We’ve received news that Harvard is offering a short course on causal inference that may be of interest to readers of this blog. See the details below for more information:
An Introduction to Causal Inference: This 5-day course introduces concepts and methods for causal inference from observational data. Upon completion of the course, participants will be prepared to further explore the causal inference literature. Topics covered include the g-formula, inverse probability weighting of marginal structural models, g-estimation of structural nested models, causal mediation analysis, and methods to handle unmeasured confounding. The last day will end with a “capstone” open Q&A session.
Instructors: Miguel Hernán, Judith Lok, James Robins, Eric Tchetgen Tchetgen & Tyler VanderWeele
Prerequisites: Participants are expected to be familiar with basic concepts in epidemiology and biostatistics, including linear and logistic regression and survival analysis techniques.
Tuition: $450/person, to be paid at the time of registration. Tuition will be waived for up to 2 students with primary affiliation at an institution in a developing country.
Date/Location: June 12-16, 2017 at the Harvard T.H. Chan School of Public Health
Details and registration: https://www.hsph.harvard.edu/causal/shortcourse/