Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14960
DC FieldValueLanguage
dc.contributor.authorKonstantinou, Maria-
dc.contributor.authorBiedermann, Stefanie-
dc.contributor.authorKimber, Alan-
dc.date.accessioned2019-08-22T09:53:46Z-
dc.date.available2019-08-22T09:53:46Z-
dc.date.issued2017-09-01-
dc.identifier.citationComputational Statistics and Data Analysis, 2017, vol. 113, pp. 239-250en_US
dc.identifier.issn01679473-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/14960-
dc.description.abstractThe exponential-based proportional hazards model is often assumed in time-to-event experiments but may only approximately hold. Deviations in different neighbourhoods of this model are considered that include other widely used parametric proportional hazards models and the data are assumed to be subject to censoring. Minimax designs are then found explicitly, based on criteria corresponding to classical c- and D-optimality. Analytical characterisations of optimal designs are provided which, unlike optimal designs for related problems in the literature, have finite support and thus avoid the issues of implementing a density-based design in practice. Finally, the proposed designs are compared with the balanced design that is traditionally used in practice, and recommendations for practitioners are given.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofComputational Statistics and Data Analysisen_US
dc.rights© Elsevieren_US
dc.subjectc-optimalityen_US
dc.subjectD-optimalityen_US
dc.subjectMinimax optimal designsen_US
dc.subjectProportional hazards modelsen_US
dc.subjectType-I censoringen_US
dc.titleModel robust designs for survival trialsen_US
dc.typeArticleen_US
dc.collaborationRuhr-Universität Bochumen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationUniversity of Southamptonen_US
dc.subject.categoryEnvironmental Biotechnologyen_US
dc.subject.categoryOther Agricultural Sciencesen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.countryGermanyen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldAgricultural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1016/j.csda.2016.10.013en_US
dc.identifier.scopus2-s2.0-85006136706-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85006136706-
dc.relation.volume113en_US
cut.common.academicyear2019-2020en_US
dc.identifier.spage239en_US
dc.identifier.epage250en_US
item.languageiso639-1en-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
crisitem.author.deptDepartment of Chemical Engineering-
crisitem.author.facultyFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.orcid0000-0002-4140-0444-
crisitem.author.parentorgFaculty of Geotechnical Sciences and Environmental Management-
crisitem.journal.journalissn0167-9473-
crisitem.journal.publisherElsevier-
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