Statistical analysis of bivariate failure time data with Marshall-Olkin Weibull models

被引:11
|
作者
Li, Yang [1 ]
Sun, Jianguo [1 ]
Song, Shuguang [2 ]
机构
[1] Univ Missouri, Dept Stat, Columbia, MO 65211 USA
[2] Boeing Co, Support & Serv Technol, Chicago, IL USA
关键词
Bivariate failure time data; Parametric estimation; Marginal approach; Weibull models; KAPLAN-MEIER ESTIMATE; EXPONENTIAL-DISTRIBUTION; TAIL DEPENDENCE; SURVIVAL-DATA; EM ALGORITHM; DISTRIBUTIONS; PARAMETERS; COPULAS; PLANE;
D O I
10.1016/j.csda.2011.12.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper discusses parametric analysis of bivariate failure time data, which often occur in medical studies among others. For this, as in the case of univariate failure time data, exponential and Weibull models are probably the most commonly used ones. However, it is surprising that there seem no general estimation procedures available for fitting the bivariate Weibull model to bivariate right-censored failure time data except some methods for special situations. We present and investigate two general but simple estimation procedures, one being a graphical approach and the other being a marginal approach, for the problem. An extensive simulation study is conducted to assess the performances of the proposed approaches and shows that they work well for practical situations. An illustrative example is provided. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:2041 / 2050
页数:10
相关论文
共 50 条