Over the last decades, large international datasets such as the European Social Survey (ESS), the European Value Study (EVS) and the World Value Survey (WVS) have been collected to compare value means over multiple time points and across many countries. Yet analyzing comparative survey data requires the fulfillment of specific assumptions, i.e., that these values are comparable over time and across countries. Given the large number of groups that can be compared in repeated cross-national datasets, establishing measurement invariance has been, however, considered unrealistic. Indeed, studies which did assess it often failed to establish higher levels of invariance such as scalar invariance. In this paper we first introduce the newly developed approximate approach based on Bayesian structural equation modeling (BSEM) to assess cross-group invariance over countries and time points and contrast the findings with the results from the traditional exact measurement invariance test. BSEM examines whether measurement parameters are approximately (rather than exactly) invariant. We apply BSEM to a subset of items measuring the universalism value from the Portrait Values Questionnaire (PVQ) in the ESS. The invariance of this value is tested simultaneously across 15 ESS countries over six ESS rounds with 173,071 respondents and 90 groups in total. Whereas, the use of the traditional approach only legitimates the comparison of latent means of 37 groups, the Bayesian procedure allows the latent mean comparison of 73 groups. Thus, our empirical application demonstrates for the first time the BSEM test procedure on a particularly large set of groups.
Keywords: Bayesian estimation; European Social Survey; Portrait Value Questionnaire; approximate vs. exact measurement invariance; cross-national research; repeated cross-sections; universalism.