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Wild bootstrap logrank tests with broader power functions for testing superiority

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  • Ditzhaus, Marc
  • Pauly, Markus

Abstract

A novel wild bootstrap procedure is introduced for testing superiority in unpaired two-sample survival data. Combining classical weighted logrank tests yields a procedure with broader power behavior. Right censoring within the data is allowed and may differ between the groups. The tests are shown to be asymptotically exact under the null, consistent for fixed alternatives and admissible for a larger set of local alternatives. Beside these asymptotic properties, the procedures’ strengths are also illustrated in simulations for finite sample sizes. The tests are implemented in the novel R-package mdir.logrank and its application is demonstrated in an empirical example.

Suggested Citation

  • Ditzhaus, Marc & Pauly, Markus, 2019. "Wild bootstrap logrank tests with broader power functions for testing superiority," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 1-11.
    • Handle: RePEc:eee:csdana:v:136:y:2019:i:c:p:1-11
    DOI: 10.1016/j.csda.2019.02.001
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    References listed on IDEAS

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    1. Tobias Bluhmki & Claudia Schmoor & Dennis Dobler & Markus Pauly & Juergen Finke & Martin Schumacher & Jan Beyersmann, 2018. "A wild bootstrap approach for the Aalen–Johansen estimator," Biometrics, The International Biometric Society, vol. 74(3), pages 977-985, September.
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    1. Marc Ditzhaus & Jon Genuneit & Arnold Janssen & Markus Pauly, 2023. "CASANOVA: Permutation inference in factorial survival designs," Biometrics, The International Biometric Society, vol. 79(1), pages 203-215, March.

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