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A discontinuity adjustment for subdistribution function confidence bands applied to right-censored competing risks data. (English) Zbl 1373.62488
Summary: The wild bootstrap is the resampling method of choice in survival analytic applications. Theoretic justifications typically rely on the assumption of existing intensity functions which is equivalent to an exclusion of ties among the event times. However, such ties are omnipresent in practical studies. It turns out that the wild bootstrap should only be applied in a modified manner that corrects for altered limit variances and emerging dependencies. This again ensures the asymptotic exactness of inferential procedures. An analogous necessity is the use of the Greenwood-type variance estimator for Nelson-Aalen estimators which is particularly preferred in tied data regimes. All theoretic arguments are transferred to bootstrapping Aalen-Johansen estimators for cumulative incidence functions in competing risks. An extensive simulation study as well as an application to real competing risks data of male intensive care unit patients suffering from pneumonia illustrate the practicability of the proposed technique.

62N03 Testing in survival analysis and censored data
62G09 Nonparametric statistical resampling methods
62G15 Nonparametric tolerance and confidence regions
62P10 Applications of statistics to biology and medical sciences; meta analysis
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