ADVANCED REGRESSION METHODS FOR POPULATION HEALTH

Prerequisites & course information

Requisites: POP HLTH/B M I 552 Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2025 Learning Outcomes: 1. Extend the knowledge of regression analysis beyond ordinary linear models Audience: Graduate 2. Describe the features of correlated data and their implications in drawing inference Audience: Graduate 3. Construct proper linear and generalized linear models for longitudinal and clustered data Audience: Graduate 4. Describe the assumptions needed for estimation and inference Audience: Graduate 5. Implement the inference procedures to solve real-world problems using statistical packages such as SAS and R Audience: Graduate 6. Use diagnostic tools to assess model fit Audience: Graduate 7. Interpret and present the analytic results to answer substantive questions Audience: Graduate Learning Outcomes: 1. Extend the knowledge of regression analysis beyond ordinary linear models Audience: Graduate 2. Describe the features of correlated data and their implications in drawing inference Audience: Graduate 3. Construct proper linear and generalized linear models for longitudinal and clustered data Audience: Graduate 4. Describe the assumptions needed for estimation and inference Audience: Graduate 5. Implement the inference procedures to solve real-world problems using statistical packages such as SAS and R Audience: Graduate 6. Use diagnostic tools to assess model fit Audience: Graduate 7. Interpret and present the analytic results to answer substantive questions Audience: Graduate