A Multilevel Mixture IRT Model With an Application to DIF

Sun-Joo Cho and Allan S. Cohen

Journal of Educational and Behavioral Statistics, 2010, vol. 35, issue 3, 336-370

Abstract: Mixture item response theory models have been suggested as a potentially useful methodology for identifying latent groups formed along secondary, possibly nuisance dimensions. In this article, we describe a multilevel mixture item response theory (IRT) model (MMixIRTM) that allows for the possibility that this nuisance dimensionality may function differently at different levels. A MMixIRT model is described that enables simultaneous detection of differences in latent class composition at both examinee and school levels. The MMixIRTM can be viewed as a combination of an IRT model, an unrestricted latent class model, and a multilevel model. A Bayesian estimation of the MMixIRTM is described including analysis of label switching, use of priors, and model selection strategies. Results of a simulation study indicated that the generated parameters were recovered very well for the conditions considered. Use of MMixIRTM also was illustrated with the standardized mathematics test.

Keywords: finite mixture modeling; item response theory; multilevel modeling; MCMC (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:35:y:2010:i:3:p:336-370

DOI: 10.3102/1076998609353111

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