The Bayesian Covariance Structure Model for Testlets

Autor/inn/en	Fox, Jean-Paul; Wenzel, Jeremias; Klotzke, Konrad
Titel	The Bayesian Covariance Structure Model for Testlets
Quelle	In: Journal of Educational and Behavioral Statistics, 46 (2021) 2, S.219-243 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998620941204
Schlagwörter	Bayesian Statistics; Tests; Item Response Theory; Hierarchical Linear Modeling; Equations (Mathematics); Monte Carlo Methods; Markov Processes + Suchen Sie Ihr Suchwort? Examination; Prüfung; Examen; Item-Response-Theorie; Equations; Mathematics; Gleichungslehre; Monte-Carlo-Methode; Markowscher Prozess
Abstract	Standard item response theory (IRT) models have been extended with testlet effects to account for the nesting of items; these are well known as (Bayesian) testlet models or random effect models for testlets. The testlet modeling framework has several disadvantages. A sufficient number of testlet items are needed to estimate testlet effects, and a sufficient number of individuals are needed to estimate testlet variance. The prior for the testlet variance parameter can only represent a positive association among testlet items. The inclusion of testlet parameters significantly increases the number of model parameters, which can lead to computational problems. To avoid these problems, a Bayesian covariance structure model (BCSM) for testlets is proposed, where standard IRT models are extended with a covariance structure model to account for dependences among testlet items. In the BCSM, the dependence among testlet items is modeled without using testlet effects. This approach does not imply any sample size restrictions and is very efficient in terms of the number of parameters needed to describe testlet dependences. The BCSM is compared to the well-known Bayesian random effects model for testlets using a simulation study. Specifically for testlets with a few items, a small number of test takers, or weak associations among testlet items, the BCSM shows more accurate estimation results than the random effects model. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01