A computational method for estimating a change point in the Cox hazard model

被引：1
作者：
G. Y. Arenas
J. A. Villaseñor
O. Palmeros
F. Tajonar
机构：
[1] Colegio de Postgraduados,Departamento de Estadística
[2] Universidad Autónoma de Chapingo,Área de Matemáticas
[3] Benemérita Universidad Autónoma de Puebla,Facultad de Ciencias Físico Matemáticas
来源：
Computational Statistics | 2021年 / 36卷
关键词：
Survival analysis; Hazard function; Parameter estimation; Monte Carlo simulation; Clinical trials;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The hazard function describes the instantaneous rate of failure at a time t, given that the individual survives up to the instant t. The effect of the covariates produces a variation in the hazard function, hence a change point might occur. When dealing with survival analysis, it is of interest to identify where a change point has occurred. This paper proposes a new method for estimating the change point in the Cox proportional hazard model, which is based on maximum likelihood estimation combined with moments estimation (ME) and a numerical mehtod to minimize an objective function given by ME. The mean square error of the estimator is obtained by Monte Carlo simulation, considering different scenarios. For the purpose of studying the behavior of the proposed estimator in terms of its mean square error, a comparative study against a known method to estimate the change point is included. A real data application is also included.
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页码：2491 / 2506
页数：15
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