Categorical Data Analysis

Description: This course presents the theory and applications of categorical data analysis. Topics include analysis of contingency tables, the logistic regression model, model building strategies, assessing model fit, conditional logistic regression for matched data, multinomial and ordinal logistic regression, and Poisson regression.

Textbook: An Introduction to Categorical Data Analysis, 3rd edition Alan Agresti

Materials:  

• Distribution Theory and Hypothesis Testing for Categorical Random Variables

• Contingency Tables

• Generalized Linear Models

• Logistic Regression

• Model Selection and Goodness of Fit

• Multinomial Logistic Regression

• Ordinal Logistic Regression

• Random Effects Model and Machine Learning