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.

危害函数描述了在时间t处的瞬时故障率，假设个体可以生存到瞬时t为止。协变量的作用会导致危险函数发生变化，因此可能会出现变化点。在进行生存分析时，确定发生变更点的位置很重要。本文提出了一种新的估计Cox比例风险模型中变化点的方法，该方法基于最大似然估计与矩估计（ME）结合数值方法，以最小化ME给定的目标函数。估计器的均方误差是通过考虑不同情况的蒙特卡洛模拟获得的。为了研究所提出的估计器在均方误差方面的行为，我们将其与已知的估计变化点的方法进行了比较研究。还包括一个真实的数据应用程序。