. The collection of pathsthrough the network yields the set of all possibletest forms, allowing test specialists the opportunityto review them before they are administered. Also,limiting the exposure of an individual MFS to aspecific period of time can enhance test security.This article provides an overview of methods thathave been developed to generate parallel MFSs.The approach is applied to the assembly of anexperimental computerized Law School Admission Test (LSAT).
1 aArmstrong, Ronald, D1 aJones, Douglas, H1 aKoppel, Nicole, B1 aPashley, Peter, J uhttp://apm.sagepub.com/content/28/3/147.abstract01539nas a2200229 4500008004100000020002200041245006400063210006300127260002600190300001200216490000700228520081800235653003401053653003001087653002801117653001301145100001901158700001501177700001601192700001701208856008401225 2004 eng d a0146-6216 (Print)00aComputerized adaptive testing with multiple-form structures0 aComputerized adaptive testing with multipleform structures bSage Publications: US a147-1640 v283 aA multiple-form structure (MFS) is an ordered collection or network of testlets (i.e., sets of items). An examinee's progression through the network of testlets is dictated by the correctness of an examinee's answers, thereby adapting the test to his or her trait level. The collection of paths through the network yields the set of all possible test forms, allowing test specialists the opportunity to review them before they are administered. Also, limiting the exposure of an individual MFS to a specific period of time can enhance test security. This article provides an overview of methods that have been developed to generate parallel MFSs. The approach is applied to the assembly of an experimental computerized Law School Admission Test (LSAT). (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aLaw School Admission Test10amultiple-form structure10atestlets1 aArmstrong, R D1 aJones, D H1 aKoppel, N B1 aPashley, P J uhttp://iacat.org/content/computerized-adaptive-testing-multiple-form-structures02884nas a2200301 4500008004100000020002200041245013700063210006900200250001500269260000800284300001000292490000700302520186600309653001102175653003302186653001102219653004602230653002402276653002902300653003002329653002902359100001502388700001602403700001602419700001602435700001002451856012102461 2004 eng d a0003-9993 (Print)00aScore comparability of short forms and computerized adaptive testing: Simulation study with the activity measure for post-acute care0 aScore comparability of short forms and computerized adaptive tes a2004/04/15 cApr a661-60 v853 aOBJECTIVE: To compare simulated short-form and computerized adaptive testing (CAT) scores to scores obtained from complete item sets for each of the 3 domains of the Activity Measure for Post-Acute Care (AM-PAC). DESIGN: Prospective study. SETTING: Six postacute health care networks in the greater Boston metropolitan area, including inpatient acute rehabilitation, transitional care units, home care, and outpatient services. PARTICIPANTS: A convenience sample of 485 adult volunteers who were receiving skilled rehabilitation services. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Inpatient and community-based short forms and CAT applications were developed for each of 3 activity domains (physical & mobility, personal care & instrumental, applied cognition) using item pools constructed from new items and items from existing postacute care instruments. RESULTS: Simulated CAT scores correlated highly with score estimates from the total item pool in each domain (4- and 6-item CAT r range,.90-.95; 10-item CAT r range,.96-.98). Scores on the 10-item short forms constructed for inpatient and community settings also provided good estimates of the AM-PAC item pool scores for the physical & movement and personal care & instrumental domains, but were less consistent in the applied cognition domain. Confidence intervals around individual scores were greater in the short forms than for the CATs. CONCLUSIONS: Accurate scoring estimates for AM-PAC domains can be obtained with either the setting-specific short forms or the CATs. The strong relationship between CAT and item pool scores can be attributed to the CAT's ability to select specific items to match individual responses. The CAT may have additional advantages over short forms in practicality, efficiency, and the potential for providing more precise scoring estimates for individuals.10aBoston10aFactor Analysis, Statistical10aHumans10aOutcome Assessment (Health Care)/*methods10aProspective Studies10aQuestionnaires/standards10aRehabilitation/*standards10aSubacute Care/*standards1 aHaley, S M1 aCoster, W J1 aAndres, P L1 aKosinski, M1 aNi, P uhttp://iacat.org/content/score-comparability-short-forms-and-computerized-adaptive-testing-simulation-study-activity00634nas a2200193 4500008004100000245009100041210006900132300000900201490000700210100001400217700001600231700001400247700001700261700002000278700001400298700001500312700001200327856010100339 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://iacat.org/content/validating-german-computerized-adaptive-test-anxiety-healthy-sample-cat00504nas a2200109 4500008004100000245012000041210006900161260001500230100001500245700001600260856011800276 2003 eng d00aCalibrating CAT pools and online pretest items using nonparametric and adjusted marginal maximum likelihood methods0 aCalibrating CAT pools and online pretest items using nonparametr aChicago IL1 aKrass, I A1 aWilliams, B uhttp://iacat.org/content/calibrating-cat-pools-and-online-pretest-items-using-nonparametric-and-adjusted-marginal02650nas a2200385 4500008004100000245014400041210006900185300001200254490000700266520138100273653002101654653003301675653002901708653001501737653001001752653000901762653002201771653002601793653003301819653002501852653001901877653001001896653002501906653001601931653002401947653002601971653002701997653003202024653001302056653002802069100001702097700001602114700001402130856012002144 2003 eng d00aCalibration of an item pool for assessing the burden of headaches: an application of item response theory to the Headache Impact Test (HIT)0 aCalibration of an item pool for assessing the burden of headache a913-9330 v123 aBACKGROUND: Measurement of headache impact is important in clinical trials, case detection, and the clinical monitoring of patients. Computerized adaptive testing (CAT) of headache impact has potential advantages over traditional fixed-length tests in terms of precision, relevance, real-time quality control and flexibility. OBJECTIVE: To develop an item pool that can be used for a computerized adaptive test of headache impact. METHODS: We analyzed responses to four well-known tests of headache impact from a population-based sample of recent headache sufferers (n = 1016). We used confirmatory factor analysis for categorical data and analyses based on item response theory (IRT). RESULTS: In factor analyses, we found very high correlations between the factors hypothesized by the original test constructers, both within and between the original questionnaires. These results suggest that a single score of headache impact is sufficient. We established a pool of 47 items which fitted the generalized partial credit IRT model. By simulating a computerized adaptive health test we showed that an adaptive test of only five items had a very high concordance with the score based on all items and that different worst-case item selection scenarios did not lead to bias. CONCLUSION: We have established a headache impact item pool that can be used in CAT of headache impact.10a*Cost of Illness10a*Decision Support Techniques10a*Sickness Impact Profile10aAdolescent10aAdult10aAged10aComparative Study10aDisability Evaluation10aFactor Analysis, Statistical10aHeadache/*psychology10aHealth Surveys10aHuman10aLongitudinal Studies10aMiddle Aged10aMigraine/psychology10aModels, Psychological10aPsychometrics/*methods10aQuality of Life/*psychology10aSoftware10aSupport, Non-U.S. Gov't1 aBjorner, J B1 aKosinski, M1 aWare, Jr. uhttp://iacat.org/content/calibration-item-pool-assessing-burden-headaches-application-item-response-theory-headache00549nas a2200133 4500008004100000245011800041210006900159260001500228100001400243700001400257700001400271700001400285856011600299 2003 eng d00aA comparison of item exposure control procedures using a CAT system based on the generalized partial credit model0 acomparison of item exposure control procedures using a CAT syste aChicago IL1 aBurt, W M1 aKim, S -J1 aDavis, LL1 aDodd, B G uhttp://iacat.org/content/comparison-item-exposure-control-procedures-using-cat-system-based-generalized-partial03162nas a2200361 4500008004100000245012500041210006900166300001200235490000700247520200400254653002902258653001502287653001002302653000902312653002202321653002002343653003302363653002402396653001102420653001002431653000902441653001602450653002502466653002602491653004302517653003202560653001902592653002802611100001702639700001602656700001402672856011402686 2003 eng d00aThe feasibility of applying item response theory to measures of migraine impact: a re-analysis of three clinical studies0 afeasibility of applying item response theory to measures of migr a887-9020 v123 aBACKGROUND: Item response theory (IRT) is a powerful framework for analyzing multiitem scales and is central to the implementation of computerized adaptive testing. OBJECTIVES: To explain the use of IRT to examine measurement properties and to apply IRT to a questionnaire for measuring migraine impact--the Migraine Specific Questionnaire (MSQ). METHODS: Data from three clinical studies that employed the MSQ-version 1 were analyzed by confirmatory factor analysis for categorical data and by IRT modeling. RESULTS: Confirmatory factor analyses showed very high correlations between the factors hypothesized by the original test constructions. Further, high item loadings on one common factor suggest that migraine impact may be adequately assessed by only one score. IRT analyses of the MSQ were feasible and provided several suggestions as to how to improve the items and in particular the response choices. Out of 15 items, 13 showed adequate fit to the IRT model. In general, IRT scores were strongly associated with the scores proposed by the original test developers and with the total item sum score. Analysis of response consistency showed that more than 90% of the patients answered consistently according to a unidimensional IRT model. For the remaining patients, scores on the dimension of emotional function were less strongly related to the overall IRT scores that mainly reflected role limitations. Such response patterns can be detected easily using response consistency indices. Analysis of test precision across score levels revealed that the MSQ was most precise at one standard deviation worse than the mean impact level for migraine patients that are not in treatment. Thus, gains in test precision can be achieved by developing items aimed at less severe levels of migraine impact. CONCLUSIONS: IRT proved useful for analyzing the MSQ. The approach warrants further testing in a more comprehensive item pool for headache impact that would enable computerized adaptive testing.10a*Sickness Impact Profile10aAdolescent10aAdult10aAged10aComparative Study10aCost of Illness10aFactor Analysis, Statistical10aFeasibility Studies10aFemale10aHuman10aMale10aMiddle Aged10aMigraine/*psychology10aModels, Psychological10aPsychometrics/instrumentation/*methods10aQuality of Life/*psychology10aQuestionnaires10aSupport, Non-U.S. Gov't1 aBjorner, J B1 aKosinski, M1 aWare, Jr. uhttp://iacat.org/content/feasibility-applying-item-response-theory-measures-migraine-impact-re-analysis-three00516nas a2200169 4500008004100000245003700041210003700078260004900115300001400164653003400178100001800212700001300230700001700243700001200260700001500272856005900287 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://iacat.org/content/item-selection-polytomous-cat00512nas a2200121 4500008004100000245009800041210006900139260001500208100001600223700001800239700001700257856011600274 2003 eng d00aRecalibration of IRT item parameters in CAT: Sparse data matrices and missing data treatments0 aRecalibration of IRT item parameters in CAT Sparse data matrices aChicago IL1 aHarmes, J C1 aParshall, C G1 aKromrey, J D uhttp://iacat.org/content/recalibration-irt-item-parameters-cat-sparse-data-matrices-and-missing-data-treatments01512nas a2200229 4500008004100000245008700041210006900128300001200197490000700209520075300216653002100969653001300990653003001003653003401033653001101067653001501078653001501093653001801108100002301126700002701149856010601176 2003 eng d00aUsing response times to detect aberrant responses in computerized adaptive testing0 aUsing response times to detect aberrant responses in computerize a251-2650 v683 aA lognormal model for response times is used to check response times for aberrances in examinee behavior on computerized adaptive tests. Both classical procedures and Bayesian posterior predictive checks are presented. For a fixed examinee, responses and response times are independent; checks based on response times offer thus information independent of the results of checks on response patterns. Empirical examples of the use of classical and Bayesian checks for detecting two different types of aberrances in response times are presented. The detection rates for the Bayesian checks outperformed those for the classical checks, but at the cost of higher false-alarm rates. A guideline for the choice between the two types of checks is offered.10aAdaptive Testing10aBehavior10aComputer Assisted Testing10acomputerized adaptive testing10aModels10aperson Fit10aPrediction10aReaction Time1 avan der Linden, WJ1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/using-response-times-detect-aberrant-responses-computerized-adaptive-testing01637nas a2200133 4500008004100000245008400041210006900125300001200194490000700206520114900213100002701362700001601389856009801405 2002 eng d00aDetection of person misfit in computerized adaptive tests with polytomous items0 aDetection of person misfit in computerized adaptive tests with p a164-1800 v263 aItem scores that do not fit an assumed item response theory model may cause the latent trait value to be inaccurately estimated. For a computerized adaptive test (CAT) using dichotomous items, several person-fit statistics for detecting mis.tting item score patterns have been proposed. Both for paper-and-pencil (P&P) tests and CATs, detection ofperson mis.t with polytomous items is hardly explored. In this study, the nominal and empirical null distributions ofthe standardized log-likelihood statistic for polytomous items are compared both for P&P tests and CATs. Results showed that the empirical distribution of this statistic differed from the assumed standard normal distribution for both P&P tests and CATs. Second, a new person-fit statistic based on the cumulative sum (CUSUM) procedure from statistical process control was proposed. By means ofsimulated data, critical values were determined that can be used to classify a pattern as fitting or misfitting. The effectiveness of the CUSUM to detect simulees with item preknowledge was investigated. Detection rates using the CUSUM were high for realistic numbers ofdisclosed items. 1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/detection-person-misfit-computerized-adaptive-tests-polytomous-items00524nas a2200109 4500008004100000245010600041210006900147260002500216653003400241100001900275856012000294 2002 eng d00aAn empirical comparison of achievement level estimates from adaptive tests and paper-and-pencil tests0 aempirical comparison of achievement level estimates from adaptiv aNew Orleans, LA. USA10acomputerized adaptive testing1 aKingsbury, G G uhttp://iacat.org/content/empirical-comparison-achievement-level-estimates-adaptive-tests-and-paper-and-pencil-tests00474nas a2200097 4500008004100000245010600041210006900147260001900216100001900235856012200254 2002 eng d00aAn empirical comparison of achievement level estimates from adaptive tests and paper-and-pencil tests0 aempirical comparison of achievement level estimates from adaptiv aNew Orleans LA1 aKingsbury, G G uhttp://iacat.org/content/empirical-comparison-achievement-level-estimates-adaptive-tests-and-paper-and-pencil-tests-001774nas a2200217 4500008004100000245006200041210006200103260005600165300001200221520108400233653002401317653001601341653001401357653002201371653001501393653001801408653001301426100001901439700001601458856008201474 2002 eng d00aGenerating abstract reasoning items with cognitive theory0 aGenerating abstract reasoning items with cognitive theory aMahwah, N.J. USAbLawrence Erlbaum Associates, Inc. a219-2503 a(From the chapter) Developed and evaluated a generative system for abstract reasoning items based on cognitive theory. The cognitive design system approach was applied to generate matrix completion problems. Study 1 involved developing the cognitive theory with 191 college students who were administered Set I and Set II of the Advanced Progressive Matrices. Study 2 examined item generation by cognitive theory. Study 3 explored the psychometric properties and construct representation of abstract reasoning test items with 728 young adults. Five structurally equivalent forms of Abstract Reasoning Test (ART) items were prepared from the generated item bank and administered to the Ss. In Study 4, the nomothetic span of construct validity of the generated items was examined with 728 young adults who were administered ART items, and 217 young adults who were administered ART items and the Advanced Progressive Matrices. Results indicate the matrix completion items were effectively generated by the cognitive design system approach. (PsycINFO Database Record (c) 2005 APA )10aCognitive Processes10aMeasurement10aReasoning10aTest Construction10aTest Items10aTest Validity10aTheories1 aEmbretson, S E1 aKyllomen, P uhttp://iacat.org/content/generating-abstract-reasoning-items-cognitive-theory03058nas a2200325 4500008004100000020004100041245008100082210006900163250001500232260000800247300001100255490000700266520201300273653001502286653001002301653004002311653005702351653003302408653001102441653001102452653001802463653000902481653002802490653001202518653005502530100001502585700001802600700001502618856009902633 2002 eng d a0025-7079 (Print)0025-7079 (Linking)00aMultidimensional adaptive testing for mental health problems in primary care0 aMultidimensional adaptive testing for mental health problems in a2002/09/10 cSep a812-230 v403 aOBJECTIVES: Efficient and accurate instruments for assessing child psychopathology are increasingly important in clinical practice and research. For example, screening in primary care settings can identify children and adolescents with disorders that may otherwise go undetected. However, primary care offices are notorious for the brevity of visits and screening must not burden patients or staff with long questionnaires. One solution is to shorten assessment instruments, but dropping questions typically makes an instrument less accurate. An alternative is adaptive testing, in which a computer selects the items to be asked of a patient based on the patient's previous responses. This research used a simulation to test a child mental health screen based on this technology. RESEARCH DESIGN: Using half of a large sample of data, a computerized version was developed of the Pediatric Symptom Checklist (PSC), a parental-report psychosocial problem screen. With the unused data, a simulation was conducted to determine whether the Adaptive PSC can reproduce the results of the full PSC with greater efficiency. SUBJECTS: PSCs were completed by parents on 21,150 children seen in a national sample of primary care practices. RESULTS: Four latent psychosocial problem dimensions were identified through factor analysis: internalizing problems, externalizing problems, attention problems, and school problems. A simulated adaptive test measuring these traits asked an average of 11.6 questions per patient, and asked five or fewer questions for 49% of the sample. There was high agreement between the adaptive test and the full (35-item) PSC: only 1.3% of screening decisions were discordant (kappa = 0.93). This agreement was higher than that obtained using a comparable length (12-item) short-form PSC (3.2% of decisions discordant; kappa = 0.84). CONCLUSIONS: Multidimensional adaptive testing may be an accurate and efficient technology for screening for mental health problems in primary care settings.10aAdolescent10aChild10aChild Behavior Disorders/*diagnosis10aChild Health Services/*organization & administration10aFactor Analysis, Statistical10aFemale10aHumans10aLinear Models10aMale10aMass Screening/*methods10aParents10aPrimary Health Care/*organization & administration1 aGardner, W1 aKelleher, K J1 aPajer, K A uhttp://iacat.org/content/multidimensional-adaptive-testing-mental-health-problems-primary-care00468nas a2200097 4500008004100000245011500041210006900156260001500225100001500240856011500255 2001 eng d00aApplication of score information for CAT pool development and its connection with "likelihood test information0 aApplication of score information for CAT pool development and it aSeattle WA1 aKrass, I A uhttp://iacat.org/content/application-score-information-cat-pool-development-and-its-connection-likelihood-test01035nas a2200145 4500008004100000245021400041210006900255300001100324490000600335520038100341100001600722700001600738700001700754856011800771 2001 eng d00aConcerns with computerized adaptive oral proficiency assessment. A commentary on "Comparing examinee attitudes Toward computer-assisted and other oral proficient assessments": Response to the Norris Commentary0 aConcerns with computerized adaptive oral proficiency assessment a95-1080 v53 aResponds to an article on computerized adaptive second language (L2) testing, expressing concerns about the appropriateness of such tests for informing language educators about the language skills of L2 learners and users and fulfilling the intended purposes and achieving the desired consequences of language test use.The authors of the original article respond. (Author/VWL)1 aNorris, J M1 aKenyon, D M1 aMalabonga, V uhttp://iacat.org/content/concerns-computerized-adaptive-oral-proficiency-assessment-commentary-comparing-examinee00421nas a2200121 4500008004100000245005900041210005700100300001200157490000700169100002700176700001600203856008000219 2001 eng d00aCUSUM-based person-fit statistics for adaptive testing0 aCUSUMbased personfit statistics for adaptive testing a199-2180 v261 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/cusum-based-person-fit-statistics-adaptive-testing00583nas a2200133 4500008004100000245013700041210006900178260001500247100001800262700001700280700001600297700001700313856011900330 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://iacat.org/content/nearest-neighbors-simple-strata-and-probabilistic-parameters-empirical-comparison-methods00605nas a2200121 4500008004100000245017700041210006900218260002700287100001600314700001700330700001800347856011800365 2001 eng d00aOnline item parameter recalibration: Application of missing data treatments to overcome the effects of sparse data conditions in a computerized adaptive version of the MCAT0 aOnline item parameter recalibration Application of missing data aUnpublished manuscript1 aHarmes, J C1 aKromrey, J D1 aParshall, C G uhttp://iacat.org/content/online-item-parameter-recalibration-application-missing-data-treatments-overcome-effects00476nas a2200109 4500008004100000245008600041210006900127260001500196100002300211700002700234856010500261 2001 eng d00aUsing response times to detect aberrant behavior in computerized adaptive testing0 aUsing response times to detect aberrant behavior in computerized aSeattle WA1 avan der Linden, WJ1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/using-response-times-detect-aberrant-behavior-computerized-adaptive-testing00401nas a2200097 4500008004100000245008000041210006900121260000700190100001500197856009100212 2000 eng d00aChange in distribution of latent ability with item position in CAT sequence0 aChange in distribution of latent ability with item position in C aLA1 aKrass, I A uhttp://iacat.org/content/change-distribution-latent-ability-item-position-cat-sequence00540nas a2200157 4500008004100000245006500041210006300106260002700169490000700196653003400203100001700237700001200254700001200266700001700278856008700295 2000 eng d00aComputer-adaptive testing: A methodology whose time has come0 aComputeradaptive testing A methodology whose time has come aChicago, IL. USAbMESA0 v6910acomputerized adaptive testing1 aLinacre, J M1 aKang, U1 aJean, E1 aLinacre, J M uhttp://iacat.org/content/computer-adaptive-testing-methodology-whose-time-has-come00582nas a2200133 4500008004100000245009000041210006900131260007900200100001600279700001600295700001800311700001400329856010500343 2000 eng d00aComputerized adaptive rating scales (CARS): Development and evaluation of the concept0 aComputerized adaptive rating scales CARS Development and evaluat a(Institute Rep No. 350). Tampa FL: Personnel Decisions Research Institute.1 aBorman, W C1 aHanson, M A1 aKubisiak, U C1 aBuck, D E uhttp://iacat.org/content/computerized-adaptive-rating-scales-cars-development-and-evaluation-concept00600nas a2200109 4500008004100000245009300041210006900134260012700203100002700330700001600357856011700373 2000 eng d00aDetecting person misfit in adaptive testing using statistical process control techniques0 aDetecting person misfit in adaptive testing using statistical pr aW. J. van der Linden, and C. A. W. Glas (Editors). Computerized Adaptive Testing: Theory and Practice. Norwell MA: Kluwer.1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/detecting-person-misfit-adaptive-testing-using-statistical-process-control-techniques-000571nas a2200133 4500008004100000245009300041210006900134260004900203300001200252653001500264100002700279700001600306856011500322 2000 eng d00aDetecting person misfit in adaptive testing using statistical process control techniques0 aDetecting person misfit in adaptive testing using statistical pr aDordrecht, The NetherlandsbKluwer Academic. a201-21910aperson Fit1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/detecting-person-misfit-adaptive-testing-using-statistical-process-control-techniques00639nas a2200109 4500008004100000245011000041210006900151260014400220100002700364700001600391856012200407 2000 eng d00aDetection of person misfit in computerized adaptive testing with polytomous items (Research Report 00-01)0 aDetection of person misfit in computerized adaptive testing with aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/detection-person-misfit-computerized-adaptive-testing-polytomous-items-research-report-00-0100567nas a2200133 4500008004100000245012200041210006900163260003100232100001600263700001600279700001400295700001500309856010900324 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://iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized00585nas a2200133 4500008004100000245014500041210006900186260002600255100001600281700001600297700001400313700001300327856011100340 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://iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized-100583nas a2200133 4500008004100000245014200041210006900183260002700252100001600279700001600295700001400311700001300325856011100338 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://iacat.org/content/estimating-item-parameters-classical-indices-item-pool-development-computerized-000525nas a2200133 4500008004100000245010200041210006900143300001000212490000700222100001600229700001600245700001700261856011300278 2000 eng d00aItem exposure control in computer-adaptive testing: The use of freezing to augment stratification0 aItem exposure control in computeradaptive testing The use of fre a28-520 v401 aParshall, C1 aHarmes, J C1 aKromrey, J D uhttp://iacat.org/content/item-exposure-control-computer-adaptive-testing-use-freezing-augment-stratification02714nas a2200169 4500008004100000245011500041210006900156300000900225490000700234520208500241653001302326653002802339653002602367653001602393100001602409856011902425 2000 eng d00aLagrangian relaxation for constrained curve-fitting with binary variables: Applications in educational testing0 aLagrangian relaxation for constrained curvefitting with binary v a10630 v613 aThis dissertation offers a mathematical programming approach to curve fitting with binary variables. Various Lagrangian Relaxation (LR) techniques are applied to constrained curve fitting. Applications in educational testing with respect to test assembly are utilized. In particular, techniques are applied to both static exams (i.e. conventional paper-and-pencil (P&P)) and adaptive exams (i.e. a hybrid computerized adaptive test (CAT) called a multiple-forms structure (MFS)). This dissertation focuses on the development of mathematical models to represent these test assembly problems as constrained curve-fitting problems with binary variables and solution techniques for the test development. Mathematical programming techniques are used to generate parallel test forms with item characteristics based on item response theory. A binary variable is used to represent whether or not an item is present on a form. The problem of creating a test form is modeled as a network flow problem with additional constraints. In order to meet the target information and the test characteristic curves, a Lagrangian relaxation heuristic is applied to the problem. The Lagrangian approach works by multiplying the constraint by a "Lagrange multiplier" and adding it to the objective. By systematically varying the multiplier, the test form curves approach the targets. This dissertation explores modifications to Lagrangian Relaxation as it is applied to the classical paper-and-pencil exams. For the P&P exams, LR techniques are also utilized to include additional practical constraints to the network problem, which limit the item selection. An MFS is a type of a computerized adaptive test. It is a hybrid of a standard CAT and a P&P exam. The concept of an MFS will be introduced in this dissertation, as well as, the application of LR as it is applied to constructing parallel MFSs. The approach is applied to the Law School Admission Test for the assembly of the conventional P&P test as well as an experimental computerized test using MFSs. (PsycINFO Database Record (c) 2005 APA )10aAnalysis10aEducational Measurement10aMathematical Modeling10aStatistical1 aKoppel, N B uhttp://iacat.org/content/lagrangian-relaxation-constrained-curve-fitting-binary-variables-applications-educational00482nas a2200121 4500008004100000245008700041210006900128300001200197490000700209100002700216700001600243856010100259 2000 eng d00aThe null distribution of person-fit statistics for conventional and adaptive tests0 anull distribution of personfit statistics for conventional and a a327-3450 v231 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/null-distribution-person-fit-statistics-conventional-and-adaptive-tests00484nas a2200121 4500008003900000245009100039210006900130300001200199490000700211100001400218700001900232856011100251 2000 d00aPractical issues in developing and maintaining a computerized adaptive testing program0 aPractical issues in developing and maintaining a computerized ad a135-1550 v211 aWise, S L1 aKingsbury, G G uhttp://iacat.org/content/practical-issues-developing-and-maintaining-computerized-adaptive-testing-program00634nas a2200133 4500008004100000245020600041210006900247300001000316490000700326100001400333700001700347700001600364856012000380 2000 eng d00aResponse to Hays et al and McHorney and Cohen: Practical implications of item response theory and computerized adaptive testing: A brief summary of ongoing studies of widely used headache impact scales0 aResponse to Hays et al and McHorney and Cohen Practical implicat a73-820 v381 aWare, Jr.1 aBjorner, J B1 aKosinski, M uhttp://iacat.org/content/response-hays-et-al-and-mchorney-and-cohen-practical-implications-item-response-theory-and00556nas a2200121 4500008004100000245013100041210006900172260001900241100001800260700001700278700001700295856012200312 2000 eng d00aSufficient simplicity or comprehensive complexity? A comparison of probabilitic and stratification methods of exposure control0 aSufficient simplicity or comprehensive complexity A comparison o aNew Orleans LA1 aParshall, C G1 aKromrey, J D1 aHogarty, K Y uhttp://iacat.org/content/sufficient-simplicity-or-comprehensive-complexity-comparison-probabilitic-and-stratification00375nas a2200097 4500008004100000245006400041210006200105260001200167100001400179856008400193 2000 eng d00aTest security and item exposure control for computer-based 0 aTest security and item exposure control for computerbased aChicago1 aKalohn, J uhttp://iacat.org/content/test-security-and-item-exposure-control-computer-based00645nas a2200109 4500008004100000245011000041210006900151260014400220100002300364700002700387856012100414 2000 eng d00aUsing response times to detect aberrant behavior in computerized adaptive testing (Research Report 00-09)0 aUsing response times to detect aberrant behavior in computerized aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 avan der Linden, WJ1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/using-response-times-detect-aberrant-behavior-computerized-adaptive-testing-research-report00485nas a2200109 4500008004100000245009800041210006900139260002100208100001500229700001900244856011200263 1999 eng d00aAutomated flawed item detection and graphical item used in on-line calibration of CAT-ASVAB. 0 aAutomated flawed item detection and graphical item used in onlin aMontreal, Canada1 aKrass, I A1 aThomasson, G L uhttp://iacat.org/content/automated-flawed-item-detection-and-graphical-item-used-line-calibration-cat-asvab00486nas a2200109 4500008004100000245009900041210006900140260002100209100001900230700001200249856011500261 1999 eng d00aA comparison of conventional and adaptive testing procedures for making single-point decisions0 acomparison of conventional and adaptive testing procedures for m aMontreal, Canada1 aKingsbury, G G1 aZara, A uhttp://iacat.org/content/comparison-conventional-and-adaptive-testing-procedures-making-single-point-decisions00488nas a2200133 4500008004100000245007400041210006700115260001300182100001600195700001300211700001300224700001400237856010300251 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://iacat.org/content/computerized-testing-%E2%80%93-issues-and-applications-mini-course-manual00423nas a2200121 4500008004100000245005900041210005700100300001200157490000700169100002700176700001600203856008200219 1999 eng d00aCUSUM-based person-fit statistics for adaptive testing0 aCUSUMbased personfit statistics for adaptive testing a199-2180 v261 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/cusum-based-person-fit-statistics-adaptive-testing-000592nas a2200109 4500008004100000245008300041210006900124260014400193100002700337700001600364856010200380 1999 eng d00aCUSUM-based person-fit statistics for adaptive testing (Research Report 99-05)0 aCUSUMbased personfit statistics for adaptive testing Research Re aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/cusum-based-person-fit-statistics-adaptive-testing-research-report-99-0500517nas a2200109 4500008004100000245006300041210006300104260012100167100001900288700001600307856008400323 1999 eng d00aDeveloping computerized adaptive tests for school children0 aDeveloping computerized adaptive tests for school children aF. Drasgow and J. B. Olson-Buchanan (Eds.), Innovations in computerized assessment (pp. 93-115). Mahwah NJ: Erlbaum.1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/developing-computerized-adaptive-tests-school-children00499nas a2200121 4500008004100000245009700041210006900138300001000207100001400217700001700231700001600248856011300264 1999 eng d00aDynamic health assessments: The search for more practical and more precise outcomes measures0 aDynamic health assessments The search for more practical and mor a11-131 aWare, Jr.1 aBjorner, J B1 aKosinski, M uhttp://iacat.org/content/dynamic-health-assessments-search-more-practical-and-more-precise-outcomes-measures01680nas a2200145 4500008004100000245010000041210006900141300001000210490000700220520112900227653003401356100001601390700001501406856011301421 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://iacat.org/content/effect-model-misspecification-classification-decisions-made-using-computerized-test02151nas a2200277 4500008004100000020002200041245009600063210006900159250001500228260000800243300001100251490000700262520122800269653001601497653003901513653003701552653001101589653003301600653002501633653002701658653003101685100001701716700001601733700001701749856010701766 1999 eng d a1040-2446 (Print)00aEvaluating the usefulness of computerized adaptive testing for medical in-course assessment0 aEvaluating the usefulness of computerized adaptive testing for m a1999/10/28 cOct a1125-80 v743 aPURPOSE: This study investigated the feasibility of converting an existing computer-administered, in-course internal medicine test to an adaptive format. METHOD: A 200-item internal medicine extended matching test was used for this research. Parameters were estimated with commercially available software with responses from 621 examinees. A specially developed simulation program was used to retrospectively estimate the efficiency of the computer-adaptive exam format. RESULTS: It was found that the average test length could be shortened by almost half with measurement precision approximately equal to that of the full 200-item paper-and-pencil test. However, computer-adaptive testing with this item bank provided little advantage for examinees at the upper end of the ability continuum. An examination of classical item statistics and IRT item statistics suggested that adding more difficult items might extend the advantage to this group of examinees. CONCLUSIONS: Medical item banks presently used for incourse assessment might be advantageously employed in adaptive testing. However, it is important to evaluate the match between the items and the measurement objective of the test before implementing this format.10a*Automation10a*Education, Medical, Undergraduate10aEducational Measurement/*methods10aHumans10aInternal Medicine/*education10aLikelihood Functions10aPsychometrics/*methods10aReproducibility of Results1 aKreiter, C D1 aFerguson, K1 aGruppen, L D uhttp://iacat.org/content/evaluating-usefulness-computerized-adaptive-testing-medical-course-assessment00430nas a2200097 4500008004100000245008600041210006900127100001600196700001500212856010500227 1999 eng d00aFormula score and direct optimization algorithms in CAT ASVAB on-line calibration0 aFormula score and direct optimization algorithms in CAT ASVAB on1 aLevine, M V1 aKrass, I A uhttp://iacat.org/content/formula-score-and-direct-optimization-algorithms-cat-asvab-line-calibration00481nas a2200121 4500008004100000245008600041210006900127260001600196100001600212700001500228700001500243856010100258 1999 eng d00aItem exposure in adaptive tests: An empirical investigation of control strategies0 aItem exposure in adaptive tests An empirical investigation of co aLawrence KS1 aParshall, C1 aHogarty, K1 aKromrey, J uhttp://iacat.org/content/item-exposure-adaptive-tests-empirical-investigation-control-strategies00484nas a2200121 4500008004100000245008700041210006900128300001200197490000700209100002700216700001600243856010300259 1999 eng d00aThe null distribution of person-fit statistics for conventional and adaptive tests0 anull distribution of personfit statistics for conventional and a a327-3450 v231 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/null-distribution-person-fit-statistics-conventional-and-adaptive-tests-000500nas a2200109 4500008004100000245010600041210006900147260002100216100001900237700001200256856012200268 1999 eng d00aA procedure to compare conventional and adaptive testing procedures for making single-point decisions0 aprocedure to compare conventional and adaptive testing procedure aMontreal, Canada1 aKingsbury, G G1 aZara, A uhttp://iacat.org/content/procedure-compare-conventional-and-adaptive-testing-procedures-making-single-point-decisions00399nas a2200097 4500008004100000245006700041210006700108260002100175100001900196856008600215 1999 eng d00aStandard errors of proficiency estimates in stratum scored CAT0 aStandard errors of proficiency estimates in stratum scored CAT aMontreal, Canada1 aKingsbury, G G uhttp://iacat.org/content/standard-errors-proficiency-estimates-stratum-scored-cat00892nas a2200121 4500008004100000245011200041210006900153300001000222490000600232520039700238100001500635856012000650 1999 eng d00aThreats to score comparability with applications to performance assessments and computerized adaptive tests0 aThreats to score comparability with applications to performance a73-960 v63 aDevelops a conceptual framework that addresses score comparability for performance assessments, adaptive tests, paper-and-pencil tests, and alternate item pools for computerized tests. Outlines testing situation aspects that might threaten score comparability and describes procedures for evaluating the degree of score comparability. Suggests ways to minimize threats to comparability. (SLD)1 aKolen, M J uhttp://iacat.org/content/threats-score-comparability-applications-performance-assessments-and-computerized-adaptive00485nas a2200109 4500008004100000245011200041210006900153300001000222490000600232100001500238856012200253 1999 eng d00aThreats to score comparability with applications to performance assessments and computerized adaptive tests0 aThreats to score comparability with applications to performance a73-960 v61 aKolen, M J uhttp://iacat.org/content/threats-score-comparability-applications-performance-assessments-and-computerized-adaptive-001906nas a2200229 4500008004100000245008600041210006900127300001000196490000700206520111400213653003201327653003701359653001001396653003401406653003001440653002901470653003201499100001601531700001801547700001301565856009801578 1999 eng d00aThe use of Rasch analysis to produce scale-free measurement of functional ability0 ause of Rasch analysis to produce scalefree measurement of functi a83-900 v533 aInnovative applications of Rasch analysis can lead to solutions for traditional measurement problems and can produce new assessment applications in occupational therapy and health care practice. First, Rasch analysis is a mechanism that translates scores across similar functional ability assessments, thus enabling the comparison of functional ability outcomes measured by different instruments. This will allow for the meaningful tracking of functional ability outcomes across the continuum of care. Second, once the item-difficulty order of an instrument or item bank is established by Rasch analysis, computerized adaptive testing can be used to target items to the patient's ability level, reducing assessment length by as much as one half. More importantly, Rasch analysis can provide the foundation for "equiprecise" measurement or the potential to have precise measurement across all levels of functional ability. The use of Rasch analysis to create scale-free measurement of functional ability demonstrates how this methodlogy can be used in practical applications of clinical and outcome assessment.10a*Activities of Daily Living10aDisabled Persons/*classification10aHuman10aOccupational Therapy/*methods10aPredictive Value of Tests10aQuestionnaires/standards10aSensitivity and Specificity1 aVelozo, C A1 aKielhofner, G1 aLai, J-S uhttp://iacat.org/content/use-rasch-analysis-produce-scale-free-measurement-functional-ability00444nas a2200097 4500008004100000245009600041210006900137260001700206100001500223856010800238 1998 eng d00aApplication of direct optimization for on-line calibration in computerized adaptive testing0 aApplication of direct optimization for online calibration in com aSan Diego CA1 aKrass, I A uhttp://iacat.org/content/application-direct-optimization-line-calibration-computerized-adaptive-testing00553nas a2200157 4500008004100000245007600041210006900117260001400186100001600200700001600216700002000232700001500252700001400267700001800281856009600299 1998 eng d00aComputerized adaptive rating scales that measure contextual performance0 aComputerized adaptive rating scales that measure contextual perf aDallas TX1 aBorman, W C1 aHanson, M A1 aMontowidlo, S J1 aDrasgow, F1 aFoster, L1 aKubisiak, U C uhttp://iacat.org/content/computerized-adaptive-rating-scales-measure-contextual-performance00473nas a2200109 4500008004100000245009400041210006900135260001700204100001600221700001500237856011100252 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://iacat.org/content/effect-item-selection-item-exposure-rates-within-computerized-classification-test00640nas a2200109 4500008004100000245011100041210006900152260014400221100002700365700001600392856012200408 1998 eng d00aPerson fit based on statistical process control in an adaptive testing environment (Research Report 98-13)0 aPerson fit based on statistical process control in an adaptive t aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aKrimpen-Stoop, E M L A1 aMeijer, R R uhttp://iacat.org/content/person-fit-based-statistical-process-control-adaptive-testing-environment-research-report-9800594nas a2200133 4500008004100000245012500041210006900166260004600235100001400281700001600295700001600311700001400327856011900341 1998 eng d00aThe relationship between computer familiarity and performance on computer-based TOEFL test tasks (Research Report 98-08)0 arelationship between computer familiarity and performance on com aPrinceton NJ: Educational Testing Service1 aTaylor, C1 aJamieson, J1 aEignor, D R1 aKirsch, I uhttp://iacat.org/content/relationship-between-computer-familiarity-and-performance-computer-based-toefl-test-tasks00650nas a2200109 4500008004100000245012200041210006900163260014400232100001600376700002700392856012100419 1998 eng d00aSimulating the null distribution of person-fit statistics for conventional and adaptive tests (Research Report 98-02)0 aSimulating the null distribution of personfit statistics for con aEnschede, The Netherlands: University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/simulating-null-distribution-person-fit-statistics-conventional-and-adaptive-tests-research00646nas a2200121 4500008004100000245009700041210006900138260014500207100001600352700001600368700002700384856011300411 1998 eng d00aStatistical tests for person misfit in computerized adaptive testing (Research Report 98-01)0 aStatistical tests for person misfit in computerized adaptive tes aEnschede, The Netherlands : University of Twente, Faculty of Educational Science and Technology, Department of Measurement and Data Analysis1 aGlas, C A W1 aMeijer, R R1 aKrimpen-Stoop, E M L A uhttp://iacat.org/content/statistical-tests-person-misfit-computerized-adaptive-testing-research-report-98-0100592nas a2200145 4500008004100000020001000041245007300051210006900124260010000193300000700293100001600300700001600316700002300332856009100355 1998 eng d a98-0100aStatistical tests for person misfit in computerized adaptive testing0 aStatistical tests for person misfit in computerized adaptive tes aEnschede, The NetherlandsbFaculty of Educational Science and Technology, Univeersity of Twente a281 aGlas, C A W1 aMeijer, R R1 aKrimpen-Stoop, E M uhttp://iacat.org/content/statistical-tests-person-misfit-computerized-adaptive-testing00476nas a2200109 4500008004100000245010300041210006900144260001200213100001200225700001500237856011400252 1997 eng d00aEvaluating comparability in computerized adaptive testing: A theoretical framework with an example0 aEvaluating comparability in computerized adaptive testing A theo aChicago1 aWang, T1 aKolen, M J uhttp://iacat.org/content/evaluating-comparability-computerized-adaptive-testing-theoretical-framework-example00387nas a2200097 4500008004100000245005600041210005600097260004300153100001500196856007800211 1997 eng d00aGetting more precision on computer adaptive testing0 aGetting more precision on computer adaptive testing aUniversity of Tennessee, Knoxville, TN1 aKrass, I A uhttp://iacat.org/content/getting-more-precision-computer-adaptive-testing00324nas a2200097 4500008004100000245004200041210004200083260001500125100001900140856006700159 1997 eng d00aItem pool development and maintenance0 aItem pool development and maintenance aChicago IL1 aKingsbury, G G uhttp://iacat.org/content/item-pool-development-and-maintenance00460nas a2200097 4500008004100000245010700041210006900148260001500217100001900232856011100251 1997 eng d00aSome questions that must be addressed to develop and maintain an item pool for use in an adaptive test0 aSome questions that must be addressed to develop and maintain an aChicago IL1 aKingsbury, G G uhttp://iacat.org/content/some-questions-must-be-addressed-develop-and-maintain-item-pool-use-adaptive-test00613nas a2200145 4500008004100000245005200041210005100093260016700144100001600311700001600327700002100343700001600364700001700380856007000397 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://iacat.org/content/validation-experimental-cat-asvab-system00307nas a2200097 4500008004100000245003700041210003700078260001300115100001900128856006200147 1996 eng d00aItem review and adaptive testing0 aItem review and adaptive testing aNew York1 aKingsbury, G G uhttp://iacat.org/content/item-review-and-adaptive-testing01004nas a2200145 4500008004100000245005600041210005600097300001200153490000700165520056200172100001400734700002000748700001400768856007600782 1995 eng d00aComputerized adaptive testing with polytomous items0 aComputerized adaptive testing with polytomous items a5–22.0 v193 aDiscusses polytomous item response theory models and the research that has been conducted to investigate a variety of possible operational procedures (item bank, item selection, trait estimation, stopping rule) for polytomous model-based computerized adaptive testing (PCAT). Studies are reviewed that compared PCAT systems based on competing item response theory models that are appropriate for the same measurement objective, as well as applications of PCAT in marketing and educational psychology. Directions for future research using PCAT are suggested.1 aDodd, B G1 ade Ayala, R. J.1 aKoch, W R uhttp://iacat.org/content/computerized-adaptive-testing-polytomous-items00432nas a2200133 4500008004500000245005600045210005600101300000900157490000700166100001400173700001800187700001500205856007800220 1995 Engldsh 00aComputerized Adaptive Testing With Polytomous Items0 aComputerized Adaptive Testing With Polytomous Items a5-220 v191 aDodd, B G1 aDe Ayala, R J1 aKoch. W.R. uhttp://iacat.org/content/computerized-adaptive-testing-polytomous-items-000588nas a2200133 4500008004100000245013900041210006900180260002000249100001500269700001600284700001400300700001800314856012200332 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://iacat.org/content/effect-model-misspecification-classification-decisions-made-using-computerized-test-3-plm-vs00473nas a2200109 4500008004100000245009500041210006900136260002100205100001100226700001600237856011000253 1995 eng d00aThe influence of examinee test-taking behavior motivation in computerized adaptive testing0 ainfluence of examinee testtaking behavior motivation in computer aSan Francisco CA1 aKim, J1 aMcLean, J E uhttp://iacat.org/content/influence-examinee-test-taking-behavior-motivation-computerized-adaptive-testing00509nas a2200121 4500008004100000245011200041210006900153300001300222490000700235100001400242700001400256856011700270 1995 eng d00aAn investigation of procedures for computerized adaptive testing using the successive intervals Rasch model0 ainvestigation of procedures for computerized adaptive testing us a976-990.0 v551 aKoch, W R1 aDodd, B G uhttp://iacat.org/content/investigation-procedures-computerized-adaptive-testing-using-successive-intervals-rasch00545nas a2200109 4500008004100000245007200041210006900113260013400182100001700316700001600333856008600349 1995 eng d00aPrerequisite relationships for the adaptive assessment of knowledge0 aPrerequisite relationships for the adaptive assessment of knowle aGreer, J. (Ed.) Proceedings of AIED'95, 7th World Conference on Artificial Intelligence in Education, Washington, DC, AACE 43-50.1 aDowling, C E1 aKaluscha, R uhttp://iacat.org/content/prerequisite-relationships-adaptive-assessment-knowledge00503nas a2200121 4500008004100000245009300041210006900134300000900203490000700212653003400219100001300253856011500266 1994 eng d00aMonte Carlo simulation comparison of two-stage testing and computerized adaptive testing0 aMonte Carlo simulation comparison of twostage testing and comput a25480 v5410acomputerized adaptive testing1 aKim, H-O uhttp://iacat.org/content/monte-carlo-simulation-comparison-two-stage-testing-and-computerized-adaptive-testing00509nas a2200133 4500008004100000245008100041210006900122300001000191490000700201653003400208100001900242700001600261856009800277 1993 eng d00aAssessing the utility of item response models: computerized adaptive testing0 aAssessing the utility of item response models computerized adapt a21-270 v1210acomputerized adaptive testing1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/assessing-utility-item-response-models-computerized-adaptive-testing01363nas a2200145 4500008004100000245013200041210006900173300001100242490000700253520078900260100001401049700001401063700002001077856012001097 1993 eng d00aComputerized adaptive testing using the partial credit model: Effects of item pool characteristics and different stopping rules0 aComputerized adaptive testing using the partial credit model Eff a61-77.0 v533 aSimulated datasets were used to research the effects of the systematic variation of three major variables on the performance of computerized adaptive testing (CAT) procedures for the partial credit model. The three variables studied were the stopping rule for terminating the CATs, item pool size, and the distribution of the difficulty of the items in the pool. Results indicated that the standard error stopping rule performed better across the variety of CAT conditions than the minimum information stopping rule. In addition it was found that item pools that consisted of as few as 30 items were adequate for CAT provided that the item pool was of medium difficulty. The implications of these findings for implementing CAT systems based on the partial credit model are discussed. 1 aDodd, B G1 aKoch, W R1 ade Ayala, R. J. uhttp://iacat.org/content/computerized-adaptive-testing-using-partial-credit-model-effects-item-pool-characteristics00371nas a2200097 4500008004100000245006000041210006000101260001900161100001100180856008200191 1993 eng d00aIndividual differences in computerized adaptive testing0 aIndividual differences in computerized adaptive testing aNew Orleans LA1 aKim, J uhttp://iacat.org/content/individual-differences-computerized-adaptive-testing00410nas a2200121 4500008004100000245005600041210005200097260001500149100001400164700001900178700001600197856007500213 1993 eng d00aAn investigation of restricted self-adapted testing0 ainvestigation of restricted selfadapted testing aAtlanta GA1 aWise, S L1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/investigation-restricted-self-adapted-testing00472nas a2200109 4500008004100000245009300041210006900134260001600203100001100219700001500230856011700245 1993 eng d00aMonte Carlo simulation comparison of two-stage testing and computerized adaptive testing0 aMonte Carlo simulation comparison of twostage testing and comput aAtlanta, GA1 aKim, H1 aPlake, B S uhttp://iacat.org/content/monte-carlo-simulation-comparison-two-stage-testing-and-computerized-adaptive-testing-000451nas a2200097 4500008004100000245009900041210006900140100001900209700001600228856010900244 1993 eng d00aA practical examination of the use of free-response questions in computerized adaptive testing0 apractical examination of the use of freeresponse questions in co1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/practical-examination-use-free-response-questions-computerized-adaptive-testing00517nas a2200133 4500008004100000245009900041210006900140300001000209490000600219100001800225700001400243700001400257856011200271 1992 eng d00aA comparison of the partial credit and graded response models in computerized adaptive testing0 acomparison of the partial credit and graded response models in c a17-340 v51 aDe Ayala, R J1 aDodd, B G1 aKoch, W R uhttp://iacat.org/content/comparison-partial-credit-and-graded-response-models-computerized-adaptive-testing00478nas a2200133 4500008004100000245008200041210006900123300001200192490000700204100001100211700001400222700001300236856009500249 1992 eng d00aA comparison of the performance of simulated hierarchical and linear testlets0 acomparison of the performance of simulated hierarchical and line a243-2510 v291 aWainer1 aKaplan, B1 aLewis, C uhttp://iacat.org/content/comparison-performance-simulated-hierarchical-and-linear-testlets00427nas a2200097 4500008004100000245008800041210006900129260001200198100001500210856010400225 1992 eng d00aEstimation of ability level by using only observable quantities in adaptive testing0 aEstimation of ability level by using only observable quantities aChicago1 aKirisci, L uhttp://iacat.org/content/estimation-ability-level-using-only-observable-quantities-adaptive-testing00449nas a2200109 4500008004100000245007800041210006900119260001900188100002100207700001500228856009600243 1992 eng d00aScaling of two-stage adaptive test configurations for achievement testing0 aScaling of twostage adaptive test configurations for achievement aNew Orleans LA1 aHendrickson, A B1 aKolen, M J uhttp://iacat.org/content/scaling-two-stage-adaptive-test-configurations-achievement-testing00511nas a2200145 4500008004100000245008200041210006900123300001200192490000600204100001100210700001300221700001400234700001600248856010100264 1991 eng d00aBuilding algebra testlets: A comparison of hierarchical and linear structures0 aBuilding algebra testlets A comparison of hierarchical and linea axxx-xxx0 v81 aWainer1 aLewis, C1 aKaplan, B1 aBraswell, J uhttp://iacat.org/content/building-algebra-testlets-comparison-hierarchical-and-linear-structures00580nas a2200121 4500008004100000245016000041210006900201300000900270490000700279653003400286100002000320856011800340 1991 eng d00aA comparison of paper-and-pencil, computer-administered, computerized feedback, and computerized adaptive testing methods for classroom achievement testing0 acomparison of paperandpencil computeradministered computerized f a17190 v5210acomputerized adaptive testing1 aKuan, Tsung Hao uhttp://iacat.org/content/comparison-paper-and-pencil-computer-administered-computerized-feedback-and-computerized00363nas a2200085 4500008004100000245006800041210006500109100001900174856008400193 1991 eng d00aA comparison of procedures for content-sensitive item selection0 acomparison of procedures for contentsensitive item selection1 aKingsbury, G G uhttp://iacat.org/content/comparison-procedures-content-sensitive-item-selection00492nas a2200121 4500008004100000245009900041210006900140300001200209490000600221100001900227700001200246856011200258 1991 eng d00aA comparison of procedures for content-sensitive item selection in computerized adaptive tests0 acomparison of procedures for contentsensitive item selection in a241-2610 v41 aKingsbury, G G1 aZara, A uhttp://iacat.org/content/comparison-procedures-content-sensitive-item-selection-computerized-adaptive-tests00518nas a2200121 4500008004100000245007700041210006900118260007500187100001100262700001400273700001300287856009600300 1991 eng d00aSome empirical guidelines for building testlets (Technical Report 91-56)0 aSome empirical guidelines for building testlets Technical Report aPrinceton NJ: Educational Testing Service, Program Statistics Research1 aWainer1 aKaplan, B1 aLewis, C uhttp://iacat.org/content/some-empirical-guidelines-building-testlets-technical-report-91-5600457nas a2200109 4500008004100000245009200041210006900133300000800202490001100210100001900221856010700240 1990 eng d00aAdapting adaptive testing: Using the MicroCAT Testing System in a local school district0 aAdapting adaptive testing Using the MicroCAT Testing System in a a3-60 v29 (2)1 aKingsbury, G G uhttp://iacat.org/content/adapting-adaptive-testing-using-microcat-testing-system-local-school-district00551nas a2200133 4500008004100000245010600041210006900147260003100216100001100247700001300258700001100271700001600282856011900298 1990 eng d00aAn adaptive algebra test: A testlet-based, hierarchically structured test with validity-based scoring0 aadaptive algebra test A testletbased hierarchically structured t aETS Technical Report 90-921 aWainer1 aLewis, C1 aKaplan1 aBraswell, J uhttp://iacat.org/content/adaptive-algebra-test-testlet-based-hierarchically-structured-test-validity-based-scoring00450nas a2200109 4500008004100000245008100041210006900122260001400191100001900205700001600224856010000240 1990 eng d00aAssessing the utility of item response models: Computerized adaptive testing0 aAssessing the utility of item response models Computerized adapt aBoston MA1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/assessing-utility-item-response-models-computerized-adaptive-testing-000416nas a2200133 4500008004100000245005100041210005100092300001000143490000700153100001400160700001400174700002100188856007300209 1990 eng d00aComputerized adaptive measurement of attitudes0 aComputerized adaptive measurement of attitudes a20-300 v231 aKoch, W R1 aDodd, B G1 aFitzpatrick, S J uhttp://iacat.org/content/computerized-adaptive-measurement-attitudes01504nas a2200157 4500008004100000245008900041210006900130300001200199490000700211520093700218653003401155100002001189700001401209700001401223856010901237 1990 eng d00aA simulation and comparison of flexilevel and Bayesian computerized adaptive testing0 asimulation and comparison of flexilevel and Bayesian computerize a227-2390 v273 aComputerized adaptive testing (CAT) is a testing procedure that adapts an examination to an examinee's ability by administering only items of appropriate difficulty for the examinee. In this study, the authors compared Lord's flexilevel testing procedure (flexilevel CAT) with an item response theory-based CAT using Bayesian estimation of ability (Bayesian CAT). Three flexilevel CATs, which differed in test length (36, 18, and 11 items), and three Bayesian CATs were simulated; the Bayesian CATs differed from one another in the standard error of estimate (SEE) used for terminating the test (0.25, 0.10, and 0.05). Results showed that the flexilevel 36- and 18-item CATs produced ability estimates that may be considered as accurate as those of the Bayesian CAT with SEE = 0.10 and comparable to the Bayesian CAT with SEE = 0.05. The authors discuss the implications for classroom testing and for item response theory-based CAT.10acomputerized adaptive testing1 ade Ayala, R. J.1 aDodd, B G1 aKoch, W R uhttp://iacat.org/content/simulation-and-comparison-flexilevel-and-bayesian-computerized-adaptive-testing00543nas a2200145 4500008004500000245009400045210006900139300001200208490000700220100001500227700001500242700001700257700001400274856010900288 1989 Engldsh 00aAdaptive and Conventional Versions of the DAT: The First Complete Test Battery Comparison0 aAdaptive and Conventional Versions of the DAT The First Complete a363-3710 v131 aHenly, S J1 aKlebe, K J1 aMcBride, J R1 aCudeck, R uhttp://iacat.org/content/adaptive-and-conventional-versions-dat-first-complete-test-battery-comparison-000537nas a2200145 4500008004100000245009400041210006900135300001200204490000700216100001500223700001500238700001700253700001400270856010700284 1989 eng d00aAdaptive and conventional versions of the DAT: The first complete test battery comparison0 aAdaptive and conventional versions of the DAT The first complete a363-3710 v131 aHenly, S J1 aKlebe, K J1 aMcBride, J R1 aCudeck, R uhttp://iacat.org/content/adaptive-and-conventional-versions-dat-first-complete-test-battery-comparison00516nas a2200109 4500008004100000245013200041210006900173260001800242100001900260700001600279856011100295 1989 eng d00aAssessing the impact of using item parameter estimates obtained from paper-and-pencil testing for computerized adaptive testing0 aAssessing the impact of using item parameter estimates obtained aSan Francisco1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/assessing-impact-using-item-parameter-estimates-obtained-paper-and-pencil-testing00646nas a2200097 4500008004100000245013800041210006900179260016300248100001800411856011900429 1989 eng d00aDie Optimierung der Mebgenauikeit beim branched adaptiven Testen [Optimization of measurement precision for branched-adaptive testing0 aDie Optimierung der Mebgenauikeit beim branched adaptiven Testen aK. D. Kubinger (Ed.), Moderne Testtheorie Ein Abrib samt neusten Beitrgen [Modern test theory Overview and new issues] (pp. 187-218). Weinhem, Germany: Beltz.1 aKubinger, K D uhttp://iacat.org/content/die-optimierung-der-mebgenauikeit-beim-branched-adaptiven-testen-optimization-measurement00489nas a2200121 4500008004100000245009800041210006900139300001200208490000600220100001400226700001400240856011300254 1989 eng d00aAn investigation of procedures for computerized adaptive testing using partial credit scoring0 ainvestigation of procedures for computerized adaptive testing us a335-3570 v21 aKoch, W R1 aDodd, B G uhttp://iacat.org/content/investigation-procedures-computerized-adaptive-testing-using-partial-credit-scoring00523nas a2200133 4500008004500000245009500045210006900140300001200209490000700221100001400228700001400242700001800256856011500274 1989 Engldsh 00aOperational Characteristics of Adaptive Testing Procedures Using the Graded Response Model0 aOperational Characteristics of Adaptive Testing Procedures Using a129-1430 v131 aDodd, B G1 aKoch, W R1 aDe Ayala, R J uhttp://iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-graded-response-model-000519nas a2200133 4500008004100000245009500041210006900136300001200205490000700217100001400224700001400238700002000252856011300272 1989 eng d00aOperational characteristics of adaptive testing procedures using the graded response model0 aOperational characteristics of adaptive testing procedures using a129-1430 v131 aDodd, B G1 aKoch, W R1 ade Ayala, R. J. uhttp://iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-graded-response-model00430nas a2200121 4500008004100000245006700041210006700108300001200175490000600187100001900193700001200212856008400224 1989 eng d00aProcedures for selecting items for computerized adaptive tests0 aProcedures for selecting items for computerized adaptive tests a359-3750 v21 aKingsbury, G G1 aZara, A uhttp://iacat.org/content/procedures-selecting-items-computerized-adaptive-tests00491nas a2200121 4500008004100000245009400041210006900135300001200204490000700216100001300223700002500236856010800261 1989 eng d00aTailored interviewing: An application of item response theory for personality measurement0 aTailored interviewing An application of item response theory for a502-5190 v531 aKamakura1 aBalasubramanian, S K uhttp://iacat.org/content/tailored-interviewing-application-item-response-theory-personality-measurement00482nas a2200121 4500008004100000245009400041210006900135300001000204490000700214100001700221700001400238856010800252 1988 eng d00aAssessment of academic skills of learning disabled students with classroom microcomputers0 aAssessment of academic skills of learning disabled students with a81-880 v171 aWatkins, M W1 aKush, J C uhttp://iacat.org/content/assessment-academic-skills-learning-disabled-students-classroom-microcomputers00505nas a2200109 4500008004100000245011200041210006900153260001900222100001900241700001600260856011900276 1988 eng d00aA comparison of achievement level estimates from computerized adaptive testing and paper-and-pencil testing0 acomparison of achievement level estimates from computerized adap aNew Orleans LA1 aKingsbury, G G1 aHouser, R L uhttp://iacat.org/content/comparison-achievement-level-estimates-computerized-adaptive-testing-and-paper-and-pencil00520nas a2200121 4500008004100000245010800041210006900149260001600218100001400234700001400248700002000262856011600282 1988 eng d00aComputerized adaptive attitude measurement: A comparison of the graded response and rating scale models0 aComputerized adaptive attitude measurement A comparison of the g aNew Orleans1 aDodd, B G1 aKoch, W R1 ade Ayala, R. J. uhttp://iacat.org/content/computerized-adaptive-attitude-measurement-comparison-graded-response-and-rating-scale00475nas a2200121 4500008004100000245008700041210006900128300001000197490001100207100001900218700001200237856010400249 1988 eng d00aComputerized adaptive testing: A four-year-old pilot study shows that CAT can work0 aComputerized adaptive testing A fouryearold pilot study shows th a73-760 v16 (4)1 aKingsbury, G G1 aet. al. uhttp://iacat.org/content/computerized-adaptive-testing-four-year-old-pilot-study-shows-cat-can-work00382nas a2200109 4500008004100000245005500041210005300096260001900149100001500168700001400183856007500197 1988 eng d00aA predictive analysis approach to adaptive testing0 apredictive analysis approach to adaptive testing aNew Orleans LA1 aKirisci, L1 aHsu, T -C uhttp://iacat.org/content/predictive-analysis-approach-adaptive-testing00476nas a2200097 4500008004100000245007000041210006200111260010100173100001800274856008600292 1988 eng d00aOn a Rasch-model-based test for non-computerized adaptive testing0 aRaschmodelbased test for noncomputerized adaptive testing aLangeheine, R. and Rost, J. (Ed.), Latent trait and latent class models. New York: Plenum Press.1 aKubinger, K D uhttp://iacat.org/content/rasch-model-based-test-non-computerized-adaptive-testing00482nas a2200121 4500008004100000245009700041210006900138300001200207490000700219100001100226700001500237856010800252 1987 eng d00aCATS, testlets, and test construction: A rationale for putting test developers back into CAT0 aCATS testlets and test construction A rationale for putting test a185-2020 v321 aWainer1 aKiely, G L uhttp://iacat.org/content/cats-testlets-and-test-construction-rationale-putting-test-developers-back-cat00511nas a2200109 4500008004100000245011700041210006900158260001800227100002000245700001400265856012200279 1987 eng d00aComputerized adaptive testing: A comparison of the nominal response model and the three-parameter logistic model0 aComputerized adaptive testing A comparison of the nominal respon aWashington DC1 ade Ayala, R. J.1 aKoch, W R uhttp://iacat.org/content/computerized-adaptive-testing-comparison-nominal-response-model-and-three-parameter-logistic00536nas a2200121 4500008004100000245011700041210006900158260002700227100001200254700001300266700001400279856012100293 1987 eng d00aFunctional and design specifications for the National Council of State Boards of Nursing adaptive testing system0 aFunctional and design specifications for the National Council of aUnpublished manuscript1 aZara, A1 aBosma, J1 aKaplan, R uhttp://iacat.org/content/functional-and-design-specifications-national-council-state-boards-nursing-adaptive-testing00439nas a2200121 4500008003900000245007300039210006900112300001200181490000700193100001100200700001500211856009100226 1987 d00aItem clusters and computerized adaptive testing: A case for testlets0 aItem clusters and computerized adaptive testing A case for testl a185-2010 v241 aWainer1 aKiely, G L uhttp://iacat.org/content/item-clusters-and-computerized-adaptive-testing-case-testlets00561nas a2200109 4500008004100000245012200041210006900163260007500232100001100307700001500318856011800333 1986 eng d00aCATs, testlets, and test construction: A rationale for putting test developers back into CAT (Technical Report 86-71)0 aCATs testlets and test construction A rationale for putting test aPrinceton NJ: Educational Testing Service, Program Statistics Research1 aWainer1 aKiely, G L uhttp://iacat.org/content/cats-testlets-and-test-construction-rationale-putting-test-developers-back-cat-technical00563nas a2200121 4500008004100000245011900041210006900160260004800229100001400277700001500291700001600306856011900322 1986 eng d00aCollege Board computerized placement tests: Validation of an adaptive test of basic skills (Research Report 86-29)0 aCollege Board computerized placement tests Validation of an adap aPrinceton NJ: Educational Testing Service.1 aWard, W C1 aKline, R G1 aFlaugher, J uhttp://iacat.org/content/college-board-computerized-placement-tests-validation-adaptive-test-basic-skills-research00514nas a2200097 4500008004100000245005100041210005000092260018200142100001900324856007300343 1986 eng d00aComputerized adaptive testing: A pilot project0 aComputerized adaptive testing A pilot project aW. C. Ryan (ed.), Proceedings: NECC 86, National Educational Computing Conference (pp.172-176). Eugene OR: University of Oregon, International Council on Computers in Education.1 aKingsbury, G G uhttp://iacat.org/content/computerized-adaptive-testing-pilot-project00478nas a2200109 4500008004100000245009200041210006900133260002100202100001400223700001700237856011400254 1986 eng d00aOperational characteristics of adaptive testing procedures using partial credit scoring0 aOperational characteristics of adaptive testing procedures using aSan Francisco CA1 aKoch, W R1 aG., Dodd., B uhttp://iacat.org/content/operational-characteristics-adaptive-testing-procedures-using-partial-credit-scoring00645nas a2200121 4500008004100000245022600041210006900267300000900336490000700345653003400352100001900386856011800405 1985 eng d00aAdaptive self-referenced testing as a procedure for the measurement of individual change due to instruction: A comparison of the reliabilities of change estimates obtained from conventional and adaptive testing procedures0 aAdaptive selfreferenced testing as a procedure for the measureme a30570 v4510acomputerized adaptive testing1 aKingsbury, G G uhttp://iacat.org/content/adaptive-self-referenced-testing-procedure-measurement-individual-change-due-instruction00442nas a2200121 4500008004100000245007200041210006900113300000800182490000600190100002000196700001400216856009000230 1985 eng d00aALPHATAB: A lookup table for Bayesian computerized adaptive testing0 aALPHATAB A lookup table for Bayesian computerized adaptive testi a3260 v91 ade Ayala, R. J.1 aKoch, W R uhttp://iacat.org/content/alphatab-lookup-table-bayesian-computerized-adaptive-testing00357nas a2200109 4500008004100000245004700041210004700088260001200135100001400147700001400161856007200175 1985 eng d00aComputerized adaptive attitude measurement0 aComputerized adaptive attitude measurement aChicago1 aKoch, W R1 aDodd, B G uhttp://iacat.org/content/computerized-adaptive-attitude-measurement01630nas a2200145 4500008004100000245008600041210006900127300001200196490000700208520111300215100001701328700001601345700001501361856010801376 1985 eng d00aCurrent developments and future directions in computerized personality assessment0 aCurrent developments and future directions in computerized perso a803-8150 v533 aAlthough computer applications in personality assessment have burgeoned rapidly in recent years, the majority of these uses capitalize on the computer's speed, accuracy, and memory capacity rather than its potential for the development of new, flexible assessment strategies. A review of current examples of computer usage in personality assessment reveals wide acceptance of automated clerical tasks such as test scoring and even test administration. The computer is also assuming tasks previously reserved for expert clinicians, such as writing narrative interpretive reports from test results. All of these functions represent automation of established assessment devices and interpretive strategies. The possibility also exists of harnessing some of the computer's unique adaptive capabilities to alter standard devices and even develop new ones. Three proposed strategies for developing computerized adaptive personality tests are described, with the conclusion that the computer's potential in this area justifies a call for further research efforts., (C) 1985 by the American Psychological Association1 aButcher, J N1 aKeller, L S1 aBacon, S F uhttp://iacat.org/content/current-developments-and-future-directions-computerized-personality-assessment00506nas a2200109 4500008004100000245011600041210006900157100001600226700001600242700002100258856011700279 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://iacat.org/content/validity-study-computerized-adaptive-testing-version-armed-services-vocational-aptitude00638nam a2200097 4500008004100000245022200041210006900263260007500332100001900407856011400426 1984 eng d00aAdaptive self-referenced testing as a procedure for the measurement of individual change in instruction: A comparison of the reliabilities of change estimates obtained from conventional and adaptive testing procedures0 aAdaptive selfreferenced testing as a procedure for the measureme aUnpublished doctoral dissertation, Univerity of Minnesota, Minneapolis1 aKingsbury, G G uhttp://iacat.org/content/adaptive-self-referenced-testing-procedure-measurement-individual-change-instruction00483nas a2200121 4500008004500000245008700045210006900132300001200201490000600213100001800219700001600237856010800253 1984 Engldsh 00aItem Location Effects and Their Implications for IRT Equating and Adaptive Testing0 aItem Location Effects and Their Implications for IRT Equating an a147-1540 v81 aKingston, N M1 aDorans, N J uhttp://iacat.org/content/item-location-effects-and-their-implications-irt-equating-and-adaptive-testing00621nas a2200121 4500008004100000245011400041210006900155260011200224100001500336700001200351700001400363856012200377 1983 eng d00aAlternate forms reliability and concurrent validity of adaptive and conventional tests with military recruits0 aAlternate forms reliability and concurrent validity of adaptive aMinneapolis MN: University of Minnesota, Department of Psychology, Computerized Adaptive Testing Laboratory1 aKiely, G L1 aZara, A1 aWeiss, DJ uhttp://iacat.org/content/alternate-forms-reliability-and-concurrent-validity-adaptive-and-conventional-tests-military00531nas a2200121 4500008004100000245009900041210006900140260003900209300001200248100001900260700001400279856011600293 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure.0 acomparison of IRTbased adaptive mastery testing and a sequential aNew York, NY. USAbAcademic Press. a258-2831 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure00617nas a2200109 4500008004100000245009800041210006900139260014800208100001900356700001400375856011800389 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure0 acomparison of IRTbased adaptive mastery testing and a sequential aD. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 257-283). New York: Academic Press.1 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure-000609nas a2200109 4500008004100000245009800041210006900139260013900208100002000347700001400367856011800381 1983 eng d00aA comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure0 acomparison of IRTbased adaptive mastery testing and a sequential aD. J. Weiss (Ed.), New horizons in testing: Latent trait theory and computerized adaptive testing (pp. 1-8). New York: Academic Press.1 aKingsbury, G.G.1 aWeiss, DJ uhttp://iacat.org/content/comparison-irt-based-adaptive-mastery-testing-and-sequential-mastery-testing-procedure-100597nas a2200109 4500008004100000245010900041210006900150260011400219100001900333700001400352856012100366 1981 eng d00aA validity comparison of adaptive and conventional strategies for mastery testing (Research Report 81-3)0 avalidity comparison of adaptive and conventional strategies for aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/validity-comparison-adaptive-and-conventional-strategies-mastery-testing-research-report-8100626nas a2200109 4500008004100000245014500041210006900186260011400255100001900369700001400388856011400402 1980 eng d00aAn alternate-forms reliability and concurrent validity comparison of Bayesian adaptive and conventional ability tests (Research Report 80-5)0 aalternateforms reliability and concurrent validity comparison of aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/alternate-forms-reliability-and-concurrent-validity-comparison-bayesian-adaptive-and00604nas a2200109 4500008004100000245012300041210006900164260011400233100001900347700001400366856011400380 1980 eng d00aA comparison of adaptive, sequential, and conventional testing strategies for mastery decisions (Research Report 80-4)0 acomparison of adaptive sequential and conventional testing strat aMinneapolis, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/comparison-adaptive-sequential-and-conventional-testing-strategies-mastery-decisions00702nas a2200109 4500008004100000245009600041210006900137260024100206100001900447700001400466856011200480 1980 eng d00aA comparison of ICC-based adaptive mastery testing and the Waldian probability ratio method0 acomparison of ICCbased adaptive mastery testing and the Waldian aD. J. Weiss (Ed.). Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 120-139). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory1 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/comparison-icc-based-adaptive-mastery-testing-and-waldian-probability-ratio-method00616nas a2200097 4500008004100000245011300041210006900154260015700223100001700380856012100397 1980 eng d00aComputerized instructional adaptive testing model: Formulation and validation (AFHRL-TR-79-33, Final Report)0 aComputerized instructional adaptive testing model Formulation an aBrooks Air Force Base TX: Air Force Human Resources Laboratory", Also Catalog of Selected Documents in Psychology, February 1981, 11, 20 (Ms. No, 2217) 1 aKalisch, S J uhttp://iacat.org/content/computerized-instructional-adaptive-testing-model-formulation-and-validation-afhrl-tr-79-3300432nas a2200109 4500008004100000245006300041210006000104260004600164100002000210700001500230856007700245 1980 eng d00aAn empirical study of a broad range test of verbal ability0 aempirical study of a broad range test of verbal ability aPrinceton NJ: Educational Testing Service1 aKreitzberg, C B1 aJones, D J uhttp://iacat.org/content/empirical-study-broad-range-test-verbal-ability00647nas a2200097 4500008004100000245008200041210006900123260024200192100001700434856009800451 1980 eng d00aA model for computerized adaptive testing related to instructional situations0 amodel for computerized adaptive testing related to instructional aD. J. Weiss (Ed.). Proceedings of the 1979 Computerized Adaptive Testing Conference (pp. 101-119). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program, Computerized Adaptive Testing Laboratory.1 aKalisch, S J uhttp://iacat.org/content/model-computerized-adaptive-testing-related-instructional-situations00522nas a2200109 4500008004100000245007800041210006900119260009700188100001900285700001400304856009400318 1979 eng d00aAn adaptive testing strategy for mastery decisions (Research Report 79-5)0 aadaptive testing strategy for mastery decisions Research Report aMinneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aKingsbury, G G1 aWeiss, DJ uhttp://iacat.org/content/adaptive-testing-strategy-mastery-decisions-research-report-79-500622nas a2200109 4500008004100000245009400041210006900135260016900204100001400373700001700387856010800404 1979 eng d00aProblems in application of latent-trait models to tailored testing (Research Report 79-1)0 aProblems in application of latenttrait models to tailored testin aColumbia MO: University of Missouri, Department of Psychology", (also presented at National Council on Measurement in Education, 1979: ERIC No. ED 177 196) note = "1 aKoch, W J1 aReckase, M D uhttp://iacat.org/content/problems-application-latent-trait-models-tailored-testing-research-report-79-100399nam a2200097 4500008004100000245005600041210005200097260006300149100001500212856007400227 1979 eng d00aThe Rasch model in computerized personality testing0 aRasch model in computerized personality testing aPh.D. dissertation, University of Missouri, Columbia, 19791 aKunce, C S uhttp://iacat.org/content/rasch-model-computerized-personality-testing00605nas a2200109 4500008004100000245007300041210006900114260018600183100001700369700001500386856009400401 1978 eng d00aApplications of sequential testing procedures to performance testing0 aApplications of sequential testing procedures to performance tes aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aEpstein, K I1 aKnerr, C S uhttp://iacat.org/content/applications-sequential-testing-procedures-performance-testing-000399nas a2200109 4500008004100000245006100041210006000102300001200162490001000174100002000184856008500204 1978 eng d00aComputerized adaptive testing: Principles and directions0 aComputerized adaptive testing Principles and directions a319-3290 v2 (4)1 aKreitzberg, C B uhttp://iacat.org/content/computerized-adaptive-testing-principles-and-directions00449nas a2200133 4500008004100000245006100041210006000102300001200162490000600174100002000180700001300200700001500213856008700228 1978 eng d00aComputerized adaptive testing: Principles and directions0 aComputerized adaptive testing Principles and directions a319-3290 v21 aKreitzberg, C B1 aStocking1 aSwanson, L uhttp://iacat.org/content/computerized-adaptive-testing-principles-and-directions-000550nas a2200109 4500008004100000245011600041210006900157260006600226100001400292700001700306856011700323 1978 eng d00aA live tailored testing comparison study of the one- and three-parameter logistic models (Research Report 78-1)0 alive tailored testing comparison study of the one and threeparam aColumbia MO: University of Missouri, Department of Psychology1 aKoch, W J1 aReckase, M D uhttp://iacat.org/content/live-tailored-testing-comparison-study-one-and-three-parameter-logistic-models-research00467nas a2200109 4500008004100000245007300041210006900114260005000183100001700233700001500250856009200265 1977 eng d00aApplications of sequential testing procedures to performance testing0 aApplications of sequential testing procedures to performance tes aMinneapolis, MN. USAbUniversity of Minnesota1 aEpstein, K I1 aKnerr, C S uhttp://iacat.org/content/applications-sequential-testing-procedures-performance-testing00556nas a2200121 4500008004100000245009900041210006900140260007200209100001500281700001400296700001900310856010500329 1977 eng d00aCalibration of an item pool for the adaptive measurement of achievement (Research Report 77-5)0 aCalibration of an item pool for the adaptive measurement of achi aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBejar, I I1 aWeiss, DJ1 aKingsbury, G G uhttp://iacat.org/content/calibration-item-pool-adaptive-measurement-achievement-research-report-77-500387nas a2200097 4500008004100000245005900041210005800100260003700158100001900195856007500214 1977 eng d00aReal-data simulation of a proposal for tailored teting0 aRealdata simulation of a proposal for tailored teting aLeyden, The Netherlandsc06/19771 aKillcross, M C uhttp://iacat.org/content/real-data-simulation-proposal-tailored-teting00532nas a2200109 4500008004100000245004600041210004600087260018600133100001400319700001800333856007100351 1977 eng d00aStudent attitudes toward tailored testing0 aStudent attitudes toward tailored testing aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aKoch, W R1 aPatience, W M uhttp://iacat.org/content/student-attitudes-toward-tailored-testing00450nas a2200133 4500008004100000245006500041210006400106300001200170490000700182100001600189700001500205700001300220856008300233 1977 eng d00aTAILOR: A FORTRAN procedure for interactive tailored testing0 aTAILOR A FORTRAN procedure for interactive tailored testing a767-7690 v371 aCudeck, R A1 aCliff, N A1 aKehoe, J uhttp://iacat.org/content/tailor-fortran-procedure-interactive-tailored-testing00452nas a2200097 4500008004100000245006100041210005800102260009800160100001900258856007700277 1976 eng d00aA review of research in tailored testing (Report APRE No0 areview of research in tailored testing Report APRE No a9/76, Farnborough, Hants, U. K.: Ministry of Defence, Army Personnel Research Establishment.)1 aKillcross, M C uhttp://iacat.org/content/review-research-tailored-testing-report-apre-no00503nam a2200097 4500008004100000245010500041210006900146260006400215100001700279856010900296 1974 eng d00aThe comparison of two tailored testing models and the effects of the models variables on actual loss0 acomparison of two tailored testing models and the effects of the aUnpublished doctoral dissertation, Florida State University1 aKalisch, S J uhttp://iacat.org/content/comparison-two-tailored-testing-models-and-effects-models-variables-actual-loss00422nas a2200097 4500008004100000245008100041210006900122260002400191100001600215856009300231 1974 eng d00aAn empirical investigation of the stability and accuracy of flexilevel tests0 aempirical investigation of the stability and accuracy of flexile aChicago ILc03/10741 aKocher, A T uhttp://iacat.org/content/empirical-investigation-stability-and-accuracy-flexilevel-tests00454nas a2200109 4500008004100000245009000041210006900131300001000200490000600210100001700216856011100233 1974 eng d00aA tailored testing model employing the beta distribution and conditional difficulties0 atailored testing model employing the beta distribution and condi a22-280 v11 aKalisch, S J uhttp://iacat.org/content/tailored-testing-model-employing-beta-distribution-and-conditional-difficulties-000495nas a2200097 4500008004100000245008600041210006900127260008100196100001700277856010300294 1974 eng d00aA tailored testing model employing the beta distribution (unpublished manuscript)0 atailored testing model employing the beta distribution unpublish aFlorida State University, Educational Evaluation and Research Design Program1 aKalisch, S J uhttp://iacat.org/content/tailored-testing-model-employing-beta-distribution-unpublished-manuscript00417nas a2200097 4500008004100000245007900041210006900120260002000189100001900209856009100228 1974 eng d00aA tailored testing system for selection and allocation in the British Army0 atailored testing system for selection and allocation in the Brit aMontreal Canada1 aKillcross, M C uhttp://iacat.org/content/tailored-testing-system-selection-and-allocation-british-army00448nas a2200109 4500008004100000245007700041210006900118260003000187100001900217700001400236856008800250 1973 eng d00aThe potential use of tailored testing for allocation to army employments0 apotential use of tailored testing for allocation to army employm aLisbon, Portugalc06/19731 aKillcross, M C1 aCassie, A uhttp://iacat.org/content/potential-use-tailored-testing-allocation-army-employments00454nas a2200109 4500008004100000245009000041210006900131300001200200490000600212100001700218856010900235 1973 eng d00aA tailored testing model employing the beta distribution and conditional difficulties0 atailored testing model employing the beta distribution and condi a111-1200 v11 aKalisch, S J uhttp://iacat.org/content/tailored-testing-model-employing-beta-distribution-and-conditional-difficulties00426nas a2200109 4500008004100000245008500041210006900126300001200195490000700207100001700214856008500231 1969 eng d00aUse of an on-line computer for psychological testing with the up-and-down method0 aUse of an online computer for psychological testing with the upa a207-2110 v241 aKappauf, W E uhttp://iacat.org/content/use-line-computer-psychological-testing-and-down-method00397nas a2200097 4500008004100000245004800041210004800089260007900137100001700216856006600233 1959 eng d00aProgress report on the sequential item test0 aProgress report on the sequential item test aEast Lansing MI: Michigan State University, Bureau of Educational Research1 aKrathwohl, D uhttp://iacat.org/content/progress-report-sequential-item-test00316nas a2200121 4500008004100000245002900041210002500070300000800095490000600103100001900109700001600128856005000144 1956 eng d00aThe sequential item test0 asequential item test a4190 v21 aKrathwohl, D R1 aHuyser, R J uhttp://iacat.org/content/sequential-item-test