The increasing accessibility of large-scale international surveys has provided new opportunities for social scientists to conduct comparative research. Such studies frequently examine relations between latent constructs (e.g., how perceived economic threat affects political ideology) and compare them across groups (e.g., countries) to reveal cultural variations in value priorities, attitudes...
The recently proposed Mixture Multigroup Structural Equation Modeling (MMG-SEM) efficiently compares groups by clustering them based on their structural relations while accounting for the reality of measurement (non-)invariance. Currently, MMG-SEM relies on maximum likelihood (ML), which assumes continuous and normally distributed observed indicators. However, this can introduce bias when...
In the social sciences, a common research objective is the comparison of latent variables among different groups, such as in cross-cultural studies. For making valid comparisons measurement invariance (MI) is required, which implies that constructs are measured consistently across populations. When dealing with many groups, MI often does not hold, requiring pairwise comparisons between the...
Comparing relations between latent constructs across groups is essential for understanding social phenomena in different contexts. A key assumption for valid comparisons of such relations is that the constructs are measured equivalently across the groups, referred to as “measurement invariance”. Specifically, partial metric invariance is sufficient –meaning that at least some factor loadings...
Structural equation modelling (SEM) is the state-of-the-art method for analysing relations between latent variables (e.g., attitudes or behaviours), also called ‘factors’. SEM consists of a measurement model (MM), which specifies how questionnaire items measure the factors, and a structural model (SM), which captures the relations of interests. Traditionally, SEM estimates the MM and the SM...
Researchers often use vector autoregressive models to study dynamic processes of latent variables in daily life, such as the extent to which positive and negative affect carry over and interact with each other from one moment to the next. Mixture modeling allows finding clusters of individuals that are similar to each other in their dynamic processes. However, applying MMG-SEM to vector...
