1 citations · 2 across the 5 of their papers we have counts for
5 papers
Multicategory Matched Learning for Estimating Optimal Individualized Treatment Rules in Observational Studies with Application to a Hepatocellular Carcinoma Study
Xuqiao Li, Qiuyan Zhou, Ying Wu +1
One primary goal of precision medicine is to estimate the individualized treatment rules (ITRs) that optimize patients' health outcomes based on individual characteristics. Health…
Mahalanobis balancing: a multivariate perspective on approximate covariate balancing
Yimin Dai, Ying Yan
In the past decade, various exact balancing-based weighting methods were introduced to the causal inference literature. Exact balancing alleviates the extreme weight and model miss…
Kernel-Distance-Based Covariate Balancing
Xialing Wen, Ying Yan, Wenliang Pan +1
A common concern in observational studies focuses on properly evaluating the causal effect, which usually refers to the average treatment effect or the average treatment effect on…
Empirical Likelihood-Based Estimation and Inference in Randomized Controlled Trials with High-Dimensional Covariates
Wei Liang, Ying Yan
In this paper, we propose a data-adaptive empirical likelihood-based approach for treatment effect estimation and inference, which overcomes the obstacle of the traditional empiric…
Empirical Likelihood Weighted Estimation of Average Treatment Effects
Yuanyao Tan, Xialing Wen, Wei Liang +1
There has been growing attention on how to effectively and objectively use covariate information when the primary goal is to estimate the average treatment effect (ATE) in randomiz…