140.666.11 | AY 2013-2014 - Summer Inst. Term | 1 Credit(s)
M 8:30:00 AM
  • Contact Information
  • Course Learning Objectives
    Upon successful completion of this course, students will: 1) Understand causal problems as potential interventions, through the framework of potential outcomes and assignment mechanisms; 2) Understand the general role of designs and of different modes of statistical inference; 3) Identify the role of such inferences in studies with experimental treatment assignment; 4) Understand ignorable assignment of treatments, and learn ways to estimate their causal effects; understand the role of outcome models and of propensity score models; 5) Understand which observational studies can be viewed as having sequentially ignorable assignment of treatments, and learn ways to estimate their causal effects; 6) Be introduced to studies with noncompliance to treatment, and the method of instrumental variables for estimating causal effects; 7) Be introduced to more general examples of studies where the treatments can be viewed as only partially controlled; understand the implications on what are meaningful treatment effects, on design and estimation.
  • Course Description

    Provides a non-technical overview of causal DAGs theory, its relation to counterfactual theory, and its applications to causal inference. Describe how causal DAGs can be used to propose a systematic classification of biases in observational and randomized studies. Presents practical applications of causal DAGs theory to examples taken from various research areas in epidemiology, including cancer, pregnancy outcomes, and HIV/AIDS. Also describes the bias induced by the use of conventional statistical methods for the analysis of longitudinal studies with time-varying exposures.

  • Intended Audience

    Summer institute participants and JHSPH Students

  • Methods of Assessment

    Grading Policy: Method of student evaluation based on problem sets

    Grading Restrictions: Pass and Fail

  • Prerequisites

    Previous courses in introductory statistical methods.

  • 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:, 410-955-3034, or 2017 E. Monument Street.