Latent Class Analysis Essay

Latent class analysis (LCA) uses categorical latent variables to explain associations between categorical observed variables and to examine typological differences between individuals (i.e., differences in kind rather than degree). Individuals with similar response patterns are grouped into the same latent class, whereas there is maximal dissimilarity of individuals between classes. Latent class analysis allows researchers to extract latent classes, but uses continuous variables as latent class indicators (e.g., the scale scores on the Maslach Burnout Inventory). LCA represents a person-centred analysis that groups individuals by similar patterns rather than variable-based approaches that group items (Reinke, Herman, Petras, & Ialongo, 2008).