183 citations · 292 across the 15 of their papers we have counts for
4 papers · 1 filter
Regression-adjusted average treatment effect estimates in stratified randomized experiments
Hanzhong Liu, Yuehan Yang
Researchers often use linear regression to analyse randomized experiments to improve treatment effect estimation by adjusting for imbalances of covariates in the treatment and cont…
Penalized regression adjusted causal effect estimates in high dimensional randomized experiments
Hanzhong Liu, Yuehan Yang
Regression adjustments are often considered by investigators to improve the estimation efficiency of causal effect in randomized experiments when there exists many pre-experiment c…
Lasso adjustments of treatment effect estimates in randomized experiments
Adam Bloniarz, Hanzhong Liu, Cun-Hui Zhang +2
We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large. Investigators often use linear multivariate regression to an…
Asymptotic Properties of Lasso+mLS and Lasso+Ridge in Sparse High-dimensional Linear Regression
Hanzhong Liu, Bin Yu
We study the asymptotic properties of Lasso+mLS and Lasso+Ridge under the sparse high-dimensional linear regression model: Lasso selecting predictors and then modified Least Square…