Martinussen Torben, Pipper Christian B
Department of Natural Sciences, The Royal Veterinary and Agricultural University, Thorvaldsensvej 40, DK-1871 Frederiksberg C, Denmark.
Lifetime Data Anal. 2005 Mar;11(1):99-115. doi: 10.1007/s10985-004-5642-4.
Shared frailty models are of interest when one has clustered survival data and when focus is on comparing the lifetimes within clusters and further on estimating the correlation between lifetimes from the same cluster. It is well known that the positive stable model should be preferred to the gamma model in situations where the correlated survival data show a decreasing association with time. In this paper, we devise a likelihood based estimation procedure for the positive stable shared frailty Cox model, which is expected to obtain high efficiency. The proposed estimator is provided with large sample properties and also a consistent estimator of standard errors is given. Simulation studies show that the estimation procedure is appropriate for practical use, and that it is much more efficient than a recently suggested procedure. The suggested methodology is applied to a dataset concerning time to blindness for patients with diabetic retinopathy.
当存在聚类生存数据且关注点在于比较聚类内的生存时间以及进一步估计同一聚类中生存时间之间的相关性时,共享脆弱性模型就会受到关注。众所周知,在相关生存数据显示与时间呈递减关联的情况下,正稳定模型应优于伽马模型。在本文中,我们为正稳定共享脆弱性Cox模型设计了一种基于似然的估计程序,预期该程序能获得较高的效率。所提出的估计量具有大样本性质,并且还给出了标准误差的一致估计量。模拟研究表明,该估计程序适用于实际应用,并且比最近提出的一种程序效率高得多。所建议的方法应用于一个关于糖尿病视网膜病变患者失明时间的数据集。