A direct comparison approach for testing measurement invariance

Gordon W. Cheung, Rebecca S. Lau

Research output: Contribution to journalArticlepeer-review

156 Citations (Scopus)

Abstract

Measurement equivalence/invariance (ME/I) is a condition that should be met before meaningful comparisons of survey results across groups can be made. As an alternative to the likelihood ratio test (LRT), the change in comparative fit index (ΔCFI) rules of thumb, and the modification index (MI), this teaching note demonstrates the procedures for establishing bias-corrected (BC) bootstrap confidence intervals for testing ME/I. Unlike the LRT and ΔCFI methods, which need a different model estimation per item, the BC bootstrap confidence intervals approach can examine item-level ME/I tests using a single model. This method greatly simplifies the search for an invariant item as the reference indicator in the factor-ratio test. Also demonstrated here is how the factor-ratio test and the list-and-delete method can be extended from the metric invariance test to the scalar invariance test. Finally, the BC bootstrap confidence interval procedures for comparing uniqueness variances, factor variances, factor covariances, and latent means across groups are shown.

Original languageEnglish
Pages (from-to)167-198
Number of pages32
JournalOrganizational Research Methods
Volume15
Issue number2
DOIs
Publication statusPublished - Apr 2012

Keywords

  • bootstrapping
  • factor-ratio test
  • latent mean comparisons
  • measurement equivalence/invariance
  • structural equation modeling

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