Generalized Linear Models

Catalog description

The class introduces the concept of the exponential family of distributions and link functions, and their use in generalizing the standard linear regression to accommodate various outcome types. The theoretical framework will be presented but detailed practical analyses will be performed as well, including logistic regression and Poisson regression with extensions. The majority of the course will deal with the independent observations framework. However, there will be a substantial discussion of longitudinal/clustered data where correlations within clusters are expected. To deal with such data the Generalized Estimating Equations and the Generalized Linear Mixed models will be introduced. An introduction to a Bayesian analysis approach will be presented, time permitting. Prerequisite(s): BIOSTAT 706/706A or permission of the director of graduate studies. Credits: 3