Type I Error Rates for Generalized Graded Unfolding Model Fit Indices

Authors

Christine E. DeMars, James Madison UniversityFollow

Publication Date

2004

Document Type

Article

Abstract

Type I error rates were examined for several fit indices available in GGUM2000: extensions of Infit, Outfit, Andrich’s χ2, and the log-likelihood ratio χ2. Infit and Outfit had Type I error rates much lower than nominal α. Andrich’s χ2 had Type I error rates much higher than nominal α, particularly for shorter tests or larger sample sizes. The log-likelihood χ2 had Type I error rates near or below nominal α for small samples or longer tests but had inflated error rates with large samples and shorter tests. For conditions in which the log-likelihood ratio χ2 did not perform well, alternative fit indices or modifications to these procedures should be considered in future studies.

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Recommended Citation

DeMars, C. E. (2004). Type I error rates for generalized graded unfolding model fit indices. Applied Psychological Measurement, 28, 48-71.