Date of Award
Master of Science
Epidemiology and Biostatistics
Dr. John Koval
A developmental trajectory describes the course of behaviour over time. Iden tifying multiple trajectories within an overall developmental process permits a focus on subgroups of particular interest. This research introduces a SAS macro program that identifies trajectories by using the Expectation-Maximization (EM) algorithm to fit semi-parametric mixtures of logistic distributions to longitudinal binary data. For performance comparison, we consider full maximization algo rithms (e.g. SAS procedure PROC TRAJ) and standard EM, as well as two other EM-based algorithms for speeding up convergence. The simulation study shows that our EM methods produce more accurate parameter estimates than the full maximization methods. The EM-based methodology is illustrated with a longitudinal data set involving adolescents smoking behaviours.
Chu, Man-Kee Maggie, "Application of the EM Algorithm for Mixture Models" (2010). Digitized Theses. 3689.