58 citations · 63 across the 11 of their papers we have counts for
11 papers
Power and Sample Size Calculations for Hybrid Controlled Trials
Ke Zhu, Shu Yang, Xiaofei Wang
Hybrid controlled trials (HCTs) augment randomized controls with external controls (ECs) to address practical challenges in randomized controlled trials (RCTs) and improve statisti…
Robust Estimation and Inference with Selective Borrowing in Hybrid Controlled Trials: A Tutorial with SelectiveIntegrative and intFRT
Ke Zhu, Hairong Huang, Shu Yang +1
Hybrid controlled trials (HCTs) augment randomized controlled trials (RCTs) with external controls (ECs) to improve statistical efficiency when RCTs face limited sample sizes, slow…
A Conformal Selection Framework for Individual Treatment Beneficiaries with Auxiliary External Data
Jiajun Liu, Ke Zhu, Xiaofei Wang
Identifying patients who are likely to benefit from a treatment is central to precision medicine and can guide follow-up trials, enrichment designs, and individualized decisions. A…
Selective Information Borrowing for Region-Specific Treatment Effect Inference under Covariate Mismatch in Multi-Regional Clinical Trials
Chenxi Li, Ke Zhu, Shu Yang +1
Multi-regional clinical trials (MRCTs) are central to global drug development, enabling evaluation of treatment effects across diverse populations. A key challenge is valid and eff…
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…
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…
Enhancing Statistical Validity and Power in Hybrid Controlled Trials: A Randomization Inference Approach with Conformal Selective Borrowing
Ke Zhu, Shu Yang, Xiaofei Wang
External controls from historical trials or observational data can augment randomized controlled trials when large-scale randomization is impractical or unethical, such as in drug…
Doubly robust estimators for generalizing treatment effects on survival outcomes from randomized controlled trials to a target population
Dasom Lee, Shu Yang, Xiaofei Wang
In the presence of heterogeneity between the randomized controlled trial (RCT) participants and the target population, evaluating the treatment effect solely based on the RCT often…
Elastic Integrative Analysis of Randomized Trial and Real-World Data for Treatment Heterogeneity Estimation
Shu Yang, Chenyin Gao, Donglin Zeng +1
We propose a test-based elastic integrative analysis of the randomized trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers.…
Improving trial generalizability using observational studies
Dasom Lee, Shu Yang, Lin Dong +3
Complementary features of randomized controlled trials (RCTs) and observational studies (OSs) can be used jointly to estimate the average treatment effect of a target population. W…