A New Semiparametric Estimation Method for Accelerated Hazard Model
A New Semiparametric Estimation Method for Accelerated Hazard Model
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DOI：
10.1111/j.1541-0420.2011.01592.x
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发表时间：
2011-12-01
期刊：
影响因子：
1.9
通讯作者：
Zhao, Ou
中科院分区：
文献类型：
--
作者：
Zhang, Jiajia;Peng, Yingwei;Zhao, Ou
加速危险模型已经提出十多年了。然而，其应用仍然非常有限，部分原因是现有半参数估计方法的复杂性。我们提出了一种新的半参数估计方法，该方法基于模型轮廓似然函数极限的核平滑近似。该方法可得到平滑的估计方程并且易于使用。该方法的估计被证明是一致的且渐近正态的。我们的数值研究表明，新方法比现有方法更有效。所提出的方法用于重新分析脑肿瘤治疗研究的数据。
The accelerated hazard model has been proposed for more than a decade. However, its application is still very limited, partly due to the complexity of the existing semiparametric estimation method. We propose a new semiparametric estimation method based on a kernel-smoothed approximation to the limit of a profile likelihood function of the model. The method leads to smooth estimating equations and is easy to use. The estimates from the method are proved to be consistent and asymptotically normal. Our numerical study shows that the new method is more efficient than the existing method. The proposed method is employed to reanalyze the data from a brain tumor treatment study.