Induced smoothing for rank regression with censored survival times
Induced smoothing for rank regression with censored survival times
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DOI：
10.1002/sim.2576
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发表时间：
2007-02-20
影响因子：
2
通讯作者：
Wang, You-Gan
中科院分区：
文献类型：
--
作者：
Brown, B. M.;Wang, You-Gan
将加权排名回归应用于审查生存数据的加速失效时间模型已成功地产生渐近正态估计和灵活的加权方案，以提高统计效率。然而，对于仅一种简单的加权方案（Gehan 或 Wilcoxon 权重）来说，估计方程保证在参数分量中是单调的，即使在这种情况下也是阶跃函数，需要等效的线性规划来进行计算。缺乏平滑度使得标准误差或协方差矩阵估计变得更加困难。诱导平滑技术克服了涉及单调但纯跳跃估计方程（包括传统的秩回归）的各种问题中的这些困难。本文将诱导平滑应用于加速失效时间模型的 Gehan-Wilcoxon 加权秩回归，对于受审查的生存时间数据的更困难情况，其中排列参数的不适用需要一种估计函数零方差的新方法。获得平滑的单调参数估计和快速、可靠的标准误差或协方差矩阵估计。版权所有 (c) 2006 John Wiley & Sons, Ltd.
Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained. Copyright (c) 2006 John Wiley & Sons, Ltd.