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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2015
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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. |
format | Online Article Text |
id | pubmed-5395089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT bowdenjack unbiasedestimationforresponseadaptiveclinicaltrials AT trippalorenzo unbiasedestimationforresponseadaptiveclinicaltrials |