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 (Chiou and Huang 2021) 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 no 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.
翻译:经常事件分析发现,生物医学、公共卫生和工程等应用范围很广,研究对象在后续跟踪过程中可能会经历一系列令人感兴趣的事件。R套套件Reg(Chiou和Huang 2021)提供了一套全面的实用和易于使用的工具,用于对经常性事件进行回归分析,可能时会有一个信息化的终端事件。回归框架是一个总体规模变化模型,包括流行的Cox型模型、加速率模型和快速平均模型等特例。信息性审查通过特定主题的弱点进行,而不需要参数性说明。允许对经常性事件过程和终点事件采用不同的回归模型,还包括可视化和模拟工具。