Description: This course introduces public health Master's students to generalized linear models to analyze binary, discrete, ordinal, count, survival outcomes.The primary emphasis will be interpretation, inference and hands-on data analyses. We will use R to analyze public health datasets, evaluate regression assumptions, and assess model fit.
Learning Objectives: 1. Understand the context where non-continuous outcome data are generated, identify the most relevant aspects of these data that require modeling and formulate a scientific question in terms of one or a few model parameters
2. To develop the ability to use R to analyze public health data using GLM
3. Interpret results of data analysis for public health research, policy or practice