Work

Summarizing differences in cumulative incidence functions

Year: 2008

Type: article

Abstract: The cumulative incidence function is widely reported in competing risks studies, with group differences assessed by an extension of the log-rank test. However, simple, interpretable summaries of group differences are not available. An adaptation of the proportional hazards model to the cumulative incidence function is often employed, but the interpretation of the hazard ratio may be somewhat awkward, unlike the usual survival set-up. We propose nonparametric inferences for general summary measures, which may be time-varying, and for time-averaged versions of the measures. Theoretical justification is provided using counting process techniques. A real data example illustrates the practical utility of the methods.

Source: Statistics in Medicine

DOI: 10.1002/sim.3339

Authors: Mei‐Jie Zhang, Jason Fine

Institutions: Medical College of Wisconsin, University of North Carolina at Chapel Hill

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funder: National Cancer Institute

Awards: Frailty Models and Survival Analysis in Cancer Research, Techniques for modeling complex longitidinal studies, G5070435602, G71089118, G8527272899