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dc.contributor.advisorKittelson, John
dc.contributor.authorGunzburger, Elise
dc.date.accessioned2015-12-28T17:21:58Z
dc.date.available2015-12-28T17:21:58Z
dc.date.submitted2015
dc.descriptionFall
dc.descriptionIncludes bibliographical references.
dc.description.abstractAlthough multiple endpoints are typically considered in the design and interpretation of clinical trials, decision criteria are usually based on a single primary endpoint. This thesis aims to examine methods for constructing decision criteria using a bivariate endpoint so that decisions can consider joint effects on both the primary and key secondary endpoints. Specifically, decision criteria for the joint effects of a treatment on a survival endpoint and a companion longitudinal endpoint are considered. Bivariate decision criteria are explored based on three different methods for linking longitudinal and survival submodels using readily available software. The methods are illustrated with the application to a well know AIDs dataset as well as to a recent major cardiovascular trial.
dc.identifierGunzburger_ucdenveramc_1639M_10277.pdf
dc.identifier.urihttp://hdl.handle.net/10968/1181
dc.languageEnglish
dc.publisherUniversity of Colorado Anschutz Medical Campus. Strauss Health Sciences Library
dc.rightsCopyright of the original work is retained by the author.
dc.subjectBivariate
dc.subjectJoint Models
dc.subject.meshClinical Trial
dc.subject.meshDecision Support Techniques
dc.subject.meshLongitudinal Studies
dc.subject.meshSurvival
dc.titleApplication of joint longitudinal-survival models to bivariate decision making in clinical trials, The
dc.typeText
thesis.degree.disciplineBiostatistics
thesis.degree.grantorUniversity of Colorado at Denver, Anschutz Medical Campus
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)


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