Verweij P J, Van Houwelingen H C
Department of Medical Statistics, Leiden University, The Netherlands.
Stat Med. 1994;13(23-24):2427-36. doi: 10.1002/sim.4780132307.
In a Cox regression model, instability of the estimated regression coefficients can be reduced by maximizing a penalized partial log-likelihood, where a penalty function of the regression coefficients is substracted from the partial log-likelihood. In this paper, we choose the optimal weight of the penalty function by maximizing the predictive value of the model, as measured by the crossvalidated partial log-likelihood. Our methods are illustrated by a study of ovarian cancer survival and by a study of centre-effects in kidney graft survival.
在Cox回归模型中，通过最大化惩罚偏对数似然可以降低估计回归系数的不稳定性，其中从偏对数似然中减去回归系数的惩罚函数。在本文中，我们通过最大化模型的预测值（以交叉验证的偏对数似然衡量）来选择惩罚函数的最优权重。我们的方法通过一项卵巢癌生存研究和一项肾移植生存中心效应研究进行了说明。
