论文标题
使用逆生存概率加权的可变选择
Variable Selection using Inverse Survival Probability Weighting
论文作者
论文摘要
在本文中，我们提出了两种可转换生存时间检查信息的可变选择方法，例如限制的平均生存时间。为了调整审查的影响，我们考虑了有事件的受试者的生存率加权（ISPW）。我们得出了至少绝对的收缩和选择算子（LASSO）型变量选择方法，该方法考虑了平方损耗的反度加权，以及信息标准型变量选择方法，该方法适用于生存率的逆权加权，以使每个密度函数在可能性功能中的功能函数的功率函数。我们证明了ISPW拉索估计器的一致性和最大ISPW可能性估计器。 ISPW拉索和ISPW信息标准的性能是通过具有六个方案的仿真研究评估的，然后使用来自两项临床研究的数据证明了它们的可变选择能力。结果证实ISPW拉索和ISPW的可能性函数可产生良好的估计精度和一致的变量选择。我们得出的结论是，我们提出的两种方法是有用的变量选择工具，用于调整审查信息以进行生存时间分析。
In this paper, we propose two variable selection methods for adjusting the censoring information for survival times, such as the restricted mean survival time. To adjust for the influence of censoring, we consider an inverse survival probability weighting (ISPW) for subjects with events. We derive a least absolute shrinkage and selection operator (lasso)-type variable selection method, which considers an inverse weighting for of the squared losses, and an information criterion-type variable selection method, which applies an inverse weighting of the survival probability to the power of each density function in the likelihood function. We prove the consistency of the ISPW lasso estimator and the maximum ISPW likelihood estimator. The performance of the ISPW lasso and ISPW information criterion are evaluated via a simulation study with six scenarios, and then their variable selection ability is demonstrated using data from two clinical studies. The results confirm that ISPW lasso and the ISPW likelihood function produce good estimation accuracy and consistent variable selection. We conclude that our two proposed methods are useful variable selection tools for adjusting the censoring information for survival time analyses.
