An Introduction to Causal Inference is a 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 with the instructors.
Instructors: Miguel Hernán, Judith Lok, James Robins, Eric Tchetgen Tchetgen & Tyler VanderWeele
To register, please use this link
Tuition: $600 per person, to be paid at the time of registration. This course is non-degree and non-credit. A limited number of tuition waivers are available for students. To apply, please send your CV and a brief statement of interest (half page) to Ellen Furxhi by April 5.
Prerequisites: Participants are expected to be familiar with basic concepts in epidemiology and biostatistics, including linear and logistic regression and survival analysis techniques.
Venue and logistics: The course will be offered 9am-12pm and 1:30pm-4:30pm at Kresge Auditorium, Room G1, Harvard T.H. Chan School of Public Health
