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He, Yinhong – Journal of Educational Measurement, 2023
Back random responding (BRR) behavior is one of the commonly observed careless response behaviors. Accurately detecting BRR behavior can improve test validities. Yu and Cheng (2019) showed that the change point analysis (CPA) procedure based on weighted residual (CPA-WR) performed well in detecting BRR. Compared with the CPA procedure, the…
Descriptors: Test Validity, Item Response Theory, Measurement, Monte Carlo Methods
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Baris Pekmezci, Fulya; Sengul Avsar, Asiye – International Journal of Assessment Tools in Education, 2021
There is a great deal of research about item response theory (IRT) conducted by simulations. Item and ability parameters are estimated with varying numbers of replications under different test conditions. However, it is not clear what the appropriate number of replications should be. The aim of the current study is to develop guidelines for the…
Descriptors: Item Response Theory, Computation, Accuracy, Monte Carlo Methods
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Yavuz, Guler; Hambleton, Ronald K. – Educational and Psychological Measurement, 2017
Application of MIRT modeling procedures is dependent on the quality of parameter estimates provided by the estimation software and techniques used. This study investigated model parameter recovery of two popular MIRT packages, BMIRT and flexMIRT, under some common measurement conditions. These packages were specifically selected to investigate the…
Descriptors: Item Response Theory, Models, Comparative Analysis, Computer Software
Yildiz, Mustafa – ProQuest LLC, 2017
Student misconceptions have been studied for decades from a curricular/instructional perspective and from the assessment/test level perspective. Numerous misconception assessment tools have been developed in order to measure students' misconceptions relative to the correct content. Often, these tools are used to make a variety of educational…
Descriptors: Misconceptions, Students, Item Response Theory, Models
Wu, Yi-Fang – ProQuest LLC, 2015
Item response theory (IRT) uses a family of statistical models for estimating stable characteristics of items and examinees and defining how these characteristics interact in describing item and test performance. With a focus on the three-parameter logistic IRT (Birnbaum, 1968; Lord, 1980) model, the current study examines the accuracy and…
Descriptors: Item Response Theory, Test Items, Accuracy, Computation
Md Desa, Zairul Nor Deana – ProQuest LLC, 2012
In recent years, there has been increasing interest in estimating and improving subscore reliability. In this study, the multidimensional item response theory (MIRT) and the bi-factor model were combined to estimate subscores, to obtain subscores reliability, and subscores classification. Both the compensatory and partially compensatory MIRT…
Descriptors: Item Response Theory, Computation, Reliability, Classification
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Roberts, James S.; Thompson, Vanessa M. – Applied Psychological Measurement, 2011
A marginal maximum a posteriori (MMAP) procedure was implemented to estimate item parameters in the generalized graded unfolding model (GGUM). Estimates from the MMAP method were compared with those derived from marginal maximum likelihood (MML) and Markov chain Monte Carlo (MCMC) procedures in a recovery simulation that varied sample size,…
Descriptors: Statistical Analysis, Markov Processes, Computation, Monte Carlo Methods
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Kieftenbeld, Vincent; Natesan, Prathiba – Applied Psychological Measurement, 2012
Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…
Descriptors: Test Length, Markov Processes, Item Response Theory, Monte Carlo Methods
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de la Torre, Jimmy; Song, Hao – Applied Psychological Measurement, 2009
Assessments consisting of different domains (e.g., content areas, objectives) are typically multidimensional in nature but are commonly assumed to be unidimensional for estimation purposes. The different domains of these assessments are further treated as multi-unidimensional tests for the purpose of obtaining diagnostic information. However, when…
Descriptors: Ability, Tests, Item Response Theory, Data Analysis
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Finch, Holmes – Applied Psychological Measurement, 2010
The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…
Descriptors: Item Response Theory, Computation, Factor Analysis, Models
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de la Torre, Jimmy; Stark, Stephen; Chernyshenko, Oleksandr S. – Applied Psychological Measurement, 2006
The authors present a Markov Chain Monte Carlo (MCMC) parameter estimation procedure for the generalized graded unfolding model (GGUM) and compare it to the marginal maximum likelihood (MML) approach implemented in the GGUM2000 computer program, using simulated and real personality data. In the simulation study, test length, number of response…
Descriptors: Computation, Monte Carlo Methods, Markov Processes, Item Response Theory
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Wang, Wen-Chung; Chen, Cheng-Te – Educational and Psychological Measurement, 2005
This study investigates item parameter recovery, standard error estimates, and fit statistics yielded by the WINSTEPS program under the Rasch model and the rating scale model through Monte Carlo simulations. The independent variables were item response model, test length, and sample size. WINSTEPS yielded practically unbiased estimates for the…
Descriptors: Statistics, Test Length, Rating Scales, Item Response Theory