CAUSAL INFERENCE IN MEDICINE AND PUBLIC HEALTH I Syllabus
Course Learning Objectives
Upon successfully completing this course, students will be able to:
- Discuss causal problems as potential interventions, through the framework of potential outcomes and assignment mechanisms,
- Describe the spectrum of designs for both randomized and non-randomized studies,
- Identify the situations for which non-randomized designs are most appropriate,
- apply methods for estimating causal effects, including propensity score techniques, instrumental variables (“encouragement designs”), and regression discontinuity
- critically review research that claims to estimate causal effects with non-experimental data
- discuss complications encountered in causal studies, including missing data, noncompliance, and hidden bias
Course DescriptionPresents 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. Methods are motivated by examples from the health sciences, particularly mental health and community or school-level interventions.
Intended AudienceStudents from across the university
Methods of Assessment60% of 4 homeworks, 30% project, 10% class participation
Prerequisites140.621-624 or 140.651-654, or consent of the instructor
Please see the course Session for a full list of dates and items for this course.
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