Analyzing Competing Risk Data Using the R timereg Package

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...

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Bibliographic Details
Main Authors: Thomas H. Scheike, Mei-Jie Zhang
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2011-01-01
Series:Journal of Statistical Software
Subjects:
binomial modelling
competing risks
goodness of fit
inverse-censoring probability weighting
nonparametric effects
non-proportionality
R
regression effects
timereg
Online Access:http://www.jstatsoft.org/v38/i02/paper
Description
Summary: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.
ISSN:1548-7660

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