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Bayesian Multidimensional IRT Models With a Hierarchical Structure
Yanyan Sheng1*
and
Christopher K. Wikle2
1 Southern Illinois University Carbondale
2 University of Missouri–Columbia
* To whom correspondence should be addressed. E-mail: ysheng{at}siu.edu.
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Abstract |
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As item response models gain increased popularity in large-scale educational and measurement testing situations, many studies have been conducted on the development and applications of unidimensional and multidimensional models. Recently, attention has been paid to IRT-based models with an overall ability dimension underlying several ability dimensions specific for individual test items, where the focus is mainly on models with dichotomous latent traits. The purpose of this study is to propose such models with continuous latent traits under the Bayesian framework. The proposed models are further compared with the conventional IRT models using Bayesian model choice techniques. The results from simulation studies as well as actual data suggest that (a) such models can be developed; (b) compared with the unidimensional IRT model, the proposed models better describe the actual data; and (c) the use of the proposed IRT models and the multiunidimensional model should be based on different beliefs about the underlying dimensional structure of a test.
First published on December 3, 2007, doi:10.1177/0013164407308512
Educational and Psychological Measurement 2008;68:413.
A more recent version of this article appeared on June 1, 2008
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