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Treatment effects

Estimators

  • Regression adjustment
    • Continuous, binary, count, or nonnegative outcome
    • Linear, logistic, probit, heteroskedastic probit, or exponential outcome model
    • Multivalued treatment
  • Inverse-probability weighting (IPW)
    • Continuous, binary, count, fractional, or nonnegative outcome
    • Multivalued treatment
    • Logistic, probit, heteroskedastic probit, or multinomial logistic treatment model
  • Doubly robust estimators
    • IPW with regression adjustment
      • Continuous, binary, count, or nonnegative outcome
      • Linear, logistic, probit, heteroskedastic probit, or exponential outcome model
      • Multivalued treatment
      • Logistic, probit, heteroskedastic probit, or multinomial logistic treatment model
    • Augmented IPW
      • Continuous, binary, count, or nonnegative outcome
      • Linear, logistic, probit, heteroskedastic probit, or exponential outcome model
      • Multivalued treatment
      • Logistic, probit, heteroskedastic probit, or multinomial logistic treatment model
  • Propensity-score matching
    • Continuous, binary, count, fractional, or nonnegative outcome
    • Binary treatment
    • Logistic, probit, or heteroskedastic probit treatment model
  • Covariate matching
    • Continuous, binary, count, fractional, or nonnegative outcome
    • Binary treatment

Statistics

  • Average treatment effects (ATEs)
  • ATEs on the treated (ATETs)
  • Potential-outcome means (POMs)

Diagnostics

Survival-time estimators New

  • Regression adjustment
    • Weibull, exponential, gamma, lognormal outcomes
    • Binary and multivalued treatments
  • Inverse-probability weighting (IPW)
    • Weibull, exponential, gamma, lognormal outcomes
    • Logistic, probit, heteroskedastic probit, or multinomial logistic treatment model
    • Binary and multivalued treatments
  • IPW with regression adjustment
    • Weibull, exponential, gamma, lognormal outcomes
    • Logistic, probit, or heteroskedastic probit treatment model
    • Weibull, exponential, gamma, or lognormal censoring model
    • Binary and multivalued treatments
  • Weighted regression adjustment
    • Weibull, exponential, gamma, lognormal outcomes
    • Weibull, exponential, gamma, or lognormal censoring model
    • Binary and multivalued treatments

Endogenous treatment-effects estimators

  • Continuous outcome Updated
  • Count outcome Updated
  • Binary, fractional, nonnegative outcome New
  • Control-function estimator New
  • Average treatment effects (ATEs)
  • ATEs on the treated (ATETs)
  • Potential-outcome means (POMs)
  • Test for endogeneity

Postestimation Selector New

  • View and run all postestimation features for your command
  • Automatically updated as estimation commands are run

Additional resources

Watch A tour of treatment effects.

See New in Stata 14 for more about what was added in Stata 14.

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