This repository contains coursework, notes, and Stata code for PBHS 32700 / STAT 22700, a graduate-level course on categorical data analysis and survival analysis offered by the Department of Public Health Sciences at the University of Chicago. The course emphasizes the interpretation and application of statistical methods for binary, count, and time-to-event data using Stata.
- Term: Spring 2024
- Language: Stata
- Instructor: Dr. Lin Chen
This course introduces statistical methods commonly used to analyze categorical and survival data in public health and medical research. Topics include:
- Contingency tables and measures of association
- Logistic regression for binary outcomes
- Ordinal and nominal logistic regression models
- Model building and diagnostics for logistic models
- Poisson and negative binomial regression for count outcomes
- Kaplan-Meier methods for survival analysis
- Cox proportional hazards models
- Parametric survival models (e.g., exponential, Weibull)
- Model interpretation and adjusted estimates
- Use of Stata to conduct biostatistical analyses and interpret results