Empirical Likelihood Inference for the Cox Model with Time-dependent Coefficients via Local Partial Likelihood

被引:21
作者
Sun, Yanqing [1 ]
Sundaram, Rajeshwari [2 ]
Zhao, Yichuan [3 ]
机构
[1] Univ N Carolina, Dept Math & Stat, Charlotte, NC 28223 USA
[2] NICHHD, Div Epidemiol Stat & Prevent Res, NIH, Bethesda, MD USA
[3] Georgia State Univ, Dept Math & Stat, Atlanta, GA 30303 USA
关键词
empirical likelihood; empirical processes; Gaussian multiplier calibration; local partial likelihood; pointwise and simultaneous confidence regions; bands; proportional hazards model; strong approximations; CONFIDENCE BANDS; REGRESSION-MODEL; SEMIPARAMETRIC ANALYSIS; SURVIVAL PROBABILITIES; TRANSFORMATION MODELS; INTERVALS;
D O I
10.1111/j.1467-9469.2008.00634.x
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
The Cox model with time-dependent coefficients has been studied by a number of authors recently. In this paper, we develop empirical likelihood (EL) pointwise confidence regions for the time-dependent regression coefficients via local partial likelihood smoothing. The EL simultaneous confidence bands for a linear combination of the coefficients are also derived based on the strong approximation methods. The EL ratio is formulated through the local partial log-likelihood for the regression coefficient functions. Our numerical studies indicate that the EL pointwise/simultaneous confidence regions/bands have satisfactory finite sample performances. Compared with the confidence regions derived directly based on the asymptotic normal distribution of the local constant estimator, the EL confidence regions are overall tighter and can better capture the curvature of the underlying regression coefficient functions. Two data sets, the gastric cancer data and the Mayo Clinic primary biliary cirrhosis data, are analysed using the proposed method.
引用
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页码:444 / 462
页数:19
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