Latent class analysis (LCA) is a widely used technique for detecting unobserved population heterogeneity in cross-sectional data. Despite its popularity, the performance of LCA is not well understood. In this study, we evaluate the performance of LCA with binary data by examining classification accuracy, parameter estimation accuracy, and coverage…

Cluster sampling results in response variable variation both among respondents (i.e., within-cluster or Level 1) and among clusters (i.e., between-cluster or Level 2). Properly modeling within- and between-cluster variation could be of substantive interest in numerous settings, but applied researchers typically test only within-cluster (i.e.,…

Both structural equation models and hierarchical linear models (HLMs) have been commonly used in multilevel analysis. This study utilized simulated data to investigate the power difference among 3 multilevel models: HLM, deviation structural equation models, and a hybrid approach of HLM and structural equation models. Two factors were examined:…