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

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  • Merrell, David
  • Chandereng, Thevaa
  • Park, Yeonhee

Abstract

In clinical trials, response-adaptive randomization (RAR) has the appealing ability to assign more subjects to better-performing treatments based on interim results. Traditional RAR strategies alter the randomization ratio on a patient-by-patient basis. An alternate approach is blocked RAR, which groups patients together in blocks and recomputes the randomization ratio in a block-wise fashion; past works show that this provides robustness against time-trend bias. However, blocked RAR poses additional questions: how many blocks should there be, and how many patients should each block contain?

Suggested Citation

  • Merrell, David & Chandereng, Thevaa & Park, Yeonhee, 2023. "A Markov decision process for response-adaptive randomization in clinical trials," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:csdana:v:178:y:2023:i:c:s0167947322001797
    DOI: 10.1016/j.csda.2022.107599
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    1. repec:bla:biomet:v:71:y:2015:i:4:p:969-978 is not listed on IDEAS
    2. William F. Rosenberger & Nigel Stallard & Anastasia Ivanova & Cherice N. Harper & Michelle L. Ricks, 2001. "Optimal Adaptive Designs for Binary Response Trials," Biometrics, The International Biometric Society, vol. 57(3), pages 909-913, September.
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