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Causal Inference Using Stata: Estimating Average Treatment Effects

June 21 : 18:00 - June 25 : 22:00 CEST

$1295
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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 parameters estimated, 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

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Course topics

  • Double-robustness property of the augmented IPW and IPW regression-adjustment estimators
  • Using different functional forms for outcome model and treatment model
  • Multivalued treatments
  • Estimators when the treatment is endogenous

The discussion of estimators that handle an endogenously assigned treatment includes extended regression model (ERM) estimators.

  • The potential-outcome framework, the average treatment effect, and the average treatment effect on the treated
  • Observational data differ from experimental data
  • Six estimators:
    • Regression-adjustment estimator
    • Inverse-probability-weighted (IPW) estimator
    • Augmented IPW estimator
    • IPW regression-adjustment estimator
    • Nearest-neighbor matching estimator
    • Propensity-score matching estimator
  • Endogenous treatment effects within the potential-outcome framework
  • The double-robustness property of the augmented IPW and IPW regression-adjustment estimators
  • Using different functional forms for outcome model and treatment model
  • Multivalued treatments
  • Extended regression models that allow the combination of endogenous treatment with endogenous sample selection and endogenous covariates

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

Prerequisites

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

Dates and Time

  • June 21-25, 2021
  • 18:00 – 22:00 CET (6 – 10 PM CET) (5 – 9 PM UK/GMT)

Click here to Enroll

Details

Start:
June 21 : 18:00 CEST
End:
June 25 : 22:00 CEST
Cost:
$1295
Event Category:

Venue

Online

Organizer

StataCorp LLC
View Organizer Website

Event Conditions

Course registration is binding. Upon cancellation more than 8 working days before the course start date, we invoice 50% of the course fee. Upon cancellation less than 8 working days before the course start date, we invoice the full course fee. Click here to read the full Terms and Conditions!