most citedRobust and Efficient Semi-Supervised Estimation of Average Treatment Effects with Application to Electronic Health Records Data

28 citations · 43 across the 2 of their papers we have counts for

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stat.ME2018★ 28 cited

Robust and Efficient Semi-Supervised Estimation of Average Treatment Effects with Application to Electronic Health Records Data

David Cheng, Ashwin Ananthakrishnan, Tianxi Cai

We consider the problem of estimating the average treatment effect (ATE) in a semi-supervised learning setting, where a very small proportion of the entire set of observations are…

stat.ME2017★ 15 cited

Estimating Average Treatment Effects with a Double-Index Propensity Score

David Cheng, Abhishek Chakrabortty, Ashwin N. Ananthakrishnan +1

We consider estimating average treatment effects (ATE) of a binary treatment in observational data when data-driven variable selection is needed to select relevant covariates from…