Model robust designs for survival trials

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dc.contributor.authorKonstantinou, Maria
dc.contributor.authorBiedermann, Stefanie
dc.contributor.authorKimber, Alan
dc.date.accessioned2016-07-25T11:23:48Z
dc.date.available2016-07-25T11:23:48Z
dc.date.issued2016
dc.description.abstractThe exponential-based proportional hazards model is often assumed in time- to-event experiments but may only approximately hold. We consider deviations in different neighbourhoods of this model that include other widely used paramet- ric proportional hazards models and we further assume that the data are subject to censoring. Minimax designs are then found explicitly based on criteria corre- sponding to classical c- and D-optimality. We provide analytical characterisations of optimal designs which, unlike optimal designs for related problems in the litera- ture, have finite support and thus avoid the issues of implementing a density-based design in practice. Finally, our designs are compared with the balanced design that is traditionally used in practice, and recommendations for practitioners are given.en
dc.identifier.urihttp://hdl.handle.net/2003/35156
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-17203
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;38, 2016en
dc.subjectproportional hazards modelsen
dc.subjectType-I censoringen
dc.subjectc-optimalityen
dc.subjectD-optimalityen
dc.subjectminimax optimal designsen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleModel robust designs for survival trialsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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