This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 184
Type: Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #308014
Title: Improved Survival Modeling Using a Reduced Piecewise Exponential Approach
Author(s): Gang Han*+ and Michael J. Schell and Jongphil Kim
Companies: Moffitt Cancer Center & Research Institute and Moffitt Cancer Center and Moffitt Cancer Center & Research Institute
Address: 12902 Magnolia Drive, Tampa, FL, 33612,
Keywords: Survival analysis ; exponential family ; uniformly most powerful unbiased test ; pool-adjacent-violators algorithm
Abstract:

In medical research, statistical models for survival data are typically non- or semi-parametric, e.g., the Kaplan-Meier curve. Parametric survival modeling, however, can reveal additional insights to clinicians. A major constraint of the existing parametric models is the lack of flexibility due to distribution assumptions. A flexible and parsimonious piecewise exponential model is presented. This model identifies shifts in the failure rate over time using a likelihood ratio test and a backward elimination procedure. It can be combined with presumed order restrictions on the failure rate. Such modeling provides an additional descriptive tool in understanding differences in patient response and can also serve as a validation tool for exponential failure. An application in a lung cancer study is presented.


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