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Journal of the American Statistical Association|February 12, 2019
A Bayesian Machine Learning Approach for Optimizing Dynamic Treatment RegimesThomas A Murray, Ying Yuan, Peter F Thall
Journal of the Royal Statistical Society. Series C, Applied Statistics|March 13, 2012
Estimating progression-free survival in paediatric brain tumour patients when some progression statuses are unknownYing Yuan, Peter F Thall, Johannes E Wolff
Statistics in Medicine|May 19, 2016
Utility-based designs for randomized comparative trials with categorical outcomesThomas A Murray, Peter F Thall, Ying Yuan
Statistics in Medicine|April 20, 2026
BAR12: Bayesian Autoregressive Phase 1-2 Design for Cell Therapy Trials With Manufacturing ChangesCheng-Han Yang, Peter F Thall, David Marin, et al.
Biometrics|October 3, 2024
ROMI: a randomized two-stage basket trial design to optimize doses for multiple indicationsShuqi Wang, Peter F Thall, Kentaro Takeda, et al.
JCO Precision Oncology|November 22, 2021
Lessons Learned From Implementing a Novel Bayesian Adaptive Dose-Finding Design in Advanced Pancreatic CancerRebecca S S Tidwell, Peter F Thall, Ying Yuan
Therapeutic Innovation & Regulatory Science|August 20, 2025
BOP2-Comb: Bayesian Optimal Phase II Design for Optimizing Doses and Assessing Contribution of Components in Drug CombinationsXiaohan Chi, Ying Yuan, Ruitao Lin
Journal of the American Statistical Association|November 11, 2014
Using Data Augmentation to Facilitate Conduct of Phase I-II Clinical Trials with Delayed OutcomesIck Hoon Jin, Suyu Liu, Peter F Thall, et al.
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