A Cox-type regression model with change-points in the covariates

被引:0
|
作者
Uwe Jensen
Constanze Lütkebohmert
机构
[1] Universität Hohenheim,Institut für Angewandte Mathematik und Statistik
来源
Lifetime Data Analysis | 2008年 / 14卷
关键词
Survival analysis; Cox model; Change-point; Consistency; Asymptotic normality;
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学科分类号
摘要
We consider a Cox-type regression model with change-points in the covariates. A change-point specifies the unknown threshold at which the influence of a covariate shifts smoothly, i.e., the regression parameter may change over the range of a covariate and the underlying regression function is continuous but not differentiable. The model can be used to describe change-points in different covariates but also to model more than one change-point in a single covariate. Estimates of the change-points and of the regression parameters are derived and their properties are investigated. It is shown that not only the estimates of the regression parameters are \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\sqrt{n}}$$\end{document} -consistent but also the estimates of the change-points in contrast to the conjecture of other authors. Asymptotic normality is shown by using results developed for M-estimators. At the end of this paper we apply our model to an actuarial dataset, the PBC dataset of Fleming and Harrington (Counting processes and survival analysis, 1991) and to a dataset of electric motors.
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页码:267 / 285
页数:18
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