Contemporary Issues in the Assessment of Measurement Invariance 1 |
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| Coordinator 1 | Dr Daniel Seddig (University of Cologne & University of Zurich) |
| Coordinator 2 | Professor Eldad Davidov (University of Cologne & University of Zurich) |
| Coordinator 3 | Professor Peter Schmidt (University of Giessen) |
The assessment of the comparability of cross-national and longitudinal survey data is a prerequisite for meaningful and valid comparisons of substantive constructs across contexts and time. A powerful tool to test the equivalence of measurements is multiple-group confirmatory factor analysis (MGCFA). Although the procedures of measurement invariance (MI) testing seem to become increasingly used by applied researchers, several issues remain under discussion and are not yet solved. For example:
(1) Can we trust models with small deviations (approximate MI)? Is partial MI sufficient? How should one deal with the lack of scalar MI, as is the case in many large-scale cross-national surveys?
(2) How to decide whether a model with a high level of MI should be preferred over a model with a lower level of MI? Which fit indices should be used?
(3) Is MI needed anyway and would it be best to start firstly with a robustness calculation?
Recent approaches have tackled the issues subsumed under (1) and aimed at relaxing certain requirements when testing for measurement invariance (Bayesian approximate MI, Muthén and Asparouhov 2012; van de Schoot et al 203) or using the alignment method (Asparouhov and Muthén 2014). Furthermore, researchers addressed the issues subsumed under (2) and recommended the use of particular fit statistics (e.g., CFI, RMSEA, SRMR) to decide among competing models (Chen 2007). The question raised under (3) is a more general one and raises concerns about the contemporary uses of the concept of MI. Researchers (Welzel and Inglehart 2016) have argued that variations in measurements across context can be ignored, for example in the presence of theoretically reasonable associations of a construct with external criteria.
This session aims at presenting studies that assess measurement invariance and/or address one of the issues listed above or related ones. 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 and use for example Monte-Carlo simulations to study the above mentioned issues.