Please use this identifier to cite or link to this item: https://doi.org/10.1006/jmva.2001.1987
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dc.titleAn adaptive design for multi-arm clinical trials
dc.contributor.authorBai, Z.D.
dc.contributor.authorHu, F.
dc.contributor.authorShen, L.
dc.date.accessioned2014-10-28T05:09:55Z
dc.date.available2014-10-28T05:09:55Z
dc.date.issued2002
dc.identifier.citationBai, Z.D., Hu, F., Shen, L. (2002). An adaptive design for multi-arm clinical trials. Journal of Multivariate Analysis 81 (1) : 1-18. ScholarBank@NUS Repository. https://doi.org/10.1006/jmva.2001.1987
dc.identifier.issn0047259X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104989
dc.description.abstractThe randomized play-the-winner (RPW) rule is very useful in clinical trials for patient allocation with two treatments. L. J. Wei (1979, Ann. Statist. 7, 291-296) introduces the generalized Friedman's urn (GFU) model to clinical trials of K treatments (as an extension of the RPW). In this paper, we propose a new adaptive design for multi-arm clinical trials. The proposed adaptive design proportionally depends on the success rates of each treatment, so that a treatment which is doing well is more likely to be assigned in future trials than a treatment which is doing poorly. The new design is more reasonable although it is no longer a GFU model. In the paper we show that the new design has some desirable asymptotic properties and that it has wider and easier applications in practice. Some simulations also support this new design. © 2001 Elsevier Science (USA).
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1006/jmva.2001.1987
dc.sourceScopus
dc.subjectAdaptive designs
dc.subjectAsymptotic limits
dc.subjectClinical trial
dc.subjectGeneralized Friedman's urn
dc.subjectPlay-the winner
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1006/jmva.2001.1987
dc.description.sourcetitleJournal of Multivariate Analysis
dc.description.volume81
dc.description.issue1
dc.description.page1-18
dc.description.codenJMVAA
dc.identifier.isiut000175333500001
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