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

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).