Influence functions for linear regression (with an application to regression adjustment)

Ben Jann
Influence functions are useful, for example, because they provide an easy and flexible way to estimate standard errors. This paper contains a brief overview of influence functions in the context of linear regression and illustrates how their empirical counterparts can be computed in Stata, both for unweighted data and for weighted data. Influence functions for regression-adjustment estimators of average treatment effects are also covered.
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.