Analyzing Competing Risk Data Using the R timereg Package

Abstract

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.

Keywords

• binomial modelling
• competing risks
• goodness of fit
• inverse-censoring probability weighting
• nonparametric effects
• non-proportionality
• R
• regression effects
• timereg