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.

• Elliott, MR, Ten Have TR, Gallo, J, Bogner, HR Katz, IR (2005). "Use of Latent Class Models to Assist in Diagnoses using Emotional Affect Data," Biostatistics, 6, 119-143.