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Consistent covariances estimation for stratum imbalances under minimization method for covariate‐adaptive randomization

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  • Zixuan Zhao
  • Yanglei Song
  • Wenyu Jiang
  • Dongsheng Tu

Abstract

Pocock and Simon's minimization method is a popular approach for covariate‐adaptive randomization in clinical trials. Valid statistical inference with data collected under the minimization method requires the knowledge of the limiting covariance matrix of within‐stratum imbalances, whose existence is only recently established. In this work, we propose a bootstrap‐based estimator for this limit and establish its consistency, in particular, by Le Cam's third lemma. As an application, we consider in simulation studies adjustments to existing robust tests for treatment effects with survival data by the proposed estimator. It shows that the adjusted tests achieve a size close to the nominal level, and unlike other designs, the robust tests without adjustment may have an asymptotic size inflation issue under the minimization method.

Suggested Citation

  • Zixuan Zhao & Yanglei Song & Wenyu Jiang & Dongsheng Tu, 2024. "Consistent covariances estimation for stratum imbalances under minimization method for covariate‐adaptive randomization," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(2), pages 861-890, June.
  • Handle: RePEc:bla:scjsta:v:51:y:2024:i:2:p:861-890
    DOI: 10.1111/sjos.12703
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    References listed on IDEAS

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    1. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2018. "Inference Under Covariate-Adaptive Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1784-1796, October.
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