Nonparametric estimation of cause-specific cross hazard ratio with bivariate competing risks data

被引：29

作者：

Cheng, Yu ^{[1
]}

Fine, Jason P. ^{[2
,3
]}

机构：

[1] Univ Pittsburgh, Dept Stat, Pittsburgh, PA 15260 USA

[2] Univ Wisconsin, Dept Stat, Madison, WI 53706 USA

[3] Univ Wisconsin, Dept Biostat & Med Informat, Madison, WI 53706 USA

来源：

BIOMETRIKA | 2008年 / 95卷 / 01期

关键词：

bivariate hazard function; cross ratio; dependent censoring; empirical processes theory; rank correlation;

D O I：

10.1093/biomet/asm089

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We propose an alternative representation of the cause-specific cross hazard ratio for bivariate competing risks data. The representation leads to a simple plug-in estimator, unlike an existing ad hoc procedure. The large sample properties of the resulting inferences are established. Simulations and a real data example demonstrate that the proposed methodology may substantially reduce the computational burden of the existing procedure, while maintaining similar efficiency properties.

引用

页码：233 / 240

页数：8

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