Finding Clusters of Groups with Measurement Invariance: Unraveling Intercept Non-Invariance with Mixture Multigroup Factor Analysis

Comparisons of latent constructs across groups are ubiquitous in behavioral research and, nowadays, often numerous involved. Measurement invariance the is imperative for valid comparisons and can be tested by multigroup factor analysis. Metric (invariant loadings) holds, whereas scalar intercepts) rarely supported many groups. Scalar a prerequisite comparing means, however. One may inspect group-specific intercepts to pinpoint non-invariances, but this daunting task case This paper presents mixture analysis (MMG-FA) clustering based on their intercepts. Clusters with obtained imposing cluster-specific invariant loadings unique variances, (co)variances differ between Thus, MMG-FA ties down number generates clusters wherein means validly compared.