FURTHER RESULTS ON THE NONPARAMETRIC LINEAR-REGRESSION MODEL IN SURVIVAL ANALYSIS
FURTHER RESULTS ON THE NONPARAMETRIC LINEAR-REGRESSION MODEL IN SURVIVAL ANALYSIS
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DOI：
10.1002/sim.4780121705
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发表时间：
1993-09-15
影响因子：
2
通讯作者：
AALEN, OO
中科院分区：
文献类型：
--
作者：
AALEN, OO
本文进一步发展了生存分析中的非参数线性回归模型。研究了三个主题。首先，鞅残差，最初开发的考克斯模型，介绍了我们的线性模型。他们的理论是发达国家，他们被证明是有用的判断拟合优度。本文的第二个重点是使用自举复制来判断累积回归图的哪些特征可能反映真实的现象，而不仅仅是随机变化。特别是，这适用于判断协变量的影响是否随时间消失，这是一个没有正式测试存在的问题。第三个主题是回归函数本身的密度类型或核估计。这可能比累积图提供更直接的信息。该方法说明了口咽癌的临床试验的数据，并通过移植肾患者的生存时间。
This paper gives further developments of a non-parametric linear regression model in survival analysis. Three subjects are studied. First, martingale residuals, originally developed for the Cox model, are introduced for our linear model. Their theory is developed and they are shown to be useful for judging goodness of fit. The second focus of the paper is on the use of bootstrap replications to judge which features of the cumulative regression plots are likely to reflect real phenomena and not merely random variation. In particular, this is applied to judging whether the effect of a covariate disappears over time, a problem for which no formal test exists. The third subject is density type, or kernel, estimation of the regression functions themselves. This might give more direct information than the cumulative plots. The approaches are illustrated by data from a clinical trial of carcinoma of the oropharynx, and by survival times of grafts in renal patients.