Latent class analysis (LCA) is a statistical method used to group individuals (cases, units)
into classes (categories) of an unobserved (latent) variable on the basis of the responses …

ABSTRACT A first application of multilevel latent class analysis (MLCA) to educational large-
scale assessment data is demonstrated. This statistical technique addresses several of the …

Latent class analysis (LCA) is a statistical method used to identify unobserved subgroups in
a population with a chosen set of indicators. Given the increasing popularity of LCA, our aim …

Latent class analysis is an analytic technique often used in educational and psychological
research to identify meaningful groups of individuals within a larger heterogeneous …

Latent class (LC) analysis is used by social, behavioral, and medical science researchers
among others as a tool for clustering (or unsupervised classification) with categorical …

Filled with well-chosen empirical examples to teach the technique, this book provides a
thorough guide to latent class scaling models for binary response variables. Substantive …

The LCA Stata Plugin was developed for Stata for Windows (version 11.0 or higher). The
plugin allows Stata users to employ the same functionality in the SAS procedure PROC LCA …

This chapter gives an applied introduction to latent profile and latent class analysis
(LPA/LCA). LPA/LCA are model-based methods for clustering individuals in unobserved …

This study investigated the performance of three selected approaches to estimating a two-
phase mixture model, where the first phase was a two-class latent class analysis model and …

A statistical model can be called a latent class (LC) or mixture model if it assumes that some
of its parameters differ across unobserved subgroups, LCs, or mixture components. This …