Advanced Regression for Correlated Data

3 credits · Graduate School

This course is the second in a two-course series on advanced regression analysis that extends linear and generalized linear models to the analysis of dependent (specifically, longitudinal) data. Parametric (generalized least squares, likelihood-based mixed-effects models) and semi-parametric (generalized estimating equations) regression-based methods are central to the course. Advanced topics include transition models, marginalized models, missing data, and joint models for longitudinal and survival data. Emphasis is placed on the theoretical framework for longitudinal data analysis, the statistical properties of longitudinal data analysis methods, and their development and application to modern biomedical research. Prerequisites: BIOS 7345. Spring [3]. French.