Sensitivity analysis for informative censoring in parametric survival models: an evaluation of the method
Sensitivity analysis for informative censoring in parametric survival models: an evaluation of the method
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发表时间：
2017
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通讯作者：
Panagiotis Bompotas;A. Kimber;Stefanie Biedermann
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作者：
Panagiotis Bompotas;A. Kimber;Stefanie Biedermann
在 Siannis、Copas 和 Lu 在 Biostatistics 上发表的一篇论文中，作者提出并研究了参数生存分析中信息审查的敏感性分析。更具体地说，他们引入了一个参数模型，该模型允许故障和审查过程之间以参数增量形式存在依赖性，参数增量可以被认为是测量两个过程之间依赖性的大小，以及测量这种依赖性模式的偏差函数。基于该模型，对于较小的 delta 值，他们还推导了简化的封闭式表达式（近似值），用于模型相关参数的敏感性分析。从那时起，这种方法的一些扩展也出现在文献中。本文讨论了有关上述方法的一些理论问题。然后报告了广泛的模拟研究的结果，这表明了所提出的敏感性分析的一些缺点，特别是在存在干扰参数的情况下。
In a paper by Siannis, Copas and Lu in Biostatistics, the authors proposed and studied a sensitivity analysis for informative censoring in parametric survival analysis. More specifically, they introduced a parametric model that allows for dependence between the failure and censoring processes in terms of a parameter delta which can be thought of as measuring the size of the dependence between the two processes, and a bias function that measures the pattern of this dependence. Based on this model, for small values of delta, they also derived simplified closed form expressions (approximations) for the sensitivity analysis of the associated parameters of the model. Since then, some extensions of this approach have also appeared in the literature. In this paper, some theoretical issues concerning the above approach are discussed. Then the results of an extensive simulation study are reported, which indicate some shortcomings of the proposed sensitivity analysis, particularly in the presence of nuisance parameters.