Subject: Biostatistics
Course Number: 215
Course Title: Strengthening causal inferences based on observational data
Units: 3
School: Graduate Division
Department: Clinical Research Program

Course Description: The course will define causal effects in terms of potential outcomes, show when standard regression methods do and do not support causal inferences, and show how to estimate and interpret marginal and conditional causal effects. It will also cover propensity scores, inverse probability weighting, marginal structural models (for time-dependent treatments with time-dependent confounder/mediators), mediation analysis, new-user designs, instrumental variables, and principal stratification.
Prerequisites: EPIDEMIOL 203, BIOSTAT 208, and BIOSTAT 209 (may be enrolled concurrently). Exceptions to these prerequisites may be made with the consent of the Course Director, space permitting.
Restrictions: This course is part of the Training in Clinical Research (TICR) Program and may have space limitations. Auditing is not permitted.
Activities: Direct - Lecture, Direct - Lab-Skills, Direct - Discussion, Student - Lecture, Student - Lab-Skills, Student - Discussion

Instructor of Record: T. Newman
May the student choose the instructor for this course? No
Does enrollment in this course require instructor approval? No

Quarter(s) Offered: Spring
Course Grading Convention: Letter Grade, P/NP (Pass/Not Pass) or S/U (Satisfactory/Unsatisfactory)
Graduate Division course: Yes
Is this a web-based online course? No
Is this an Interprofessional Education (IPE) course? No
May students in the Graduate Division (i.e. pursuing Master or PhD) enroll in this course? Yes
Repeat course for credit? No