Still Comparing Apples With Oranges?

Abstract

Measurement invariance testing has become an integral part of the methodological repertoire in psychological assessment.Whenever researchers attempt to compare scales or test scores across groups or over time, it needs to be ensured that they do not compare "apples with oranges."Measurement invariance testing is the road that leads to the information about whether the comparisons of means or variances are valid.In other words, invariance testing examines the between-group or between-time points variation in factor means and variances by ruling out differences in measurement (Bauer, 2017).This ensures the fairness of scales or tests and therefore contributes to crafting a validity argument (Kane, 2013).In this editorial, we briefly review some of the principles and practices of measurement invariance testing in psychological assessment contexts and encourage EJPA authors to critically review the limitations of the commonly used approach to invariance testingmulti-group confirmatory factor analysis.We suggest considering alternatives to this approach, for instance, when submitting to EJPA and we discuss the potential of these alternative approaches.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 76 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.