Estimators
Inverse-probability weights (IPW)
Propensity-score matching
Covariate matching
Regression adjustment
Weighted regression
Doubly robust methods
Augmented IPW (AIPW)
IPW with regression adjustment
Watch Regression adjustment (RA).
Watch Inverse-probability weighting.
Watch Inverse-probability weights (IPW) with RA.
Watch Augmented IPW.
Watch Nearest-neighbor matching.
Watch Propensity-score matching.
Endogeneity and Heckman-style selection with treatment effects
Linear regression
Interval regression, including tobit
Probit regression
Ordered probit regression
Exogenous or endogenous regressors
Endogenous or exogenous treatment; binary or ordinal treatment
Learn about Extended regression models.
Statistics
Average treatment effects (ATEs)
ATEs on the treated (ATETs)
Potential-outcome means (POMs)
Outcomes
Continuous—linear
Binary—logistic, probit, heteroskedastic probit
Count—Poisson
Fractional
Non-negative, including exponential mean
Survival—exponential, Weibull, gamma, lognormal
Watch Treatment effects for survival models in Stata.
Treatments
Binary—logistic, probit, heteroskedastic probit
Multivalued-multinomial logistic
Diagnostics
Overlap plots
Covariate balance*
Endogenous treatment effects
Continuous outcome
Count outcome
Control-function estimator*
ATEs, ATETs, and POMs
Test for endogeneity
Watch Endogenous treatment effects.
Postestimation selector*
View and run all postestimation features for your command
Automatically updated as estimation commands are run
Watch Postestimation Selector.
Watch A tour of treatment effects.
Watch Introduction to treatment effects, part 1.
Watch Introduction to treatment effects, part 2.
Additional resource
Extended Regression Models Reference Manual
In the spotlight: Double-robust treatment effects (two wrongs don’t make a right, but one does)
In the spotlight: Treatment effects
In the spotlight: eteffects and the challenges of making causal inferences