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Bayesian Inference and Novel Models for Survival Data with Cured Fraction

Title: Bayesian Inference and Novel Models for Survival Data with Cured Fraction.
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Name(s): Gupta, Cherry Chunqi Huang, author
Sinha, Debajyoti, professor directing dissertation
Glueckauf, Robert L., university representative
Slate, Elizabeth H., committee member
Pati, Debdeep, committee member
Florida State University, degree granting institution
College of Arts and Sciences, degree granting college
Department of Statistics, degree granting department
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2016
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource (46 pages)
Language(s): English
Abstract/Description: Existing cure-rate survival models are generally not convenient for modeling and estimating the survival quantiles of a patient with specified covariate values. They also do not allow inference on the change in the number of clonogens over time. This dissertation proposes two novel classes of cure-rate model, the transform-both-sides cure-rate model (TBSCRM) and the clonogen proliferation cure-rate model (CPCRM). Both can be used to make inference about both the cure-rate and the survival probabilities over time. The TBSCRM can also produce estimates of a patient's quantiles of survival time, and the CPCRM can produce estimates of a patient's expected number of clonogens at each time. We develop methods of Bayesian inference about the covariate effects on relevant quantities such as the cure-rate, methods which use Markov Chain Monte Carlo (MCMC) tools. We also show that the TBSCRM-based and CPCRM-based Bayesian methods perform well in simulation studies and outperform existing cure-rate models in application to the breast cancer survival data from the National Cancer Institute’s Surveillance, Epidemiology and End Results (SEER) database.
Identifier: FSU_2016SU_Gupta_fsu_0071E_13423 (IID)
Submitted Note: A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Degree Awarded: Summer Semester 2016.
Date of Defense: July 14, 2016.
Bibliography Note: Includes bibliographical references.
Advisory Committee: Debajyoti Sinha, Professor Directing Dissertation; Robert Glueckauf, University Representative; Elizabeth Slate, Committee Member; Debdeep Pati, Committee Member.
Subject(s): Statistics
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_2016SU_Gupta_fsu_0071E_13423
Owner Institution: FSU

Choose the citation style.
Gupta, C. C. H. (2016). Bayesian Inference and Novel Models for Survival Data with Cured Fraction. Retrieved from http://purl.flvc.org/fsu/fd/FSU_2016SU_Gupta_fsu_0071E_13423