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Cure Rate Model with Spline Estimated Components

dc.contributor.authorWang, Luen
dc.contributor.committeechairDu, Pangen
dc.contributor.committeecochairTerrell, George R.en
dc.contributor.committeememberSmith, Eric P.en
dc.contributor.committeememberLiu, Chuanhaien
dc.contributor.committeememberLeman, Scotland C.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T20:14:11Zen
dc.date.adate2010-07-30en
dc.date.available2014-03-14T20:14:11Zen
dc.date.issued2010-07-13en
dc.date.rdate2013-05-21en
dc.date.sdate2010-07-22en
dc.description.abstractIn some survival analysis of medical studies, there are often long term survivors who can be considered as permanently cured. The goals in these studies are to estimate the cure probability of the whole population and the hazard rate of the noncured subpopulation. The existing methods for cure rate models have been limited to parametric and semiparametric models. More specifically, the hazard function part is estimated by parametric or semiparametric model where the effect of covariate takes a parametric form. And the cure rate part is often estimated by a parametric logistic regression model. We introduce a non-parametric model employing smoothing splines. It provides non-parametric smooth estimates for both hazard function and cure rate. By introducing a latent cure status variable, we implement the method using a smooth EM algorithm. Louis' formula for covariance estimation in an EM algorithm is generalized to yield point-wise confidence intervals for both functions. A simple model selection procedure based on the Kullback-Leibler geometry is derived for the proposed cure rate model. Numerical studies demonstrate excellent performance of the proposed method in estimation, inference and model selection. The application of the method is illustrated by the analysis of a melanoma study.en
dc.description.degreePh. D.en
dc.identifier.otheretd-07222010-123652en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07222010-123652/en
dc.identifier.urihttp://hdl.handle.net/10919/28359en
dc.publisherVirginia Techen
dc.relation.haspartthesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNonparametric Function Estimationen
dc.subjectSmoothing Splinen
dc.titleCure Rate Model with Spline Estimated Componentsen
dc.typeDissertationen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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