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Estimating Average Treatment Effects Using Stata


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:

  1. regression-adjustment estimator
  2. inverse-probability-weighted (IPW) estimator
  3. augmented IPW estimator
  4. IPW regression-adjustment estimator
  5. nearest-neighbor matching estimator
  6. propensity-score matching estimator

The course also discusses

All topics are discussed using a combination of math and Stata examples.

Price: $1,295  

We offer a 15% discount for group enrollments of three or more participants.

Course topics


A general familiarity with Stata and a graduate-level course in regression analysis or comparable experience.

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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.





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