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Cox回归中固定协变量的时间依赖性效应。

Time-dependent effects of fixed covariates in Cox regression.

作者信息

Verweij P J, van Houwelingen H C

机构信息

Department of Medical Statistics, Leiden University, The Netherlands.

出版信息

Biometrics. 1995 Dec;51(4):1550-6.

PMID:8589239
Abstract

A nonparametric modification is proposed for Cox's proportional hazards model (Cox, 1972, Journal of the Royal Statistical Society, Series B 34, 187-220), where the covariates are fixed, but their effects are allowed to vary in time. Parameters are introduced for the covariate effects at the (uncensored) survival times. Estimates are obtained by maximizing the penalized partial log-likelihood that arises if a penalty function of the first order differences of consecutive parameters is subtracted from the partial log-likelihood. The choice of the smoothing parameter, which determines the weight of the penalty, is based on Akaike's Information Criterion. The methods are illustrated in a set of ovarian cancer data and in a set of kidney transplantation data.

摘要

针对考克斯比例风险模型(考克斯,1972年,《皇家统计学会杂志》,B辑第34卷,第187 - 220页)提出了一种非参数修正方法,其中协变量是固定的,但它们的效应允许随时间变化。针对(未删失的)生存时间的协变量效应引入了参数。通过最大化惩罚后的偏对数似然来获得估计值,即从偏对数似然中减去连续参数一阶差分的惩罚函数。平滑参数的选择决定了惩罚的权重,它基于赤池信息准则。这些方法在一组卵巢癌数据和一组肾移植数据中得到了说明。

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