Stata's causal-inference suite allows you to estimate experimental-type causal effects from observational data. Whether you are interested in a continuous, binary, count, fractional, or survival outcome; whether you are modeling the outcome process or treatment process; Stata can estimate your treatment effect. With the most comprehensive set of causal-inference estimators available in any software package, you will find the one that's right for you.
Learn about causal inference and causal-inference analysis.
See Difference-in-differences (DID) and DDD models.
See Heterogeneous difference in differences (DID).
See Treatment-effects lasso estimation.
Endogeneity, Heckman-style selection, and panel data with causal effects
Difference-in-differences (DID) and triple-differences (DDD)
Treatment effects with high-dimensional controls
Watch A tour of treatment effects.
Watch Introduction to treatment effects, part 1.
Watch Introduction to treatment effects, part 2.
See New in Stata 18 to learn about what was added in Stata 18.