Cook R J, Lawless J F, Nadeau C
Department of Statistics and Actuarial Science, University of Waterloo, Canada.
Biometrics. 1996 Jun;52(2):557-71.
Robust nonparametric tests are considered for use in longitudinal studies in which the response of interest is a recurrent event. The tests are robust in the sense that they do not rely on distributional assumptions regarding the processes generating the events. The methods we describe are presented in the context of a clinical trial with attention initially directed at the two-sample problem in which a single experimental treatment is compared to a control. We investigate a family of generalized pseudo-score statistics (Lawless and Nadeau, 1995, Technometrics 37, 158-168) in which weight functions may be chosen to generate tests sensitive to various types of departure from the null hypothesis that the mean functions for the treatment and control groups are identical. All tests we consider are evaluated by simulation with respect to the type I error rate and power under a variety of practical scenarios. An application involving data from a kidney transplant study illustrates these procedures. For trials with multiple treatment arms, we generalize these approaches and indicate test statistics appropriate for unstructured alternatives and tests based on linear contrasts of the treatment-specific mean functions. Extensions of this methodology for stratified designs are also indicated.
对于感兴趣的响应为复发事件的纵向研究，考虑使用稳健的非参数检验。这些检验具有稳健性，因为它们不依赖于关于生成事件过程的分布假设。我们所描述的方法是在一项临床试验的背景下提出的，最初关注的是将单一实验治疗与对照进行比较的两样本问题。我们研究了一族广义伪得分统计量（Lawless和Nadeau，1995年，《技术计量学》37卷，第158 - 168页），其中可以选择权重函数来生成对治疗组和对照组均值函数相同的原假设的各种偏离类型敏感的检验。我们考虑的所有检验都是通过模拟在各种实际情况下评估其一类错误率和功效。一个涉及肾移植研究数据的应用说明了这些程序。对于具有多个治疗组的试验，我们推广这些方法，并指出适用于非结构化备择假设的检验统计量以及基于特定治疗均值函数线性对比的检验。还指出了这种方法在分层设计中的扩展。
