626 citations · 642 across the 3 of their papers we have counts for
3 papers
Calibrated Percentile Double Bootstrap For Robust Linear Regression Inference
Daniel McCarthy, Kai Zhang, Lawrence Brown +4
We consider inference for the parameters of a linear model when the covariates are random and the relationship between response and covariates is possibly non-linear. Conventional…
Improved Precision in Estimating Average Treatment Effects
Emil Pitkin, Richard Berk, Lawrence Brown +4
The Average Treatment Effect (ATE) is a global measure of the effectiveness of an experimental treatment intervention. Classical methods of its estimation either ignore relevant co…
Valid post-selection inference
Richard Berk, Lawrence Brown, Andreas Buja +2
It is common practice in statistical data analysis to perform data-driven variable selection and derive statistical inference from the resulting model. Such inference enjoys none o…