frailtyEM-package: frailtyEM: Fitting Frailty Models with the EM Algorithm

In frailtyEM: Fitting Frailty Models with the EM Algorithm

Description

Contains functions for fitting shared frailty models with a semi-parametric baseline hazard with the Expectation-Maximization algorithm. Supported data formats include clustered failures with left truncation and recurrent events in gap-time or Andersen-Gill format. Several frailty distributions, such as the the gamma, positive stable and the Power Variance Family are supported.

Details

This is an R package for fitting semiparametric shared frailty models with the EM algorithm. You can check the "issues" section Github (link below) For the gamma frailty model, the results are identical with those from the survival pacakage, although frailtyEM provides a more readable output, including confidence intervals for the frailty variance. Other supported distributions include the PVF, compound Poisson, inverse Gaussian, positive stable. Univariate and multivariate data with left truncation are supported, including recurrent events data in Andersen-Gill formulation.

For background on the methods and basic usage of the package, see the paper in the references or the package vignette. The main fitting function is emfrail. For prediction, see predict.emfrail and for plotting, autoplot.emfrail (recommended, uses ggplot2) or plot.emfrail.

Author(s)

Theodor Balan [e-mail]

References

Balan TA, Putter H (2019) "frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models", Journal of Statistical Software 90(7) 1-29. doi:10.18637/jss.v090.i07

See Also

Useful links:

• https://github.com/tbalan/frailtyEM

• Report bugs at https://github.com/tbalan/frailtyEM/issues

frailtyEM documentation built on Sept. 22, 2019, 5:05 p.m.