A Primer to Latent Profile and Latent Class Analysis

This chapter gives an applied introduction to latent profile and class analysis (LPA/LCA). LPA/LCA are model-based methods for clustering individuals in unobserved groups. Their primary goals probing whether and, if so, how many classes can be identified the data estimating their proportional size response profiles. Moreover, membership serve as a predictor or outcome external variables. Substantively, adopt person-centred approach that is useful analysing individual differences learning prerequisites, processes, outcomes. provides conceptual overview of LPA/LCA, nuts-and-bolts discussion steps decisions involved application, illustrative examples using available R statistical environment.