The Utility of Latent Class Analysis to Understand Heterogeneity in Youth Coping Strategies: A Methodological Introduction

Latent class analysis (LCA) is a useful statistical approach for understanding heterogeneity in a population. This article provides a pedagogical introduction to LCA modeling and provides an example of its use to understand youth's daily coping strategies. The analytic procedures are outlined for choosing the number of classes and integration of the LCA variable within a structural equation model framework, specifically a latent class moderation model, and a detailed table provides a summary of relevant modeling steps. This applied example demonstrates the modeling context when the LCA variable is moderating the association between a covariate and two outcome variables. Results indicate that students' coping strategies moderate the association between social stress and negative mood; however, they do not moderate the social stress-positive mood association. Supplemental Material include R (MplusAutomation) code to automate the enumeration procedure, ML three-step auxiliary variable integration, and the generation of figures for visually depicting LCA results.

Automated summary

Latent class analysis is a statistical method used to understand heterogeneity in a population, and it can be applied in various research fields. This article provides an introduction to LCA modeling and demonstrates its application in understanding youth's coping strategies. The results indicate that students' coping strategies moderate the association between social stress and negative mood.