2001 A SAS procedure based on mixture models for estimating developmental trajectories

This article introduces a new SAS procedure written by the authors that analyzes longitu-dinal data (developmental trajectories) by fitting a mixture model. The TRAJ procedure fits semiparametric (discrete) mixtures of censored normal, Poisson, zero-inflated Pois-son, and Bernoulli distributions to longitudinal data. Applications to psychometric scale data, offense counts, and a dichotomous prevalence measure in violence research are il-lustrated. In addition, the use of the Bayesian information criterion to address the prob-lem of model selection, including the estimation of the number of components in the mix-ture, is demonstrated