SURVIVAL ANALYSIS WITH MEDIAN REGRESSION-MODELS
SURVIVAL ANALYSIS WITH MEDIAN REGRESSION-MODELS
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DOI：
10.2307/2291141
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发表时间：
1995-03-01
影响因子：
3.7
通讯作者：
WEI, LJ
中科院分区：
文献类型：
--
作者：
YING, Z;JUNG, SH;WEI, LJ
中位数是长尾生存分布中心的简单且有意义的度量。为了检查协变量对生存的影响，通常均值回归模型的自然替代方法是对故障时间变量的中值进行回归或其对协变量的变换。在本文中，我们提出半参数程序来对此类中值回归模型进行推断，并可能进行删失观察。我们的建议可以使用模拟退火算法有效地实现。进行数值研究以显示新程序相对于一些最近开发的加速失效时间模型方法的优势，加速失效时间模型是生存分析中的一种特殊类型的平均回归模型。文章中讨论的建议通过肺癌数据集进行了说明。
The median is a simple and meaningful measure for the center of a long-tailed survival distribution. To examine the covariate effects on survival, a natural alternative to the usual mean regression model is to regress the median of the failure time variable or a transformation thereof on the covariates. In this article we propose semiparametric procedures to make inferences for such median regression models with possibly censored observations. Our proposals can be implemented efficiently using a simulated annealing algorithm. Numerical studies are conducted to show the advantage of the new procedures over some recently developed methods for the accelerated failure time model, a special type of mean regression models in the survival analysis. The proposals discussed in the article are illustrated with a lung cancer data set.