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Eray Selçuk; Ergül Demir – International Journal of Assessment Tools in Education, 2024
This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions. For this purpose, depending on the changes in the priori distribution type, sample size, test length, and logistics model, the ability and item…
Descriptors: Item Response Theory, Item Analysis, Test Items, Simulation
Egamaria Alacam; Craig K. Enders; Han Du; Brian T. Keller – Grantee Submission, 2023
Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…
Descriptors: Regression (Statistics), Scores, Psychometrics, Test Items
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Kim, Kyung Yong – Journal of Educational Measurement, 2020
New items are often evaluated prior to their operational use to obtain item response theory (IRT) item parameter estimates for quality control purposes. Fixed parameter calibration is one linking method that is widely used to estimate parameters for new items and place them on the desired scale. This article provides detailed descriptions of two…
Descriptors: Item Response Theory, Evaluation Methods, Test Items, Simulation
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Drabinová, Adéla; Martinková, Patrícia – Journal of Educational Measurement, 2017
In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…
Descriptors: Test Items, Regression (Statistics), Guessing (Tests), Identification
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Attali, Yigal; Saldivia, Luis; Jackson, Carol; Schuppan, Fred; Wanamaker, Wilbur – ETS Research Report Series, 2014
Previous investigations of the ability of content experts and test developers to estimate item difficulty have, for themost part, produced disappointing results. These investigations were based on a noncomparative method of independently rating the difficulty of items. In this article, we argue that, by eliciting comparative judgments of…
Descriptors: Test Items, Difficulty Level, Comparative Analysis, College Entrance Examinations
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de la Torre, Jimmy; Lee, Young-Sun – Journal of Educational Measurement, 2013
This article used the Wald test to evaluate the item-level fit of a saturated cognitive diagnosis model (CDM) relative to the fits of the reduced models it subsumes. A simulation study was carried out to examine the Type I error and power of the Wald test in the context of the G-DINA model. Results show that when the sample size is small and a…
Descriptors: Statistical Analysis, Test Items, Goodness of Fit, Error of Measurement
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Ranger, Jochen; Kuhn, Jorg-Tobias – Journal of Educational Measurement, 2012
The information matrix can equivalently be determined via the expectation of the Hessian matrix or the expectation of the outer product of the score vector. The identity of these two matrices, however, is only valid in case of a correctly specified model. Therefore, differences between the two versions of the observed information matrix indicate…
Descriptors: Goodness of Fit, Item Response Theory, Models, Matrices
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Debelak, Rudolf; Arendasy, Martin – Educational and Psychological Measurement, 2012
A new approach to identify item clusters fitting the Rasch model is described and evaluated using simulated and real data. The proposed method is based on hierarchical cluster analysis and constructs clusters of items that show a good fit to the Rasch model. It thus gives an estimate of the number of independent scales satisfying the postulates of…
Descriptors: Test Items, Factor Analysis, Evaluation Methods, Simulation
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Yao, Lihua – Applied Psychological Measurement, 2013
Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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Suh, Youngsuk; Bolt, Daniel M. – Journal of Educational Measurement, 2011
In multiple-choice items, differential item functioning (DIF) in the correct response may or may not be caused by differentially functioning distractors. Identifying distractors as causes of DIF can provide valuable information for potential item revision or the design of new test items. In this paper, we examine a two-step approach based on…
Descriptors: Test Items, Test Bias, Multiple Choice Tests, Simulation
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Gan, Zhengdong – Changing English: Studies in Culture and Education, 2012
Leung and Lewkowicz remind us that the debate over the past two decades that is most relevant to ELT (English languge teaching) pedagogy and curriculum concerns test-task authenticity. This paper first reviews how the authenticity debate in the literature of second language acquisition, pedagogy and testing has evolved. Drawing on a body of…
Descriptors: Teaching Methods, English (Second Language), Second Language Learning, Second Language Instruction
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Wang, Wen-Chung; Jin, Kuan-Yu – Educational and Psychological Measurement, 2010
In this study, the authors extend the standard item response model with internal restrictions on item difficulty (MIRID) to fit polytomous items using cumulative logits and adjacent-category logits. Moreover, the new model incorporates discrimination parameters and is rooted in a multilevel framework. It is a nonlinear mixed model so that existing…
Descriptors: Difficulty Level, Test Items, Item Response Theory, Generalization
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Thompson, Nathan A. – Practical Assessment, Research & Evaluation, 2011
Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…
Descriptors: Adaptive Testing, Computer Assisted Testing, Classification, Probability
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Carvajal, Jorge; Skorupski, William P. – Educational and Psychological Measurement, 2010
This study is an evaluation of the behavior of the Liu-Agresti estimator of the cumulative common odds ratio when identifying differential item functioning (DIF) with polytomously scored test items using small samples. The Liu-Agresti estimator has been proposed by Penfield and Algina as a promising approach for the study of polytomous DIF but no…
Descriptors: Test Bias, Sample Size, Test Items, Computation
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Murphy, Daniel L.; Dodd, Barbara G.; Vaughn, Brandon K. – Applied Psychological Measurement, 2010
This study examined the performance of the maximum Fisher's information, the maximum posterior weighted information, and the minimum expected posterior variance methods for selecting items in a computerized adaptive testing system when the items were grouped in testlets. A simulation study compared the efficiency of ability estimation among the…
Descriptors: Simulation, Adaptive Testing, Item Analysis, Item Response Theory
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