Description: This course introduces students to modern causal inference concepts applied to epidemiology, primarily based on the potential outcomes paradigm
Learning Objectives: This course will help students:
1) Recognize the evolution of causal thinking in epidemiology.
2) Become familiar with concepts involving individual vs. average causal effects, counterfactuals, and causal contrasts.
3) Learn the assumptions required to identify causal effects.
4) Formulate causal questions using causal diagrams.
5) Understand sources and effects of bias including confounding, selection, misclassification within a potential outcomes frame.
6) Appreciate the principles underlying approaches to management of bias at the level of data analysis through G methods, including inverse probability weighting.
In addition, the course addresses a CEPH-required foundational learning objective:
• Explain the role of quantitative and qualitative methods and sciences in describing and assessing a population’s health.
