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Causal Inference in Medicine and Public Health I

3rd Term
Academic Year
2022 - 2023
Instruction Method
Synchronous Online
Class Time(s)
Tu, Th, 10:30 - 11:50am
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Elizabeth Stuart
Contact Email
Frequency Schedule
Every Year

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
Jointly Offered With
Special Comments

Please note: This is the virtual/online section of a course that is also offered onsite. Students will need to commit to the modality for which they register.