Stata 14 adds to its existing models of treatment effects by introducing new command stteffects which, like the existing teffects allows the users to estimate average treatment effects (ATEs), average treatment effects on the treated (ATETs), and potential-outcome means (POMs) but also allows users to model a combination of the outcome, treatment assignment and censoring. Further, stteffects also offers the options of estimating treatment effects by inverse probability weighting (IPW) through stteffects ipw, different regression-adjustment methods through stteffects ra through stteffects wra and stteffects ipwra allows a choice between two doubly robust estimators.

Stata 14 allows users to deal with endogenous treatments where the treatment assignment is correlated with the outcome through the new command eteffects which estimates ATEs, ATETs and POMs for continuous, count and binary outcomes.

Read more about the new features of treatment effects in more than 163 new pages in the Stata Treatment-Effects Reference Manual.

A selected list of available estimators and features in Stata 14 for Treatment Effects:

Available Estimators Available Features
Inverse probability weighting (IPW) Overidentification test
Regression adjustment Diagnostic summary statistics by group
Weighted regression adjustment Diagnostic plots
IPW with regression adjustment Probability weights for many commands
Endogenous treatment effects etregress estimates a potential-outcome model
etregress allows estimation using
a control function

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