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Proportional hazard model for time-dependent covariates with repeated events

机译:具有重复事件的时间相关协变量的比例风险模型

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Cox's proportional hazard is potentially the most used method in life data and survival analysis. Although the method is relatively simple to understand, its major difficulties in estimation are observed when time dependent-covariates with repeated events are used as input variables. This paper presents a review and analysis of the model parameter estimation. The model's assumptions are discussed, and a detailed analysis highlights the application, advantages and potential limitations when the assumption of proportionality is violated.
机译:考克斯的比例风险可能是生命数据和生存分析中使用最多的方法。尽管该方法相对易于理解,但是当将具有重复事件的时间相关协变量用作输入变量时,会发现其估计方面的主要困难。本文对模型参数估计进行了回顾和分析。讨论了模型的假设,并进行了详细分析,突出了违反比例假设时的应用,优点和潜在限制。

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