A design for testing clinical strategies: biased adaptive within-subject randomization
We propose a method for assigning treatment in clinical trials, called the 'biased coin adaptive within-subject' (BCAWS) design: during the course of follow-up, the subject's response to a treatment is used to influence the future treatment, through a 'biased coin' algorithm...
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| Veröffentlicht in: | Journal of the Royal Statistical Society. Series A, Statistics in society Statistics in society, 2000, Vol.163 (1), p.29-38 |
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| container_issue | 1 |
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| container_title | Journal of the Royal Statistical Society. Series A, Statistics in society |
| container_volume | 163 |
| creator | Lavori, P. W. Dawson, R. |
| description | We propose a method for assigning treatment in clinical trials, called the 'biased coin adaptive within-subject' (BCAWS) design: during the course of follow-up, the subject's response to a treatment is used to influence the future treatment, through a 'biased coin' algorithm. This design results in treatment patterns that are closer to actual clinical practice and may be more acceptable to patients with chronic disease than the usual fixed trial regimens, which often suffer from drop-out and non-adherence. In this work, we show how to use the BCAWS design to compare treatment strategies, and we provide a simple example to illustrate the method. |
| doi_str_mv | 10.1111/1467-985X.00154 |
| format | Article |
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W.</creatorcontrib><creatorcontrib>Dawson, R.</creatorcontrib><title>A design for testing clinical strategies: biased adaptive within-subject randomization</title><title>Journal of the Royal Statistical Society. Series A, Statistics in society</title><description>We propose a method for assigning treatment in clinical trials, called the 'biased coin adaptive within-subject' (BCAWS) design: during the course of follow-up, the subject's response to a treatment is used to influence the future treatment, through a 'biased coin' algorithm. This design results in treatment patterns that are closer to actual clinical practice and may be more acceptable to patients with chronic disease than the usual fixed trial regimens, which often suffer from drop-out and non-adherence. 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W.</creatorcontrib><creatorcontrib>Dawson, R.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Journal of the Royal Statistical Society. Series A, Statistics in society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lavori, P. W.</au><au>Dawson, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A design for testing clinical strategies: biased adaptive within-subject randomization</atitle><jtitle>Journal of the Royal Statistical Society. Series A, Statistics in society</jtitle><date>2000</date><risdate>2000</risdate><volume>163</volume><issue>1</issue><spage>29</spage><epage>38</epage><pages>29-38</pages><issn>0964-1998</issn><eissn>1467-985X</eissn><abstract>We propose a method for assigning treatment in clinical trials, called the 'biased coin adaptive within-subject' (BCAWS) design: during the course of follow-up, the subject's response to a treatment is used to influence the future treatment, through a 'biased coin' algorithm. This design results in treatment patterns that are closer to actual clinical practice and may be more acceptable to patients with chronic disease than the usual fixed trial regimens, which often suffer from drop-out and non-adherence. 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| fulltext | fulltext |
| identifier | ISSN: 0964-1998 |
| ispartof | Journal of the Royal Statistical Society. Series A, Statistics in society, 2000, Vol.163 (1), p.29-38 |
| issn | 0964-1998 1467-985X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_38853218 |
| source | RePEc; JSTOR Mathematics & Statistics; EBSCOhost Business Source Complete; Access via Wiley Online Library; JSTOR Archive Collection A-Z Listing; Oxford University Press Journals All Titles (1996-Current) |
| subjects | Adaptive randomization Algorithms Applications Clinical trials Data imputation Decision making Depressive disorders Design of clinical trials Diseases Economic sociology Exact sciences and technology Experiment design Health outcomes Inference Mathematics Medical sciences Missing data Monoamine oxidase inhibitors Probability and statistics Random allocation Sciences and techniques of general use Serotonin agents Statistics Symptoms Time-varying treatments |
| title | A design for testing clinical strategies: biased adaptive within-subject randomization |
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