Empirical copulas for consecutive survival data
Empirical copulas for consecutive survival data
复制标题
连续生存数据的经验联结函数
DOI：
10.1007/s11749-013-0339-1
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
W. Stute
中科院分区：
文献类型：
--
作者：
E. Strzalkowska;W. Stute
在对医疗数据的分析中，整个生命周期常常被分成若干片段，以表征慢性病发展的各个阶段。本文给出了两个具有截断和右审查的连续生存数据的非参数联结函数估计。我们还讨论了将斯皮尔曼的Rho和肯德尔的Tau扩展到目前的情况。
In the analysis of medical data the whole lifetime is often split into pieces characterizing the various stages in the development of a chronical disease. In this paper we provide a nonparametric copula function estimator for two consecutive survival data which are subject to truncation and right censorship. We also discuss an extension of Spearman’s Rho and Kendall’s Tau to the present situation.