Categorical Data Analysis for Epidemiologic Studies
- Course Number
- CHL5407H
- Series
- 5400 (Epidemiology)
- Format
- Tutorials
- Course Instructor(s)
- Catharine Chambers, Jesse T. Young
Course Description
This course is designed to introduce epidemiology students with some background in basic statistical analysis to the principals and methods of categorical data analysis relevant to epidemiological studies, with an emphasis on application and interpretation.
Course Objectives
At the end of this course students should:
- Be able to identify and obtain several types of categorical data;
- Be able to enter/import categorical data into a SAS statistical computer package and prepare the data for analysis;
- Know how to model binary outcomes using logistic regression and log-binomial regression and correctly interpret the results;
- Be able to apply statistical regression models and interpret results from nominal and ordinal outcome data;
- Recognize count data and be able to appropriately analyze it using several different regression strategies;
- Recognize matched, correlated, and clustered categorical data and know how to analyze appropriately;
- Be able to develop a research question and associated analytic plan;
- Be able to effectively communicate findings from analyses using categorical epidemiological data.
Methods of Assessment
| Assignment 1: Introduction to categorical data | 10% |
| Assignment 2: Binary models and multi-category logit models | 10% |
| Assignment 3: Alternatives to logistic and Count data | 10% |
| Midterm test | 15% |
| Final test | 15% |
| Final Data Analysis Assignment (including presentation) | 40% |