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Causal Inference in Medicine and Public Health I

4th term
4 credits
Academic Year:
2022 - 2023
Instruction Method:
Asynchronous Online
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Elizabeth Stuart

Introduction to Online Learning is required prior to participating in any of the School's Internet-based courses. 140.611-12-13-14-20; or 140.621-624; or 140.651-654; or consent of the instructor


Presents an overview of methods for estimating causal effects: how to answer the question of “What is the effect of A on B?” Includes discussion of randomized designs, but with more emphasis on alternative designs for when randomization is infeasible: matching methods, propensity scores, regression discontinuity, and instrumental variables. Motivates methods by examples from the health sciences, particularly mental health and community or school-level interventions.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Discuss causal problems as potential interventions, through the framework of potential outcomes and assignment mechanisms
  2. Describe the spectrum of designs for both randomized and non-randomized studies
  3. Identify the situations for which non-randomized designs are most appropriate
  4. Apply methods for estimating causal effects, including propensity score techniques, instrumental variables (“encouragement designs”), and regression discontinuity
  5. Critically review research that claims to estimate causal effects with non-experimental data
  6. Discuss complications encountered in causal studies, including missing data, noncompliance, and hidden bias
Methods of Assessment:

This course is evaluated as follows:

  • 60% 3 homework assignments
  • 30% 1 additional homework assignment OR project (student choice)
  • 10% Participation

Instructor Consent:

No consent required

Jointly Offered With: