Contemporary issues in measurement invariance research |
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| Coordinator 1 | Dr Daniel Seddig (University of Cologne) |
| Coordinator 2 | Professor Eldad Davidov (University of Cologne and URPP Social Networks, University of Zurich) |
| Coordinator 3 | Professor Peter Schmidt (University of Giessen) |
The assessment of measurement invariance of survey data is a prerequisite for meaningful and valid comparisons of substantive constructs across countries, cultures, and time. A powerful tool to test measurement invariance is multiple-group confirmatory factor analysis. In addition to testing “exact” (full or partial) measurement invariance with the traditional tools, recent methods have aimed at testing “approximate” measurement invariance using Bayesian structural equation modeling or alignment optimization, assessing clustered measurement invariance, using visualization techniques, and separating response shift bias and true change. In addition, many researchers are concerned with paying more attention to survey methodological aspects in order to advance the development of invariant measurements, such as rating scale and survey mode decisions, cognitive pretesting and web probing approaches, and cross-cultural scale adoption and translation methods. Finally, multilevel analysis and qualitative methods have been used to try to explain noninvariance.
This session aims to present studies that address questions such as “How much can we trust the above methods and related methods to test for measurement invariance?" or "What is the need to test for measurement invariance in different situations?”. We welcome (1) presentations that are applied and make use of empirical survey data, and/or that (2) take a methodological approach to address and examine measurement invariance testing.