Learn how and when to use Stata’s treatment-effects estimators to analyze treatment effects in observational data. Use regression adjustment, inverse probability weights, doubly robust methods, propensity-score matching, and covariate matching to estimate average treatment effects (ATEs) and ATEs on the treated. We will cover the conceptual and theoretical underpinnings of treatment effects as well as many examples using Stata.
After presenting the potential-outcome framework and discussing the estimated parameters, the course discusses six estimators:
The course also discusses
All topics are discussed using a combination of math and Stata examples.
We offer a 15% discount for group enrollments of three or more participants.
A general familiarity with Stata and a graduate-level course in regression analysis or comparable experience.
Currently, there are no scheduled sessions of this course.
Enrollment is limited. Computers with Stata installed are provided at all public training sessions. All training courses run from 8:30 a.m. to 4:30 p.m. each day. A continental breakfast, lunch, and an afternoon snack will also be provided; the breakfast is available before the course begins.