Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Thomas H. Scheike, Mei-Jie Zhang
Title: Analyzing Competing Risk Data Using the R timereg Package

In this paper we describe flexible competing risks regression models using the comp.risk() function available in the timereg package for R based on Scheike et al. (2008). Regression models are specified for the transition probabilities, that is the cumulative incidence in the competing risks setting. The model contains the Fine and Gray (1999) model as a special case. This can be used to do goodness-of-fit test for the subdistribution hazards’ proportionality assumption (Scheike and Zhang 2008). The program can also construct confidence bands for predicted cumulative incidence curves.

We apply the methods to data on follicular cell lymphoma from Pintilie (2007), where the competing risks are disease relapse and death without relapse. There is important non-proportionality present in the data, and it is demonstrated how one can analyze these data using the flexible regression models.

Page views:: 21866. Submitted: 2009-05-25. Published: 2011-01-04.
Paper: Analyzing Competing Risk Data Using the R timereg Package     Download PDF (Downloads: 28860)
timereg_1.4-2.tar.gz: R source package Download (Downloads: 1476; 304KB)
v38i02.R: R example code from the paper Download (Downloads: 1747; 2KB)
follic.txt: Example data (comma-separated values) Download (Downloads: 2146; 32KB)

DOI: 10.18637/jss.v038.i02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.