In tbalan/frailtyEM: Fitting Frailty Models with the EM Algorithm

knitr::opts_chunk$set(
  collapse = TRUE,
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This is an R package for fitting semiparametric shared frailty models with the EM algorithm. You can check the "issues" section to see about known issues. 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.

The stable version may be installed from CRAN:

install.packages("frailtyEM")

and the development version from GitHub:

devtools::install_github("tbalan/frailtyEM")

The bulk of the documentation of the package can be found in the vignette. If the package is installed from GitHub, then the vignette is installed if the pacakge is installed like this:

devtools::install_github("tbalan/frailtyEM", build_vignettes = TRUE)

Functions

The main fitting function is emfrail(), which in general returns an emfrail() object. Several plots can be produced from this objects, via the plot.emfrail() and autoplot.emfrail() methods (the latter using ggplot2).

Another useful tool is the Commenges-Andersen score test for heterogeneity. This test does not require estimating the shared frailty model. The ca_test() function may be used in conjunction with a coxph object to calculate this.