Lasso adjustments of treatment effect estimates in randomized experiments

来源 :上海交通大学 | 被引量 : 0次 | 上传用户：adidas9910

【摘要】

：

【作者】

：

Adam Bloniarz Hanzhong Liu Cun-Hui Zhang Jasjeet S.Sekhon Bin Yu

【机构】

：

Department of Statistics,University of California,Berkeley,CA 94720,USA

【出处】

：

上海交通大学

【发表日期】

：

2016年4期

【关键词】

：

randomized experiment Neyman-Rubin model average treatment effect high-dimension

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　　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 analyze randomized experiments instead of simply reporting the difference of means between treatment and control groups.

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Lasso adjustments of treatment effect estimates in randomized experiments

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