Course Description
Introduction to analysis of categorical data including log- linear models, logistic regression, probit models, graphical models and casual inference. Motivating examples will be drawn directly from the literature in the health, biological, medical, and social sciences.
Athena Title
CATEGORICAL DATA
Prerequisite
BIOS 7010 or STAT 6210 or STAT 6310
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
At the end of the course, the successful student should be able to do the following: 1. Modeling and inference for contingency table using log- linear models; 2. Using graphical models and related ideas to organize log- linear modeling; 3. Perform logistic regression analyses with multiple predictors; 4. Compare different models with respect to their predictive power; 5. Use graphical and other methods for assessing the adequacy of the fitted model; 6. Interpret each coefficient in the model; 7. Describe the methods and results to a non-statistical reader.
Topical Outline
Analysis of contingency tables; log-linear models; logistic regression; probit model; Goodness-of-fit tests; model selection; zero-inflated counts; graphical models; causal inference