BIOE 862 - Advanced Categorical Data Techniques

Cr Hrs: 3 (48-0)

This course begins by examining the sampling models and the associated distributions that are most closely identified with categorical data. Next are reviewed the most common chi-square tests and measure of association for standard contingency tables or sets of stratified contingency tables. The generalized linear model is introduced as the backbone for building models that focus on the estimation of effects, model inference, and model checking. Specific topics for the modeling of categorical data include logistic regression for dichotomous and polytomous response, conditional logistic regression, generalized estimating equations, and generalized linear mixed modeling for models with random effects. In addition, the course will explore loglinear modeling for count data and life estimation and Cox proportional hazards model for categorized time to event data. The relation of the various approaches and procedures using SAS will be demonstrated. The course focuses on application of the above approaches to observational and clinical trial data sets.
Grade Mode: Standard
Instructional Method: Lecture-based
Prerequisites: BIOE 812 Fundamentals of Epidemiology; BIOE 821 Biostatistics for the Health Sciences II, or by permission from instructor
Term offered: Spring

Instructor of Record, Spring: Mehmet Kocak