Revisiting the Cumulative Incidence Function With Competing Risks Data
Abstract
We consider estimation of the cumulative incidence function (CIF) in the competing risks Cox model. We study three methods. Methods 1 and 2 are existing methods while Method 3 is a newly-proposed method. Method 3 is constructed so that the sum of the CIF's across all event types at the last observed event time is guaranteed, assuming no ties, to be equal to 1. The performance of the methods is examined in a simulation study, and the methods are illustrated on a data example from the field of computer code comprehension. The newly-proposed Method 3 exhibits performance comparable to that of Methods 1 and 2 in terms of bias, variance, and confidence interval coverage rates. Thus, with our newly-proposed estimator, the advantage of having the end-of-study total CIF equal to 1 is achieved with no price to be paid in terms of performance.
Keywords
Cite
@article{arxiv.2202.11743,
title = {Revisiting the Cumulative Incidence Function With Competing Risks Data},
author = {David M. Zucker and Malka Gorfine},
journal= {arXiv preprint arXiv:2202.11743},
year = {2022}
}