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

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Abstract
Testing for invariance of measurements across groups (such as countries or time points) is essential before meaningful comparisons may be conducted. However, when tested, invariance is often absent. As a result, comparisons across groups are potentially problematic and may be biased. In the current study, we propose utilizing a multilevel structural equation modeling (SEM) approach to provide a framework to explain item bias. We show how variation in a contextual variable may explain noninvariance. For the illustration of the method, we use data from the second round of the European Social Survey (ESS).