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A 3-parameter Gompertz distribution for survival data with competing risks, with an application to breast cancer data

Haile, Sarah R; Jeong, J-H; Chen, X; Cheng, Y (2016). A 3-parameter Gompertz distribution for survival data with competing risks, with an application to breast cancer data. Journal of Applied Statistics, 43(12):2239-2253.

Abstract

The cumulative incidence function is of great importance in the analysis of survival data when competing risks are present. Parametric modeling of such functions, which are by nature improper, suggests the use of improper distributions. One frequently used improper distribution is that of Gompertz, which captures only monotone hazard shapes. In some applications, however, subdistribution hazard estimates have been observed with unimodal shapes. An extension to the Gompertz distribution is presented which can capture unimodal as well as monotone hazard shapes. Important properties of the proposed distribution are discussed, and the proposed distribution is used to analyze survival data from a breast cancer clinical trial.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Language:English
Date:2016
Deposited On:26 Jan 2016 14:34
Last Modified:14 Jan 2025 02:40
Publisher:Taylor & Francis
ISSN:0266-4763
OA Status:Closed
Publisher DOI:https://doi.org/10.1080/02664763.2015.1134450
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