期刊
STATISTICS IN MEDICINE
卷 28, 期 22, 页码 2748-2768出版社
WILEY
DOI: 10.1002/sim.3640
关键词
competing risks; survival analysis; cumulative incidence function; confidence interval; semiparametric model
类别
资金
- NSF [DMS-0304922, DMS-0604576]
- NIH [2 RO1 A1054165-04]
- Intramural research program of Eunice Kennedy Shriver National Institute of Child Health and Human Development
In analyzing competing risks data, a quantity of considerable interest is the cumulative incidence function. Often, the effect of covariates on the cumulative incidence function is modeled via the proportional hazards model for the cause-specific hazard function. As the proportionality assumption may be too restrictive in practice, we consider an alternative more flexible semiparametric additive hazards model of (Biometrika 1994; 81:501-514) for the cause-specific hazard. This model specifies the effect of covariates on the cause-specific hazard to be additive as well as allows the effect of some covariates to be fixed and that of others to be time varying. We present an approach for constructing confidence intervals as well as confidence bands for the cause-specific cumulative incidence function of subjects with given values of the covariates. Furthermore, we also present an approach for constructing confidence intervals and confidence bands for comparing two cumulative incidence functions given values of the covariates. The finite sample property of the proposed estimators is investigated through simulations. We conclude our paper with an analysis of the well-known malignant melanoma data using our method. Published in 2009 by John Wiley & Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据