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math.ST2015★ 183 cited
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…
stat.ME2015★ 3 cited
Group-Linear Empirical Bayes Estimates for a Heteroscedastic Normal Mean
Asaf Weinstein, Zhuang Ma, Lawrence D. Brown +1
The problem of estimating the mean of a normal vector with known but unequal variances introduces substantial difficulties that impair the adequacy of traditional empirical Bayes e…