HST 194
Clinical Epidemiology

Term: Spring

Course Director(s): Miguel Hernan
M 1-4pm (Meets 6 sessions, January-February 2019; 1/7, 1/14, 1/28, 2/4, 2/11, 2/25)
HMS: MEC 250
Course Website:
Intermediate Biostatistics; Permission of Instructor
MIT students should register under HST.S16 (IAP 2017 only) 1st half of term
MIT Units:
1-0-1 [P/D/F] (G-Level Credit)
Harvard Units:
Clinical research is used to describe, predict, and make causal inferences. This course introduces the methods for the generation, analysis, and interpretation of data for clinical research. Major topics include the design of surveys, predictive models, randomized trials, clinical cohorts, and analyses of electronic health records. Students will learn to formulate well-defined research questions, to design data collection, to evaluate algorithms for clinical prediction, to design studies for causal inference, and to identify and prevent biases in clinical research. Familiarity with regression modeling and basic statistical theory is a pre-requisite. The course emphasizes critical thinking and practical applications, including daily assignments based on articles published in major clinical journals and the discussion of a case study each week. A key goal of the course is training students to comprehend, critique, and communicate findings from the biomedical literature.