Applied Regression Models for Categorical Data

Catalog description

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.