Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data
Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data
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DOI：
10.1093/biomet/92.1.1
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发表时间：
2005-03-01
期刊：
影响因子：
2.7
通讯作者：
Prentice, R
中科院分区：
文献类型：
--
作者：
Yang, S;Prentice, R
当两条生存曲线交叉时，对双样本生存数据进行半参数建模的标准方法是不合适的。我们引入了一个两样本模型，该模型考虑了生存曲线的交叉。模型的两个标量参数分别被解释为短期危险比和长期危险比。时变危险比由两个标量参数和一个未指定的基线分布半参数表示。新模型包括考克斯模型和比例赔率模型作为子模型。作为推断，我们使用伪极大似然方法，它可以通过一些简单的估计方程来表示，类似于COX模型的最大部分似然估计，它提供了一致的和渐近正态的估计。仿真研究表明，在中等样本量的情况下，该估计器表现良好。我们还用一个实际数据实例说明了这些方法。新模型可以很容易地扩展到回归设置。
Standard approaches to semiparametric modelling of two-sample survival data are not appropriate when the two survival curves cross. We introduce a two-sample model that accommodates crossing survival curves. The two scalar parameters of the model have the interpretations of being the short-term and long-term hazard ratios respectively. The time-varying hazard ratio is expressed semiparametrically by the two scalar parameters and an unspecified baseline distribution. The new model includes the Cox model and the proportional odds model as submodels. For inference we use a pseudo maximum likelihood approach that can be expressed via some simple estimating equations, analogous to that for the maximum partial likelihood estimator of the Cox model, that provide consistent and asymptotically normal estimators. Simulation studies show that the estimators perform well for moderate sample sizes. We also illustrate the methods with a real-data example. The new model can be extended easily to the regression setting.