This course is designed to provide students with an understanding of the statistical methods used in categorical data analysis. These include traditional methods for two-way contingency tables (e.g. Chi-squared test, Fisher’s exact test). The majority of the course, however, will focus on regression models, with a particular emphasis on logistic regression models. Analysis of repeated categorical response data, namely marginal and random effects models will also be covered. Inference using maximum likelihood estimation will be emphasized. Both application and theory will be covered.
This is a graduate level course for students of biostatistics, epidemiology and statistics. The objective of the course is to provide students with a working knowledge of the core methods involved in the analysis of categorical response variables.
This is a graduate-level course with the following prerequisites. – Statistics at the graduate level or consent of instructor. – Working knowledge of SAS or other equivalent software package is an asset.