3 citations · 4 across the 4 of their papers we have counts for
4 papers
CSTEapp: An interactive R-Shiny application of the covariate-specific treatment effect curve for visualizing individualized treatment rule
Yi Zhou, Yuhao Deng, Yu-Shi Tian +5
In precision medicine, deriving the individualized treatment rule (ITR) is crucial for recommending the optimal treatment based on patients' baseline covariates. The covariate-spec…
Identifying average causal effect in regression discontinuity design with auxiliary data
Xinqin Feng, Wenjie Hu, Pu Yang +2
Regression discontinuity designs are widely used when treatment assignment is determined by whether a running variable exceeds a predefined threshold. However, most research focuse…
A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems
Yan Lyu, Sunhao Dai, Peng Wu +7
Accurate recommendation and reliable explanation are two key issues for modern recommender systems. However, most recommendation benchmarks only concern the prediction of user-item…
Model-Assisted Inference for Covariate-Specific Treatment Effects with High-dimensional Data
Peng Wu, Zhiqiang Tan, Wenjie Hu +1
Covariate-specific treatment effects (CSTEs) represent heterogeneous treatment effects across subpopulations defined by certain selected covariates. In this article, we consider ma…