Generalized Linear Models with Applications

SPH BS 853

This course introduces statistical models for the analysis of quantitative and qualitative data, of the types usually encountered in health science research. The statistical models discussed include: Logistic regression for binary and binomial data, Nominal and Ordinal Multinomial logistic regression for multinomial data, Poisson regression for count data, and Gamma regression for data with constant coefficient of variation. All of these models are covered as special cases of the Generalized Linear Statistical Model, which provides an overarching statistical framework for these models. We will also introduce Generalized Estimating Equations (GEE) as an extension to the generalized models to the case of repeated measures data. The course emphasizes practical applications, making extensive use of SAS for data analysis.

SPRG 2016 Schedule

Section Instructor Location Schedule Notes
A1 Doros L 1110 T 2:00 pm-5:00 pm Prereqs: MPH
Biostats & Epi
core courses &
BS805
or consent
MED Campus
Class Closed

Note that this information may change at any time. Please visit the Student Link for the most up-to-date course information.