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Post‐selection inference for the Cox model with interval‐censored data

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  • Jianrui Zhang
  • Chenxi Li
  • Haolei Weng

Abstract

We develop a postselection inference method for the Cox proportional hazards model with interval‐censored data, which provides asymptotically valid p‐values and confidence intervals conditional on the model selected by lasso. The method is based on a pivotal quantity that is shown to converge to a uniform distribution under local parameters. Our method involves estimation of the efficient information matrix, for which several approaches are proposed with proof of their consistency. Thorough simulation studies show that our method has satisfactory performance in samples of modest sizes. The utility of the method is illustrated via an application to an Alzheimer's disease study.

Suggested Citation

  • Jianrui Zhang & Chenxi Li & Haolei Weng, 2025. "Post‐selection inference for the Cox model with interval‐censored data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 52(2), pages 710-735, June.
    • Handle: RePEc:bla:scjsta:v:52:y:2025:i:2:p:710-735
    DOI: 10.1111/sjos.12768
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