A note on nonparametric quantile inference for competing risks and more complex multistate models

Jan Beyersmann and Martin Schumacher

Biometrika, 2008, vol. 95, issue 4, 1006-1008

Abstract: Nonparametric quantile inference for competing risks has recently been studied by Peng & Fine (2007). Their key result establishes uniform consistency and weak convergence of the inverse of the Aalen--Johansen estimator of the cumulative incidence function, using the representation of the cumulative incidence estimator as a sum of independent and identically distributed random variables. The limit process is of a form similar to that of the standard survival result, but with the cause-specific hazard of interest replacing the all-causes hazard. We show that this fact is not a coincidence, but can be derived from a general Hadamard differentiation result. We discuss a simplified proof and extensions of the approach to more complex multistate models. As a further consequence, we find that the bootstrap works. Copyright 2008, Oxford University Press.

Date: 2008
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