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A Comparison of Item Fit Statistics for Mixed IRT Models
Journal article   Open access   Peer reviewed

A Comparison of Item Fit Statistics for Mixed IRT Models

Kyong Hee Chon, Won-Chan Lee and Stephen B. Dunbar
Journal of educational measurement, Vol.47(3), pp.318-338
09/01/2010
DOI: 10.1111/j.1745-3984.2010.00116.x
url
https://doi.org/10.1111/j.1745-3984.2010.00116.xView
Published (Version of record) Open Access

Abstract

In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G2, Orlando and Thissen's S - X2 and S - G2, and Stone's chi 2* and G2*. To investigate the relative performance of the fit statistics at the item level, we conducted two simulation studies: Type I error and power studies. We evaluated the performance of the item fit indices for various conditions of test length, sample size, and IRT models. Among the competing measures, the summed score-based indices S - X2 and S - G2 were found to be the sensible and efficient choice for assessing model fit for mixed format data. These indices performed well, particularly with short tests. The pseudo-observed score indices, chi 2* and G2*, showed inflated Type I error rates in some simulation conditions. Consistent with the findings of current literature, the PARSCALE's G2 index was rarely useful, although it provided reasonable results for long tests.
 Psychology Psychology, Applied Psychology, Educational Psychology, Mathematical Social Sciences

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