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dc.contributor.advisorSeaman, John Weldon, 1956-
dc.contributor.authorPruszynski, Jessica E.
dc.contributor.otherBaylor University. Dept. of Statistical Sciences.en
dc.date.accessioned2010-06-23T12:29:00Z
dc.date.available2010-06-23T12:29:00Z
dc.date.copyright2010-05
dc.date.issued2010-06-23T12:29:00Z
dc.identifier.urihttp://hdl.handle.net/2104/7959
dc.descriptionIncludes bibliographical references (p. ).en
dc.description.abstractWe first consider the problem of discrete censored sampling. Censored binomial data may lead to irregular likelihood functions and problems with statistical inference. We consider a Bayesian approach to inference for censored binomial problems and compare it to non-Bayesian methods. We include examples and a simulation study in which we compare point estimation, interval coverage, and interval width for Bayesian and non-Bayesian methods. The continual reassessment method (CRM) is a Bayesian design often used in Phase I cancer clinical trials. It models the toxicity response of the patient as a function of administered dose using a model that is updated as data accrues. The CRM does not take into consideration the relationship between the toxicity response and the proportion of the administered drug that is absorbed by targeted tissue. Not accounting for this discrepancy can yield misleading conclusions about the maximum tolerated dose to be used in subsequent Phase II trials. We will examine, through simulation, the effect that disregarding the level of bioavailability has on the performance of the CRM.en
dc.description.statementofresponsibilityby Jessica E. Pruszynski.en
dc.format.extent5306792 bytes
dc.format.extent75712 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen
dc.rightsBaylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission.en
dc.subjectBayesian methods.en
dc.subjectDiscrete censored sampling.en
dc.subjectPhase I clinical trials.en
dc.titleBayesian models for discrete censored sampling and dose finding.en
dc.typeThesisen
dc.description.degreePh.D.en
dc.rights.accessrightsWorldwide access.en
dc.rights.accessrightsAccess changed 3/18/13.
dc.contributor.departmentStatistical Sciences.en


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