Dobler Dennis, Pauly Markus
Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Institute of Statistics, Ulm University, Ulm, Germany.
Stat Methods Med Res. 2020 Feb;29(2):325-343. doi: 10.1177/0962280219831316. Epub 2019 Mar 5.
This paper introduces new effect parameters for factorial survival designs with possibly right-censored time-to-event data. In the special case of a two-sample design, it coincides with the concordance or Wilcoxon parameter in survival analysis. More generally, the new parameters describe treatment or interaction effects and we develop estimates and tests to infer their presence. We rigorously study their asymptotic properties and additionally suggest wild bootstrapping for a consistent and distribution-free application of the inference procedures. The small sample performance is discussed based on simulation results. The practical usefulness of the developed methodology is exemplified on a data example about patients with colon cancer by conducting one- and two-factorial analyses.
本文介绍了用于具有可能右删失的事件发生时间数据的析因生存设计的新效应参数。在双样本设计的特殊情况下，它与生存分析中的一致性或 Wilcoxon 参数一致。更一般地，新参数描述了治疗或交互效应，并且我们开发了估计和检验以推断它们的存在。我们严格研究了它们的渐近性质，并另外建议使用野生自助法来一致且无分布地应用推断程序。基于模拟结果讨论了小样本性能。通过进行单因素和双因素分析，以一个关于结肠癌患者的数据实例为例说明了所开发方法的实际用途。
