A SAS procedure based on mixture models for estimating developmental trajectories

This article introduces a new SAS procedure written by the authors that ana lyzes longitudinal data (developmental trajectories by fitting a mixture mo del. The TRAJ procedure fits semiparametric (discrete) mixtures of censored normal, Poisson, zero-inflated Poisson, and Bernoulli distributions to lon gitudinal data. Applications to psychometric scale data, offense counts and a dichotomous prevalence measure in violence research are illustrated In a ddition, the use of the Bayesian information criterion to address the probl em of model selection including the estimation of the number of components in the mixture, is demonstrated.