Farcomeni Alessio, Viviani Sara
Department of Public Health and Infectious Diseases, Sapienza - University of Rome, Italy.
Biom J. 2011 Nov;53(6):956-73. doi: 10.1002/bimj.201100008.
We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis-type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties of the approach, which is illustrated and compared through simulations. We finally fit the model on an original and on a benchmark data set.
我们提出了一种带有异常值的稳健Cox回归模型。该模型通过对部分似然贡献最小的部分进行修剪来拟合。为此，我们实施了一种Metropolis型最大化程序，并证明了其收敛到全局最优解。我们讨论了该方法的全局稳健性属性，并通过模拟进行了说明和比较。我们最终将该模型应用于一个原始数据集和一个基准数据集。
