SEMIPARAMETRIC REGRESSION WITH TIME-DEPENDENT COEFFICIENTS FOR FAILURE TIME DATA ANALYSIS

被引：0
|
作者：
Yu, Zhangsheng [1 ]
Lin, Xihong [2 ]
机构：
[1] Indiana Univ, Sch Med, Div Biostat, Indianapolis, IN 46202 USA
[2] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
来源：
STATISTICA SINICA | 2010年 / 20卷 / 02期
关键词：
Clustered survival data; efficiency; estimating equation; kernel smoothing; marginal model; profile likelihood; sandwich estimator; LOCAL PARTIAL-LIKELIHOOD; ESTIMATING EQUATIONS; HAZARD RATIO; MODEL;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We propose a working independent profile likelihood method for the semiparametric time-varying coefficient model with correlation. Kernel likelihood is used to estimate time-varying coefficients. Profile likelihood for the parametric coefficients is formed by plugging in the nonparametric estimator. For independent data, the estimator is asymptotically normal and achieves the asymptotic semiparametric efficiency bound. We evaluate the performance of proposed nonparametric kernel estimator and the profile estimator, and apply the method to the western Kenya parasitemia data.
引用
收藏
页码：853 / 869
页数：17
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