The role of multiple-group measurement invariance in family psychology research

Justin L. Kern, Brent A. McBride, Daniel J. Laxman, W. Justin Dyer, Rosa M. Santos, Laurie M. Jeans

Research output: Contribution to journalArticlepeer-review

Abstract

Measurement invariance (MI) is a property of measurement that is often implicitly assumed, but in many cases, not tested. When the assumption of MI is tested, it generally involves determining if the measurement holds longitudinally or cross-culturally. A growing literature shows that other groupings can, and should, be considered as well. Additionally, it is noted that the standard techniques for investigating MI have been focused almost exclusively on the case of 2 groups, with very little work on the case of more than 2 groups, even though the need for such techniques is apparent in many fields of research. This paper introduces and illustrates a model building technique to investigating MI for more than 2 groups. This technique is an extension of the already-existing hierarchy for testing MI introduced by Meredith (1993). An example using data on father involvement in 5 different groups of families of children with and without developmental disabilities from the Early Childhood Longitudinal Study-Birth Cohort dataset will be given. We show that without considering the possible differential functioning of the measurements on multiple developmental groups, the differences present between the groups in terms of the measurements may be obscured. This could lead to incorrect conclusions.

Original languageEnglish (US)
Pages (from-to)364-374
Number of pages11
JournalJournal of Family Psychology
Volume30
Issue number3
DOIs
StatePublished - Apr 1 2016

Keywords

  • Father involvement
  • Measurement invariance
  • Multiple-groups analysis
  • Structural equation modeling

ASJC Scopus subject areas

  • Psychology(all)

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