131 citations · 352 across the 94 of their papers we have counts for
13 papers · 2 filters
Designing Efficient Hybrid and Single-Arm Trials: External Control Borrowing and Sample Size Calculation
Yujing Gao, Xiang Zhang, Shu Yang
External controls (ECs) from historical trials or real-world data have gained increasing attention as a way to augment hybrid and single-arm trials, especially when balanced random…
Heterogeneity-Aware Federated Causal Inference Leveraging Effect-Measure Transportability
Siqi Cao, Shu Yang
Federated learning of causal estimands offers a powerful strategy to improve estimation efficiency by leveraging data from multiple study sites while preserving privacy. Existing l…
Integrating RCTs, RWD, AI/ML and Statistics: Next-Generation Evidence Synthesis
Shu Yang, Margaret Gamalo, Haoda Fu
Randomized controlled trials (RCTs)have been the cornerstone of clinical evidence; however, their cost, duration, and restrictive eligibility criteria limit power and external vali…
Multivariate Zero-Inflated Causal Model for Regional Mobility Restriction Effects on Consumer Spending
Taekwon Hong, Wenbin Lu, Shu Yang +1
The COVID-19 pandemic presents challenges to both public health and the economy. Our objective is to examine how household expenditure, a significant component of private demand, r…
Rate doubly robust estimation for weighted average treatment effects
Yiming Wang, Yi Liu, Shu Yang
The weighted average treatment effect (WATE) defines a versatile class of causal estimands for populations characterized by propensity score weights, including the average treatmen…
A Spectral Confounder Adjustment for Spatial Regression with Multiple Exposures and Outcomes
Shih-Ni Prim, Yawen Guan, Shu Yang +4
Characterizing social vulnerability is fundamental to disaster response planning. Numerous vulnerability indicators have been developed, but they are typically not validated for th…
Doubly Robust Fusion of Many Treatments for Policy Learning
Ke Zhu, Jianing Chu, Ilya Lipkovich +2
Individualized treatment rules/recommendations (ITRs) aim to improve patient outcomes by tailoring treatments to the characteristics of each individual. However, when there are man…
Robust Estimation and Inference in Hybrid Controlled Trials for Binary Outcomes: A Case Study on Non-Small Cell Lung Cancer
Jiajun Liu, Ke Zhu, Shu Yang +1
Hybrid controlled trials (HCTs), which augment randomized controlled trials (RCTs) with external controls (ECs), are increasingly receiving attention as a way to address limited po…
Integrative Analysis of High-dimensional RCT and RWD Subject to Censoring and Hidden Confounding
Xin Ye, Shu Yang, Xiaofei Wang +1
In this study, we focus on estimating the heterogeneous treatment effect (HTE) for survival outcome. The outcome is subject to censoring and the number of covariates is high-dimens…
Doubly robust omnibus sensitivity analysis of externally controlled trials with intercurrent events
Chenyin Gao, Xiang Zhang, Shu Yang
Externally controlled trials are crucial in clinical development when randomized controlled trials are unethical or impractical. These trials consist of a full treatment arm with t…
Statistical Inference for Heterogeneous Treatment Effect with Right-censored Data from Synthesizing Randomized Clinical Trials and Real-world Data
Guangcai Mao, Shu Yang, Xiaofei Wang
The heterogeneous treatment effect plays a crucial role in precision medicine.There is evidence that real-world data, even subject to biases, can be employed as supplementary evide…
Targeted Data Fusion for Region-Specific Survival Effects in the AMP HIV Prevention Trials
Yi Liu, Alexander W. Levis, Ke Zhu +3
The Antibody Mediated Prevention (AMP) trials opened a new scientific frontier by showing that passively administered monoclonal broadly neutralizing antibodies (bnAbs) could preve…
COADVISE: Covariate Adjustment with Variable Selection in Randomized Controlled Trials
Yi Liu, Ke Zhu, Larry Han +1
Adjusting for covariates in randomized controlled trials can enhance the credibility and efficiency of treatment effect estimation. However, handling numerous covariates and their…