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Unbiased estimation for response adaptive clinical trials

Bayesian adaptive trials have the defining feature that the probability of randomization to a particular treatment arm can change as information becomes available as to its true worth. However, there is still a general reluctance to implement such designs in many clinical settings. One area of conce...

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Detalles Bibliográficos
Autores principales: Bowden, Jack, Trippa, Lorenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395089/
https://www.ncbi.nlm.nih.gov/pubmed/26265771
http://dx.doi.org/10.1177/0962280215597716
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author Bowden, Jack
Trippa, Lorenzo
author_facet Bowden, Jack
Trippa, Lorenzo
author_sort Bowden, Jack
collection PubMed
description Bayesian adaptive trials have the defining feature that the probability of randomization to a particular treatment arm can change as information becomes available as to its true worth. However, there is still a general reluctance to implement such designs in many clinical settings. One area of concern is that their frequentist operating characteristics are poor or, at least, poorly understood. We investigate the bias induced in the maximum likelihood estimate of a response probability parameter, p, for binary outcome by the process of adaptive randomization. We discover that it is small in magnitude and, under mild assumptions, can only be negative – causing one’s estimate to be closer to zero on average than the truth. A simple unbiased estimator for p is obtained, but it is shown to have a large mean squared error. Two approaches are therefore explored to improve its precision based on inverse probability weighting and Rao–Blackwellization. We illustrate these estimation strategies using two well-known designs from the literature.
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spelling pubmed-53950892017-04-18 Unbiased estimation for response adaptive clinical trials Bowden, Jack Trippa, Lorenzo Stat Methods Med Res Regular Articles Bayesian adaptive trials have the defining feature that the probability of randomization to a particular treatment arm can change as information becomes available as to its true worth. However, there is still a general reluctance to implement such designs in many clinical settings. One area of concern is that their frequentist operating characteristics are poor or, at least, poorly understood. We investigate the bias induced in the maximum likelihood estimate of a response probability parameter, p, for binary outcome by the process of adaptive randomization. We discover that it is small in magnitude and, under mild assumptions, can only be negative – causing one’s estimate to be closer to zero on average than the truth. A simple unbiased estimator for p is obtained, but it is shown to have a large mean squared error. Two approaches are therefore explored to improve its precision based on inverse probability weighting and Rao–Blackwellization. We illustrate these estimation strategies using two well-known designs from the literature. SAGE Publications 2015-08-11 2017-10 /pmc/articles/PMC5395089/ /pubmed/26265771 http://dx.doi.org/10.1177/0962280215597716 Text en © The Author(s) 2015 http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Regular Articles
Bowden, Jack
Trippa, Lorenzo
Unbiased estimation for response adaptive clinical trials
title Unbiased estimation for response adaptive clinical trials
title_full Unbiased estimation for response adaptive clinical trials
title_fullStr Unbiased estimation for response adaptive clinical trials
title_full_unstemmed Unbiased estimation for response adaptive clinical trials
title_short Unbiased estimation for response adaptive clinical trials
title_sort unbiased estimation for response adaptive clinical trials
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395089/
https://www.ncbi.nlm.nih.gov/pubmed/26265771
http://dx.doi.org/10.1177/0962280215597716
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