Dissertation/Thesis Abstract

Cure Rate Models with Nonparametric Form of Covariate Effects
by Chen, Tianlei, Ph.D., Virginia Polytechnic Institute and State University, 2015, 105; 10647357
Abstract (Summary)

This thesis focuses on development of spline-based hazard estimation models for cure rate data. Such data can be found in survival studies with long term survivors. Consequently, the population consists of the susceptible and non-susceptible subpopulations with the latter termed as “cured”. The modeling of both the cure probability and the hazard function of the susceptible subpopulation is of practical interest. Here we propose two smoothing-splinesbased models falling respectively into the popular classes of two component mixture cure rate models and promotion time cure rate models.

Under the framework of two component mixture cure rate model, Wang, Du and Liang (2012) have developed a nonparametric model where the covariate effects on both the cure probability and the hazard component are estimated by smoothing splines. Our first development falls under the same framework but estimates the hazard component based on the accelerated failure time model, instead of the proportional hazards model in Wang, Du and Liang (2012). Our new model has better interpretation in practice.

The promotion time cure rate model, motivated from a simplified biological interpretation of cancer metastasis, was first proposed only a few decades ago. Nonetheless, it has quickly become a competitor to the mixture models. Our second development aims to provide a nonparametric alternative to the existing parametric or semiparametric promotion time models.

Indexing (document details)
Advisor: Du, Pang
Commitee: Hong, Yili, Kim, Inyong, Terrell, George R.
School: Virginia Polytechnic Institute and State University
Department: Statistics
School Location: United States -- Virginia
Source: DAI-B 79/01(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Statistics
Keywords: Cure rate model, Nonparametric function estimation, Penalized likelihood, Smoothing spline, Survival analysis
Publication Number: 10647357
ISBN: 9780355208320
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