Degree Name

MS (Master of Science)

Program

Mathematical Sciences

Date of Award

8-2019

Committee Chair or Co-Chairs

JeanMarie Hendrickson

Committee Members

Robert Price, Nicole Lewis

Abstract

An efficient way of analyzing survival clinical data such as cancer data is a great concern to health experts. In this study, we investigate and propose an efficient way of handling survival clinical data. Simulation studies were conducted to compare performances of various forms of survival model techniques using an R package ``survsim". Models performance was conducted with varying sample sizes as small ($n5000$). For small and mild samples, the performance of the semi-parametric outperform or approximate the performance of the parametric model. However, for large samples, the parametric model outperforms the semi-parametric model. We compared the effectiveness and reliability of our proposed techniques using a real clinical data of mild sample size. Finally, systematic steps on how to model and explain the proposed techniques on real survival clinical data was provided.

Document Type

Thesis - Withheld

Copyright

Copyright by the authors.

Available for download on Saturday, July 15, 2023

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