DIF Detection Using Multiple-Group Categorical CFA With Minimum Free Baseline Approach

Yu Wei Chang, Wei Kang Huang, Rung-Ching Tsai

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)181-199
Number of pages19
JournalJournal of Educational Measurement
Volume52
Issue number2
DOIs
Publication statusPublished - 2015 Jun 1

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Statistical Factor Analysis
Chi-Square Distribution
factor analysis
Group
statistics
efficiency
simulation

ASJC Scopus subject areas

  • Education
  • Developmental and Educational Psychology
  • Applied Psychology
  • Psychology (miscellaneous)

Cite this

DIF Detection Using Multiple-Group Categorical CFA With Minimum Free Baseline Approach. / Chang, Yu Wei; Huang, Wei Kang; Tsai, Rung-Ching.

In: Journal of Educational Measurement, Vol. 52, No. 2, 01.06.2015, p. 181-199.

Research output: Contribution to journalArticle

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