Using a Multilevel Structural Equation Modeling Approach to Explain Cross-Cultural Measurement Noninvariance

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Value Orientations From the World Values Survey (2016, background): “(2012), however, showed how once the source of non-invariance is correctly diagnosed, a multilevel structural equation model (MLSEM) can combine the original measurement model with an explanatory portion, with the omitted variable serving as an explanatory variable (Davidov et al., 2012).”
On Detecting Systematic Measurement Error in Cross-Cultural Research: A Review and Critical Reflection on Equivalence and Invariance Tests (2018, background): “cultures, which external variables predict differences in item biases, and which cultural variables predict differences in loadings or intercepts (Davidov et al., 2012).”
Testing for Approximate Measurement Invariance of Human Values in the European Social Survey (2018, unknown): “Indeed, both methodological and substantive reasons could affect the item functioning of specific items differently across countries and time points (Davidov et al. 2012, 2018).”
Measurement Invariance Testing with Many Groups: A Comparison of Five Approaches (2017, methodology): “We generated approximate MI instead of exact MI because exact invariance across a large number of groups is less realistic for intercepts, especially in cross-cultural studies (Davidov et al., 2012; Desa, 2014; Nagengast & Marsh, 2013; Rutkowski & Svetina, 2014).”