Longitudinal Design and Data Analysis

This course is a survey of growth modeling methods useful for study of developmental and change processes. General areas to be covered include conceptualization and organization of longitudinal panel data, linear growth modeling, inclusion of time-invariant and time-varying covariates, nonlinear growth models (including a variety of exponential, sigmoid and spline models), multiple-group models, and growth mixture models. Students will work through application/implementation of the models through hands-on analysis of simulated and empirical data in both structural equation modeling (SEM) and multilevel modeling (MLM) frameworks, acquire experiences in the formulation of research questions and study designs that are appropriately tethered to the different theoretical perspectives invoked by the different models.