Robust estimation for the Cox regression model based on trimming

被引：17

作者：

Farcomeni, Alessio ^{[2
,3
]}

Viviani, Sara ^{[1
,4
]}

机构：

[1] Univ Roma La Sapienza, Dept Stat, Rome, Italy

[2] Univ Roma La Sapienza, Dept Publ Hlth & Infect Dis, Rome, Italy

[3] Univ Hawaii, Dept Publ Hlth Sci, Honolulu, HI 96822 USA

[4] Univ Hawaii, Sch Nursing & Dent Hyg, Honolulu, HI 96822 USA

来源：

BIOMETRICAL JOURNAL | 2011年 / 53卷 / 06期

关键词：

Cox model; Hepatic encephalopathy; Outliers; Robustness; Trimming; RESIDUALS; DIAGNOSTICS;

D O I：

10.1002/bimj.201100008

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis-type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties of the approach, which is illustrated and compared through simulations. We finally fit the model on an original and on a benchmark data set.

引用

页码：956 / 973

页数：18

共 46 条

[1] COX REGRESSION-MODEL FOR COUNTING-PROCESSES - A LARGE SAMPLE STUDY [J].