A Markov decision process for response adaptive designs

Yanqing Yi and Xikui Wang

Econometrics and Statistics, 2023, vol. 25, issue C, 125-133

Abstract: The randomized treatment allocation process in a response adaptive clinical trial is formulated as a stochastic sequential decision problem and an algorithm is proposed to approximate the optimal value under the average reward criterion. When the information of previous treatment allocations and associated responses are summarized with sufficient statistics for unknown parameters, the decision process becomes a Markov process, on which a span-contractor operator is defined. It is proven that the average reward under the policy identified from the span-contractor operator converges almost surely to the optimal value. Numerical results reveal that the sequential procedure based on the controlled Markov process shows superior ethical advantage and at the same time produces good statistical power for large sample sizes such as 200 or larger.

Keywords: Average reward criterion; Markov decision process; Randomization; Response adaptive design of clinical trials; Statistical power (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S2452306221001301
Full text for ScienceDirect subscribers only. Contains open access articles

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:25:y:2023:i:c:p:125-133

DOI: 10.1016/j.ecosta.2021.10.015

Access Statistics for this article

Econometrics and Statistics is currently edited by E.J. Kontoghiorghes, H. Van Dijk and A.M. Colubi

More articles in Econometrics and Statistics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().