Applied Regression Models for Categorical Data

EPID 6220
Fall term (first half of term)
0.5 CU
Elective
Prerequisite
EPID 5100 or equivalent and EPID 5260 or equivalent

This course will provide in-depth treatment of several topics in categorical data analysis. We will cover a range of regression models, including logistic regression, multinomial logistic regression, proportional odds model, conditional logistic regression, shrinkage methods in machine learning, classification methods in machine learning, latent class models, interrupted time series, difference in difference, random effects models and generalized estimating equations. Topics will be illustrated in class with examples. Stata will be used for the course.