Latent Class Growth Modelling: A Tutorial

By Heather Andruff, Natasha Carraro, A. Thompson, Patrick Gaudreau, B. Louvet. 2009

631 citations recorded by the source corpus.

The present work is an introduction to Latent Class Growth Modelling (LCGM). LCGM is a semi‐parametric statistical technique used to analyze longitudinal data. It is used when the data follows a pattern of change in which both the strength and the direction of the relationship between the independent and dependent variables differ across cases. The analysis identifies distinct subgroups of individuals following a distinct pattern of change over age or time on a variable of interest. The aim of the present tutorial is to introduce readers to LCGM and provide a concrete example of how the analysis can be performed using a real‐world data set and the SAS software package with accompanying PROC TRAJ application. The advantages and limitations of this technique are also discussed.

Subfields: Education, Experimental and Cognitive Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/4591833f7f058408f0587f83ea5e9efbe7586f78

Citations in the corpus

• Reciprocal effects of psychological contract breach on counterproductive and organizational citizenship behaviors: The role of time (2018, neutral): “To interpret the indirect relationships, we estimating a full mediation SEM and a partial mediation SEM and compared them using the 2Log Likelihood (-2LL) difference test (Hayes, 2006) to assess which of these models had a better fit to the data.”