Regression Modeling for Recurrent Events Possibly with an Informative Terminal Event Using R Package reReg
Regression Modeling for Recurrent Events Possibly with an Informative Terminal Event Using R Package reReg
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使用R Package reReg对可能具有信息性终端事件的重复事件的回归建模
DOI：
10.18637/jss.v105.i05
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发表时间：
2021-04
影响因子：
5.8
通讯作者：
S. H. Chiou;Gongjun Xu;Jun Yan;Chiung-Yu Huang
中科院分区：
文献类型：
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作者：
S. H. Chiou;Gongjun Xu;Jun Yan;Chiung-Yu Huang
复发事件分析在生物医学、公共卫生和工程学等领域有着广泛的应用，在这些领域，研究对象在随访期间可能会经历一系列感兴趣的事件。R包REG提供了一个全面的实用和易于使用的工具集合，用于对反复发生的事件进行回归分析，可能会出现信息丰富的终端事件。回归框架是一个一般的尺度变化模型，它包括流行的COX模型、加速率模型和加速平均模型作为特例。信息性审查是通过特定于主题的脆弱性来实现的，不需要任何参数说明。对于重复事件过程和最终事件，允许不同的回归模型。还包括可视化和模拟工具。
Recurrent event analyses have found a wide range of applications in biomedicine, public health, and engineering, among others, where study subjects may experience a sequence of event of interest during follow-up. The R package reReg offers a comprehensive collection of practical and easy-to-use tools for regression analysis of recurrent events, possibly with the presence of an informative terminal event. The regression framework is a general scale-change model which encompasses the popular Cox-type model, the accelerated rate model, and the accelerated mean model as special cases. Informative censoring is accommodated through a subject-specific frailty without any need for parametric specification. Different regression models are allowed for the recurrent event process and the terminal event. Also included are visualization and simulation tools.