Section outline


  • Course Introduction & Conceptual Frameworks for Causal Inference

    Introduction to the course; models/heuristics for causal inference in epidemiology; discussion of counterfactuals and identifiability criteria; ideal randomized experiments; conditional randomization

    Faculty: June Chan, Rebecca Graff

    • Required Reading (please read PRIOR to watching the lectures):

      Chapter 1, Hernán & Robins, Causal Inference Book, online

    • Recommended Reading:

      Chapter 2, Hernán & Robins, Causal Inference Book, online

    • Optional Reading:

      1. Chapter 3, Hernán & Robins, Causal Inference Book, online
      2. Chapter 2, Rothman, Greenland, & Lash, 2008

    • Recorded Lectures (please watch PRIOR to class):

      Access restricted to registered students

    • Intro to EPI 207 W21 revised Media Resource
    • Conceptual Frameworks for Causal Inference - Part 1 Media Resource
    • Conceptual Frameworks for Causal Inference - Part 2 Media Resource
    • Bradford Hill (Optional) Media Resource
    • Sufficient & Component Cause (Optional) Media Resource
    • Session Slides:

    • Two word clouds from first day of class File
    • Session Audio/Video Recording (access restricted to registered students):

    • Class Recording - Week 1 Media Resource
      Not available unless: You belong to a group in Registered Students Only
    • Assignment:

      Due Thursday, January 21, 2021 at the beginning of lecture

    • Article to Read for HW - Jain, et al. JAMA 2015 File
      Not available unless: You belong to Registered Students Only
    • Watch pre-recorded lecture on DAGs

    • Assignment Answer Key (access restricted to registered students):

    • Miscellaneous: