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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
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
Kim, Nana; Bolt, Daniel M. – Educational and Psychological Measurement, 2021
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…
Descriptors: Item Response Theory, Response Style (Tests), Models, Test Items
Babcock, Ben – Applied Psychological Measurement, 2011
Relatively little research has been conducted with the noncompensatory class of multidimensional item response theory (MIRT) models. A Monte Carlo simulation study was conducted exploring the estimation of a two-parameter noncompensatory item response theory (IRT) model. The estimation method used was a Metropolis-Hastings within Gibbs algorithm…
Descriptors: Item Response Theory, Sampling, Computation, Statistical Analysis
Maguire, Angela M.; Humphreys, Michael S.; Dennis, Simon; Lee, Michael D. – Journal of Memory and Language, 2010
This paper addresses two Global Matching predictions in embedded-category designs: the within-category choice advantage in forced-choice recognition (superior discrimination for test choices comprising a same-category distractor); and the category length effect in forced-choice and old/new recognition (a loss in discriminability with increases in…
Descriptors: Bayesian Statistics, Models, Prediction, Classification
Ip, Edward H. – Applied Psychological Measurement, 2010
The testlet response model is designed for handling items that are clustered, such as those embedded within the same reading passage. Although the testlet is a powerful tool for handling item clusters in educational and psychological testing, the interpretations of its item parameters, the conditional correlation between item pairs, and the…
Descriptors: Item Response Theory, Models, Test Items, Correlation
DeCarlo, Lawrence T. – Applied Psychological Measurement, 2011
Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…
Descriptors: Bayesian Statistics, Computation, Cognitive Tests, Diagnostic Tests
van der Linden, Wim J. – Applied Psychological Measurement, 2009
An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…
Descriptors: Simulation, Adaptive Testing, Vocational Aptitude, Bayesian Statistics
van Barneveld, Christina – Applied Psychological Measurement, 2007
The purpose of this study is to examine the effects of a false assumption regarding the motivation of examinees on test construction. Simulated data were generated using two models of item responses (the three-parameter logistic item response model alone and in combination with Wise's examinee persistence model) and were calibrated using a…
Descriptors: Test Construction, Item Response Theory, Models, Bayesian Statistics

Zwick, Rebecca; Thayer, Dorothy T.; Lewis, Charles – Journal of Educational Measurement, 1999
Developed an empirical Bayes enhancement to Mantel-Haenszel (MH) analysis of differential item functioning (DIF) in which it is assumed that the MH statistics are normally distributed and that the prior distribution of underlying DIF parameters is also normal. (Author/SLD)
Descriptors: Bayesian Statistics, Item Bias, Statistical Distributions, Test Items

Zwick, Rebecca; Thayer, Dorothy; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2000
Studied a method for flagging differential item functioning (DIF) based on loss functions. Builds on earlier research that led to the development of an empirical Bayes enhancement to the Mantel-Haenszel DIF analysis. Tested the method through simulation and found its performance better than some commonly used DIF classification systems. (SLD)
Descriptors: Bayesian Statistics, Identification, Item Bias, Simulation

Zeng, Lingjia – Applied Psychological Measurement, 1997
Proposes a marginal Bayesian estimation procedure to improve item parameter estimates for the three parameter logistic model. Computer simulation suggests that implementing the marginal Bayesian estimation algorithm with four-parameter beta prior distributions and then updating the priors with empirical means of updated intermediate estimates can…
Descriptors: Algorithms, Bayesian Statistics, Estimation (Mathematics), Statistical Distributions
van der Linden, Wim J.; Vos, Hans J. – 1994
This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-based decisions. Simultaneous decision making arises when an institution has to make a series of selection, placement, or mastery decisions with respect to subjects from a population. An obvious example is the use of individualized instruction in…
Descriptors: Bayesian Statistics, Decision Making, Foreign Countries, Scores

McLeod, Lori; Lewis, Charles; Thissen, David – Applied Psychological Measurement, 2003
Explored procedures to detect test takers using item preknowledge in computerized adaptive testing and suggested a Bayesian posterior log odds ratio index for this purpose. Simulation results support the use of the odds ratio index. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Knowledge Level