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Estimation in the Positive Stable Shared Frailty Cox Proportional Hazards Model

机译:正稳定共享脆弱脆弱Cox比例危害模型的估计

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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.
机译:当一个人拥有脆弱的生存数据并且关注于比较集群中的生命周期并进一步估计来自同一集群的生命周期之间的相关性时,共享的脆弱模型就会受到关注。众所周知,在相关生存数据显示与时间的关联性降低的情况下,应优先使用正稳定模型而不是伽马模型。在本文中,我们设计了一个基于似然估计的正稳定共享脆弱性Cox模型估计程序,有望获得较高的效率。所提出的估计器具有大的样本属性,并且给出了标准误差的一致估计器。仿真研究表明,估计程序适合于实际使用,并且比最近建议的程序更有效。所建议的方法已应用于有关糖尿病性视网膜病患者失明时间的数据集。

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