Chen Ling, Feng Yanqin, Sun Jianguo
Division of Biostatistics, Washington University School of Medicine, Campus Box 8067, 660 S. Euclid Ave, St. Louis, MO, 63110, USA.
School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, China.
Lifetime Data Anal. 2017 Oct;23(4):651-670. doi: 10.1007/s10985-016-9384-x. Epub 2016 Oct 19.
This paper discusses regression analysis of clustered failure time data, which occur when the failure times of interest are collected from clusters. In particular, we consider the situation where the correlated failure times of interest may be related to cluster sizes. For inference, we present two estimation procedures, the weighted estimating equation-based method and the within-cluster resampling-based method, when the correlated failure times of interest arise from a class of additive transformation models. The former makes use of the inverse of cluster sizes as weights in the estimating equations, while the latter can be easily implemented by using the existing software packages for right-censored failure time data. An extensive simulation study is conducted and indicates that the proposed approaches work well in both the situations with and without informative cluster size. They are applied to a dental study that motivated this study.
本文讨论聚类失效时间数据的回归分析，这类数据是在从聚类中收集感兴趣的失效时间时出现的。特别地，我们考虑感兴趣的相关失效时间可能与聚类大小有关的情况。为了进行推断，当感兴趣的相关失效时间来自一类加性变换模型时，我们提出了两种估计方法，基于加权估计方程的方法和基于聚类内重抽样的方法。前者在估计方程中使用聚类大小的倒数作为权重，而后者可以通过使用现有的用于右删失失效时间数据的软件包轻松实现。我们进行了广泛的模拟研究，结果表明所提出的方法在有无信息性聚类大小的情况下都表现良好。它们被应用于一项激发本研究的牙科研究。
