Generalized Linear Models and Extensions

Catalog description

A second year course in advanced statistical techniques that covers useful quantitative tools in health & policy research. Assuming a strong foundation in regression & the general linear model, this course focuses on data analysis that utilizes models for categorical, discrete or limited outcomes that are commonly seen in health & policy studies. Examples include health status, number of clinic visits, etc. In this course students will also learn the principles of likelihood-based inference, which will assist them in some of the more advanced statistics courses.