A Markov decision process for response-adaptive randomization in clinical trials

DOI10.1016/j.csda.2022.107599OpenAlexW3202805813WikidataQ114671390 ScholiaQ114671390MaRDI QIDQ2101385

Thevaa Chandereng, David Merrell, Yeon-Hee Park

Publication date: 6 December 2022

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2109.14642

zbMATH Keywords

clinical trialsreinforcement learningresponse-adaptive randomizationadaptive trials

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• Approxrl

Cites Work

• Unnamed Item
• Optimal Adaptive Designs for Binary Response Trials
• Multi-armed bandit models for the optimal design of clinical trials: benefits and challenges
• Sequential allocation for an estimation problem with ethical costs
• Optimal few-stage designs
• Response‐adaptive randomization for multi‐arm clinical trials using the forward looking Gittins index rule
• Using Path Induction to Evaluate Sequential Allocation Procedures
• Bandit Algorithms
• Some Methods for Strengthening the Common χ 2 Tests

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