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A consistent version of distance covariance for right‐censored survival data and its application in hypothesis testing

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  • Dominic Edelmann
  • Thomas Welchowski
  • Axel Benner

Abstract

Distance covariance is a powerful new dependence measure that was recently introduced by Székely et al. and Székely and Rizzo. In this work, the concept of distance covariance is extended to measuring dependence between a covariate vector and a right‐censored survival endpoint by establishing an estimator based on an inverse‐probability‐of‐censoring weighted U‐statistic. The consistency of the novel estimator is derived. In a large simulation study, it is shown that induced distance covariance permutation tests show a good performance in detecting various complex associations. Applying the distance covariance permutation tests on a gene expression dataset from breast cancer patients outlines its potential for biostatistical practice.

Suggested Citation

  • Dominic Edelmann & Thomas Welchowski & Axel Benner, 2022. "A consistent version of distance covariance for right‐censored survival data and its application in hypothesis testing," Biometrics, The International Biometric Society, vol. 78(3), pages 867-879, September.
    • Handle: RePEc:bla:biomet:v:78:y:2022:i:3:p:867-879
    DOI: 10.1111/biom.13470
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