论文标题
共享的加权林德利脆弱模型用于集群故障时间数据
The shared weighted Lindley frailty model for cluster failure time data
论文作者
论文摘要
本文的主要目标是基于加权林德利（WL）分布引入一种新颖的脆弱模型，用于建模群集生存数据。我们研究了提出的模型的统计特性。特别是，未观察到的异质性的量直接在弱分布（例如伽玛和逆高斯脆弱模型）的方差上进行了参数化。研究了WL脆弱模型的参数和半参数版本。为参数估计提出了一种简单的期望最大化（EM）算法。进行了仿真研究以评估其有限样本性能。最后，我们将提出的模型应用于实际数据集，以分析被诊断为结直肠癌的患者进行手术时间的时间，并将我们的结果与本应用程序中的经典脆弱模型进行比较，这表明了所提出的模型的优越性。我们实现了一个R软件包，该软件包包括估算基于EM-Algorithm的拟议模型的估计。
The primary goal of this paper is to introduce a novel frailty model based on the weighted Lindley (WL) distribution for modeling clustered survival data. We study the statistical properties of the proposed model. In particular, the amount of unobserved heterogeneity is directly parameterized on the variance of the frailty distribution such as gamma and inverse Gaussian frailty models. Parametric and semiparametric versions of the WL frailty model are studied. A simple expectation-maximization (EM) algorithm is proposed for parameter estimation. Simulation studies are conducted to evaluate its finite sample performance. Finally, we apply the proposed model to a real data set to analyze times after surgery in patients diagnosed with colorectal cancer and compare our results with classical frailty models carried out in this application, which shows the superiority of the proposed model. We implement an R package that includes estimation for fitting the proposed model based on the EM-algorithm.
