Direct Bootstrapping and Permuting of Observations fail for Aalen-Johansen Estimators
Abstract
This article provides rigorous proofs that neither Efron's bootstrap nor permutation techniques can be applied directly to the observations to construct consistent resampling tests for transition probability matrices of finite-state Markov processes. These methods modify the covariance functions of the limiting distributions of the involved Aalen-Johansen processes, even in the case of fully observable individuals. An example for the failure of these resampling methods is given by cumulative incidence functions in competing risks set-ups.
Keywords
Cite
@article{arxiv.1408.2417,
title = {Direct Bootstrapping and Permuting of Observations fail for Aalen-Johansen Estimators},
author = {Dennis Dobler},
journal= {arXiv preprint arXiv:1408.2417},
year = {2014}
}
Comments
This paper has been withdrawn by the author. The Scandinavian Journal of Statistics article Conditional Studentized Survival Tests for Randomly Censored Models by A. Janssen and C.-D. Mayer (2001) already shows that the analyzed resampling procedures alter the covariance structure in the simpler survival setup, thus letting my results become trivial