We address the testing problem of proportional hazards in the two-sample survival setting allowing right censoring, i.e., we check whether the famous Cox model is underlying. Although there are many test proposals for this problem, only a few papers suggest how to improve the performance for small sample sizes. In this paper, we do exactly this by carrying out our test as a permutation as well as a wild bootstrap test. The asymptotic properties of our test, namely asymptotic exactness under the null and consistency, can be transferred to both resampling versions. Various simulations for small sample sizes reveal an actual improvement of the empirical size and a reasonable power performance when using the resampling versions. Moreover, the resampling tests perform better than the existing tests of Gill and Schumacher and Grambsch and Therneau . The tests’ practical applicability is illustrated by discussing real data examples.

中文翻译：

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右删失下比例风险的 Bootstrap 和置换秩检验。

我们解决了允许右删失的双样本生存设置中比例风险的测试问题，即我们检查著名的 Cox 模型是否是潜在的。虽然针对这个问题有很多测试建议，但只有少数论文提出了如何提高小样本量的性能。在本文中，我们通过将我们的测试作为置换和狂野的引导测试来实现这一点。我们测试的渐近特性，即零和一致性下的渐近精确性，可以转移到两个重采样版本。小样本大小的各种模拟揭示了使用重采样版本时经验大小的实际改进和合理的功效。此外，重采样测试的性能优于 Gill 和 Schumacher 以及 Grambsch 和 Therneau 的现有测试。