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首页> 外文期刊>Contemporary clinical trials >Estimating the survival functions for right-censored and interval-censored data with piecewise constant hazard functions
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Estimating the survival functions for right-censored and interval-censored data with piecewise constant hazard functions

机译：用分段恒定风险函数估计右删失和区间删失数据的生存函数

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摘要

The exponential distribution is frequently used to model the survival time of a patient population, which assumes the hazard rate to be a constant over time. This assumption is often violated as the hazard function may vary over time and exhibit one or more change points in its values. Several methods exist in the literature for detecting a single change point in a piecewise constant hazard function for right-censored data. A sequential testing approach to detecting multiple change points in the hazard function using likelihood ratio statistics and resampling is proposed, which is applicable to both right-censored and interval-censored data. Numerical results based on simulated survival data and a real example show that the proposed approach can accurately detect the change points in the hazard function for both right-censored and interval-censored data.
机译：指数分布通常用于对患者群体的生存时间进行建模，这假设危险率随时间变化是恒定的。由于危害函数可能随时间变化并在其值上显示一个或多个变化点，因此经常违反此假设。文献中存在几种方法用于检测右删失数据的分段恒定危害函数中的单个变化点。提出了一种使用似然比统计和重采样的方法来检测危险函数中多个变化点的顺序测试方法，该方法适用于右删失数据和区间删失数据。基于模拟的生存数据和一个实际例子的数值结果表明，该方法可以针对右删失数据和区间删失数据准确检测危险函数中的变化点。

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