Bayesian Generalized Growth Mixture Models

Latent class analysis attempts data reduction by classifying subjects into one of K unobserved classes based on observed data, where K is fixed and known. Observed data for latent class models have traditionally corresponded to cross-sectional observed measurements (Clogg 1985). More recently, latent class models have recently been extended to accommodate longitudinally observed data Muthen and Shedden 1999). We extend these approaches in a Bayesian framework to accommodate trajectories of both continuous and discrete data.

R code used to conduct the 4-class analysis in the manuscript (USE AT YOUR OWN RISK!!!)