Advanced Quantitative Methods in Epidemiology
- Course Number
- CHL5424H
- Series
- 5400 (Epidemiology)
- Format
- Modular
- Course Syllabus
- View Syllabus
- Course Instructor(s)
- Hailey Banack, Brice Batomen Kuimi
Course description
This is an advanced course in epidemiology focused on conceptual knowledge and analytic skills. This course specifically emphasizes causal inference perspectives. Topics covered include methods for longitudinal data analysis, quantitative assessment of interaction and effect modification, missing data, and causal modeling (e.g., marginal structural models, G-methods). Students will gain experience applying the methods presented in class lectures, including data analysis, and interpreting effect estimates.
Previous background in epidemiologic methods is assumed, including familiarity with a statistical analysis software such as Stata, R, or SAS and prior experience conducting quantitative analysis.
Learning Outcomes
- Understand the principles and assumptions of causal inference
- Gain an understanding of the theory and applications of advanced quantitative methods in epidemiology to answer complex etiologic questions;
- Learn how to apply these methods using data and software;
- Be able to critically appraise and interpret research studies that apply these approaches