Journal of Statistical Software (Jan 2023)

Regression Modeling for Recurrent Events Possibly with an Informative Terminal Event Using R Package reReg

  • Sy Han Chiou,
  • Gongjun Xu,
  • Jun Yan,
  • Chiung-Yu Huang

DOI
https://doi.org/10.18637/jss.v105.i05
Journal volume & issue
Vol. 105
pp. 1 – 34

Abstract

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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 scalechange 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.

Keywords