A wild bootstrap approach for the Aalen-Johansen estimator.

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ID: 60600
2018
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Abstract
We suggest a wild bootstrap resampling technique for nonparametric inference on transition probabilities in a general time-inhomogeneous Markov multistate model. We first approximate the limiting distribution of the Nelson-Aalen estimator by repeatedly generating standard normal wild bootstrap variates, while the data is kept fixed. Next, a transformation using a functional delta method argument is applied. The approach is conceptually easier than direct resampling for the transition probabilities. It is used to investigate a non-standard time-to-event outcome, currently being alive without immunosuppressive treatment, with data from a recent study of prophylactic treatment in allogeneic transplanted leukemia patients. Due to non-monotonic outcome probabilities in time, neither standard survival nor competing risks techniques apply, which highlights the need for the present methodology. Finite sample performance of time-simultaneous confidence bands for the outcome probabilities is assessed in an extensive simulation study motivated by the clinical trial data. Example code is provided in the web-based Supplementary Materials.
Reference Key
bluhmki2018abiometrics Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bluhmki, Tobias;Schmoor, Claudia;Dobler, Dennis;Pauly, Markus;Finke, Juergen;Schumacher, Martin;Beyersmann, Jan;
Journal biometrics
Year 2018
DOI
10.1111/biom.12861
URL
Keywords
survival analysis blood cancer graft-versus-host-disease illness-death model resampling time-dependent covariate

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