  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.
