gcmrec

General class of models for recurrent event data.

gcmrec fits the general class of semiparametric models for recurrent event data of Peña and Hollander (2004). Unlike standard survival models, it accounts for what an event does to the subject through an effective age function, for the effect of accumulating occurrences, and for unobserved heterogeneity through gamma frailties. It applies to settings such as repeated hospital readmissions, cancer relapses or successive failures of a machine, and it also fits the extension for cancer relapses of González, Peña and Slate (2005).

Installation

install.packages("gcmrec")

Development version:

# install.packages("remotes")
# remotes::install_github("isglobal-brge/gcmrec")
install.packages("gcmrec", repos = c('https://isglobal-brge.r-universe.dev', 'https://cloud.r-project.org'))

Usage

library(gcmrec)
data(readmission)

fit <- gcmrec(Survr(id, time, event) ~ as.factor(dukes) + sex,
              data = readmission, s = 3000)

summary(fit)      # hazard ratios with confidence intervals
plotForest(fit)   # and the corresponding figure
plot(fit)         # baseline survivor function

Beyond fitting, the package provides the mean cumulative function of the events (mcf()), event charts (graph.caltimes()), predictions for covariate profiles (predict(), plotPredict()) and likelihood ratio tests between nested models (anova()).

The vignette walks through a complete analysis:

vignette("gcmrec")

References

Peña, E.A. and Hollander, M. (2004). Models for recurrent events in reliability and survival analysis. In Mathematical Reliability: An Expository Perspective, chapter 6, pp. 105–123. Kluwer Academic Publishers.

González, J.R., Peña, E.A. and Slate, E.H. (2005). Modelling intervention effects after cancer relapses. Statistics in Medicine, 24(24), 3959–3975. doi:10.1002/sim.2410

License

GPL (>= 2)