Advisory Prerequisites: A previous/concurrent course in intro epidemiology or biostats is strongly recommended (e.g. EPID 701/709). R resources will be available on Canvas before the beginning of the course but prior introductory experience with R is strongly advised.
Undergraduates are allowed to enroll in this course.
Description: This course will provide participants with practical experience in building and interpreting regression models for diverse epidemiological study designs and research questions. We will cover general linear models, including linear, logistic, Poisson, and log-binomial, considering potential confounding and effect measure modification. We will work with real data sets from a variety of application areas.
Learning Objectives: 1. Apply epidemiologic theory and methods to data analysis
2. Select appropriate biostatistical tools for different epidemiologic study designs
3. Employ R programming for epidemiologic data analysis
4. Critically interpret results from epidemiologic studies
