Epidemiologic Methods II

Catalog description

You’ve probably heard the phrase “correlation doesn’t equal causation”. But if we care about improving population health and health equity, we ultimately need to know what is causing the distributions of disease, disability, and death that we observe in places and over time. A more helpful phrase that will guide this course is: “correlation equals causation under certain assumptions.” This course aims to build upon your existing knowledge of epidemiology by introducing you to a formal, counterfactual approach to causal inference. The goal of this course is for you to understand how theoretical assumptions, formulation of research questions, study design, and statistical analysis determine one’s ability to interpret an association as a causal effect, and what the implications of the causal effects are for public health. Themes of this course are relevant across a range of disciplines, including population health, social and environmental epidemiology, and public health policy.