Date of Award

12-15-2014

Document Type

Open Access Thesis

Department

Epidemiology and Biostatistics

First Advisor

Jiajia Zhang

Abstract

Typical survival methods have the assumption that every subject will eventually experience the event of interest, given enough follow-up time. However, there are some occasions in which a proportion of the population of interest will never experience the event of interest. Therefore, the incorporation of a “cure” fraction in a statistical model is necessary. In this thesis, I comprehensively evaluate mixture cure models in two different statistical software programs: the smcure package in R and the PSPMCM macro in SAS. Extensive simulation studies in R and SAS allow evaluation of the performance of these two models. An additional aspect of this thesis involves application of the mixture cure models in R and SAS to a new real data set of soft tissue sarcoma patients. The results from the models fitted to the sarcoma data set in R and in SAS will then be compared.

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Public Health Commons

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