Here - Tilburg University

Author and presenter
Meuleman, Bart; Catholic University Leuven
Title
When are item intercept differences substantial in measurement equivalence
testing? An application on ESS data.
Abstract
Applied comparative researchers are becoming increasingly aware of the
issue of measurement equivalence. By now, there exists considerable agreement
on the concrete operationalization and implications of (the various levels of)
measurement equivalence. Multiple group confirmatory factor analysis (MGCFA)
has become widely recognized as a useful statistical tool to test for equivalence.
In this framework, measurement equivalence is assessed by constraining certain
parameters – e.g. factor loadings or item intercepts - across groups.
Despite growing consensus, important issues in equivalence testing by
means of MGCFA remain unresolved. One of the most compelling problems
related to the specific criteria that should be used to decide whether an equality
constraint is violated or not. Various authors warn against relying on statistical
criteria alone, because due to the large sample sizes often used, even negligible
differences between groups can become significant. Saris et al. (2009) suggest
that one should only pay attention to substantial model misspecifications (i.e.
with a high expected parameter change).
Yet, how large should differences between groups be to be judged as
substantial? This paper proposes a concrete strategy to predict whether
differences in item intercepts will have perceivable impact on substantial
conclusions drawn from latent mean comparisons. The proposed strategy is
applied using European Social Survey (round 4) data on welfare attitudes.
Key words
Measurement equivalence, MGCFA, European Social Survey