A Cox-Aalen Model for Interval-censored Data
A Cox-Aalen Model for Interval-censored Data
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DOI：
10.1111/sjos.12113
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发表时间：
2015-06-01
影响因子：
1
通讯作者：
Cook, Richard J.
中科院分区：
文献类型：
--
作者：
Boruvka, Audrey;Cook, Richard J.
Cox-Aalen模型是通过用协变量依赖性Aalen模型替换众所周知的考克斯模型中的基线风险函数获得的，该模型允许固定和动态协变量效应。在本文中，我们研究的最大似然估计的Cox-Aalen模型的区间删失失效时间与固定的协变量。由此产生的估计全局收敛到真理慢于参数率，但其有限维分量是渐近有效的。数值研究表明，通过约束牛顿方法的估计表现良好的有限样本性质和处理时间的中到大样本与几个协变量。最后，我们应用所提出的方法来评估银屑病关节炎疾病进展的危险因素。
The Cox-Aalen model, obtained by replacing the baseline hazard function in the well-known Cox model with a covariate-dependent Aalen model, allows for both fixed and dynamic covariate effects. In this paper, we examine maximum likelihood estimation for a Cox-Aalen model based on interval-censored failure times with fixed covariates. The resulting estimator globally converges to the truth slower than the parametric rate, but its finite-dimensional component is asymptotically efficient. Numerical studies show that estimation via a constrained Newton method performs well in terms of both finite sample properties and processing time for moderate-to-large samples with few covariates. We conclude with an application of the proposed methods to assess risk factors for disease progression in psoriatic arthritis.