CAUSAL INFERENCE IN MEDICINE AND PUBLIC HEALTH II Syllabus
Course Learning Objectives
Upon successfully completing this course, students will be able to:
- describe causal problems as potential interventions, through the framework of potential outcomes and assignment mechanisms
- discuss the role of designs and of different modes of statistical inference
- implement efficient (likelihood) methods with ignorable assignment of treatments,
- describe the role of outcome models and of propensity score models
- Assess when and how comparisons of longitudinal treatments can be designed as having sequentially ignorable assignment, and learn ways to estimate their causal effects
- Master efficient methods for estimating effects in studies with noncompliance to treatment, direct and indirect effects, and censoring by death
Presents principles, methods, and applications in drawing cause-effect inferences with a focus on the health sciences. Building on the basis of 140.664, emphasizes statistical theory and design and addresses complications and extensions, aiming at cultivating students’ research skills in this area. Includes: detailed role of design for causal inference; role of models and likelihood perspective for ignorable treatment assignment; estimation of noncollapsible causal effects; statistical theory of propensity scores; use of propensity scores for estimating effect modification and for comparing multiple treatments while addressing regression to the mean; theory and methods of evaluating longitudinal treatments, including the role of sequentially ignorable designs and propensity scores; likelihood theory for instrumental variables and principal stratification designs and methods to deal with treatment noncompliance, direct and indirect effects, and censoring by death.
Students from across the university
Methods of Assessment
Grading Policy: Student evaluation based on problem sets and a final project.
Grading Restrictions: Letter grade
140.654 or equivalent for matrix representation of multiple linear and logistic regression
Academic Ethics Code
The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:
Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.
Disability Support Services
If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services: email@example.com, 410-955-3034, or 2017 E. Monument Street.