On functional misspecification of covariates in the Cox regression model
On functional misspecification of covariates in the Cox regression model
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DOI：
10.1093/biomet/88.2.572
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发表时间：
2001-06-01
期刊：
影响因子：
2.7
通讯作者：
Schumacher, M
中科院分区：
文献类型：
--
作者：
Gerds, TA;Schumacher, M
讨论了用COX回归模型分析截尾生存数据时的模型误指定问题。协变量效应的极大偏似然估计在模型错误指定下服从渐近正态分布(Lin&wei，1989)。在一般框架下考虑了协变量的函数形式错误的情形，并得到了Breslow(1972)估计的极限。此外，我们还给出了极大偏似然估计的渐近方差的显式表达式。最大偏似然估计器和通常的方差估计器的误差的数值是对于单个相关协变量的功能性错误指定并且查看表示处理或类似的第一因素对于辅助协变量测量的功能性错误合并的影响。在后一种情况下，我们分析了协变量之间相关性的影响。
Model misspecification is discussed for the analysis of censored survival data with the Cox regression model. The maximum partial likelihood estimator for covariate effects has an asymptotic normal distribution under model misspecification (Lin & Wei, 1989). Situations where the assumed functional form for covariates is wrong are considered in a general framework in which we also derive the limit of Breslow's (1972) estimator. Furthermore, we give explicit expressions for the asymptotic variance of the maximum partial likelihood estimator. Numerical values for the errors of the maximum partial likelihood estimator and of the usual variance estimator are obtained for functional misspecification of a single relevant covariate and looking at the effect of a first factor, representing treatment or something similar, for functional wrong incorporation of auxiliary covariate measurements. In the latter situations we analyse the impact of dependence between the covariates.