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ERIC Number: EJ1063587
Record Type: Journal
Publication Date: 2015
Pages: 19
Abstractor: As Provided
Reference Count: N/A
ISSN: ISSN-0022-0655
DIF Detection Using Multiple-Group Categorical CFA with Minimum Free Baseline Approach
Chang, Yu-Wei; Huang, Wei-Kang; Tsai, Rung-Ching
Journal of Educational Measurement, v52 n2 p181-199 Sum 2015
The aim of this study is to assess the efficiency of using the multiple-group categorical confirmatory factor analysis (MCCFA) and the robust chi-square difference test in differential item functioning (DIF) detection for polytomous items under the minimum free baseline strategy. While testing for DIF items, despite the strong assumption that all but the examined item are set to be DIF-free, MCCFA with such a constrained baseline approach is commonly used in the literature. The present study relaxes this strong assumption and adopts the minimum free baseline approach where, aside from those parameters constrained for identification purpose, parameters of all but the examined item are allowed to differ among groups. Based on the simulation results, the robust chi-square difference test statistic with the mean and variance adjustment is shown to be efficient in detecting DIF for polytomous items in terms of the empirical power and Type I error rates. To sum up, MCCFA under the minimum free baseline strategy is useful for DIF detection for polytomous items.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A