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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…
Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
Jiuyao Lu, Tianruo Zhang, Ke Zhu
Balancing covariates is critical for credible and efficient randomized experiments. Rerandomization addresses this by repeatedly generating treatment assignments until covariate ba…
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…
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…