This repository contains coursework, notes, and Stata code for PBHS 32410 / STAT 22401, a graduate-level course on linear and generalized linear models in public health and social science research. The course emphasizes interpreting and applying statistical models to real-world data using Stata.

• Term: Winter 2024
• Language: Stata
• Instructor: Dr. James J. Dignam

This course introduces regression methods commonly used in the analysis of public health and social science data. Topics include:

• Simple linear regression and correlation
• Multiple linear regression with continuous and categorical predictors
• Interaction terms and effect modification
• Model selection strategies and transformations
• Residual diagnostics, leverage, and influence
• Poisson regression for count outcomes
• Logistic regression for binary outcomes
• Interpretation of adjusted estimates
• Application of generalized linear models (GLMs)
• Use of Stata to conduct regression analyses and interpret model output