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dc.contributor.authorGrayling, Michael J
dc.contributor.authorWason, James MS
dc.contributor.authorMander, Adrian P
dc.date.accessioned2018-09-17T08:43:49Z
dc.date.available2018-09-17T08:43:49Z
dc.date.issued2018-04
dc.identifier.issn1551-7144
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/280278
dc.description.abstractMulti-arm multi-stage trial designs can bring notable gains in efficiency to the drug development process. However, for normally distributed endpoints, the determination of a design typically depends on the assumption that the patient variance in response is known. In practice, this will not usually be the case. To allow for unknown variance, previous research explored the performance of t-test statistics, coupled with a quantile substitution procedure for modifying the stopping boundaries, at controlling the familywise error-rate to the nominal level. Here, we discuss an alternative method based on Monte Carlo simulation that allows the group size and stopping boundaries of a multi-arm multi-stage t-test to be optimised, according to some nominated optimality criteria. We consider several examples, provide R code for general implementation, and show that our designs confer a familywise error-rate and power close to the desired level. Consequently, this methodology will provide utility in future multi-arm multi-stage trials.
dc.format.mediumPrint-Electronic
dc.languageeng
dc.publisherElsevier BV
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHumans
dc.subjectEndpoint Determination
dc.subjectAnalysis of Variance
dc.subjectData Interpretation, Statistical
dc.subjectMonte Carlo Method
dc.subjectSample Size
dc.subjectResearch Design
dc.subjectClinical Trials as Topic
dc.titleAn optimised multi-arm multi-stage clinical trial design for unknown variance.
dc.typeArticle
prism.endingPage120
prism.publicationDate2018
prism.publicationNameContemp Clin Trials
prism.startingPage116
prism.volume67
dc.identifier.doi10.17863/CAM.27646
dcterms.dateAccepted2018-02-19
rioxxterms.versionofrecord10.1016/j.cct.2018.02.011
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.licenseref.startdate2018-04
dc.contributor.orcidGrayling, Michael [0000-0002-0680-6668]
dc.contributor.orcidWason, James [0000-0002-4691-126X]
dc.contributor.orcidMander, Adrian [0000-0002-0742-9040]
dc.identifier.eissn1559-2030
dc.publisher.urlhttps://www.sciencedirect.com/science/article/pii/S1551714417303798?via=ihub#!
rioxxterms.typeJournal Article/Review
pubs.funder-project-idMRC (unknown)
pubs.funder-project-idMRC (unknown)
cam.issuedOnline2018-02-21
cam.orpheus.successThu Jan 30 12:58:15 GMT 2020 - The item has an open VoR version.
rioxxterms.freetoread.startdate2100-01-01


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International