Bayesian tests of measurement invariance

Josine Verhagen, Gerardus J.A. Fox

    Research output: Contribution to journalArticleAcademicpeer-review

    42 Citations (Scopus)
    7 Downloads (Pure)


    Random item effects models provide a natural framework for the exploration of violations of measurement invariance without the need for anchor items. Within the random item effects modelling framework, Bayesian tests (Bayes factor, deviance information criterion) are proposed which enable multiple marginal invariance hypotheses to be tested simultaneously. The performance of the tests is evaluated with a simulation study which shows that the tests have high power and low Type I error rate. Data from the European Social Survey are used to test for measurement invariance of attitude towards immigrant items and to show that background information can be used to explain cross-national variation in item functioning.
    Original languageEnglish
    Pages (from-to)383-401
    JournalBritish journal of mathematical and statistical psychology
    Issue number3
    Publication statusPublished - 5 Oct 2013


    • METIS-291405
    • IR-83847


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