EMPIRICAL LIKELIHOOD FOR COX REGRESSION MODEL UNDER RANDOM CENSORSHIP
EMPIRICAL LIKELIHOOD FOR COX REGRESSION MODEL UNDER RANDOM CENSORSHIP
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DOI：
10.1081/sac-100001859
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发表时间：
2001-03
期刊：
影响因子：
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通讯作者：
G. Qin;Bing-Yi Jing
中科院分区：
文献类型：
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作者：
G. Qin;Bing-Yi Jing
在本文中，我们研究了当失效时间受到随机删失时考克斯回归模型的经验似然方法。定义了回归系数向量的经验似然比，并证明其极限分布是自由度为\(p\)的卡方分布。给出了一些模拟研究，以比较经验似然方法和正态近似方法。
In this paper we investigate the empirical likelihood method for Cox regression model when the failure times are subject to random censoring. An empirical likelihood ratio for the vector of regression coefficients is defined and it is shown that its limiting distribution is a chi-square distributions with p degrees of freedom. Some simulation studies are presented to compare the empirical likelihood method with the normal approximation method.