Course Title: Applied Longitudinal Analysis
Course ID: BST226 (Full Term Course)
Topics to be covered:
This course covers modern methods for the analysis of longitudinal data, including the unbalanced and incomplete data characteristic of biomedical research. Topics include an introduction to the analysis of longitudinal data, the analysis of response profiles, fitting parametric curves, covariance pattern models, random effects and growth curve models, generalized linear models for longitudinal data including generalized estimating equations (GEE), and generalized linear mixed models (GLMMs). The course will also discuss connections to smoothing and multi-level modeling, and methods for handling missing data and dropout.
Prerequisites: BST210 or BST213 or BST 232 or BST260 or PHS2000A
Prior math/stat knowledge: Ask the course instructor
Computing: SAS will be used in lecture and lab sessions.