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.



Average treatment effects (ATEs)

ATEs on the treated (ATETs)

Potential-outcome means (POMs)




Binary—logistic, probit, heteroskedastic probit



Non-negative, including exponential mean

Survival—exponential, Weibull, gamma, lognormal

Watch Treatment effects for survival models in Stata.



Binary—logistic, probit, heteroskedastic probit

Multivalued-multinomial logistic



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.


dialog box for teffects


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