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frailtypack

Overview

frailtypack is an R package for the analysis of survival data using shared frailty models, joint frailty models, and other advanced survival modelling approaches.

The package provides methods for recurrent event data, terminal events, competing risks, and joint modelling of longitudinal and survival outcomes.

For a detailed description of the statistical methods, see the package documentation and vignettes.

Installation

From CRAN

install.packages("frailtypack")

Development version from GitHub

install.packages("remotes")
remotes::install_github("vrondeau/frailtypack")

Documentation

The package includes R help pages and vignettes describing its methods and their use.

help(package = "frailtypack")
browseVignettes("frailtypack")

Shiny application

An interactive Shiny application is available at:

https://frailtypack-pkg.shinyapps.io/shiny_frailtypack/

Bug reports and feature requests

Please report bugs or suggest improvements through the GitHub issue tracker:

https://github.com/vrondeau/frailtypack/issues

License

See the DESCRIPTION file and the package source for licensing information.

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Version

Install

install.packages('frailtypack')

Monthly Downloads

2,048

Version

3.8.2

License

GPL (>= 2.0)

Issues

Pull Requests

Stars

Forks

Maintainer

Virginie Rondeau

Last Published

November 4th, 2026

Functions in frailtypack (3.8.2)

Paq810

Filtered Paquid Sample Data Set for Illness-Death Modeling
cluster

Identify clusters
Diffepoce

Difference of Expected Prognostic Observed Cross-Entropy (EPOCE) estimators and its 95% tracking interval between two joint models.
additivePenal

Fit an Additive Frailty model using a semiparametric penalized likelihood estimation or a parametric estimation
SurvIC

Create a survival object for interval censoring and possibly left truncated data
Cmeasures

Concordance measures in shared frailty and Cox proportional hazard models
bcos

Breast Cosmesis Data
CPRSKbmtcrr

Transformed Bone Marrow Transplant Data for Competing Risks
colorectal

Follow-up of metastatic colorectal cancer patients: times of new lesions appearance and death
GenfrailtyPenal

Fit a Shared or a Joint Frailty Generalized Survival Model
epoce

Estimators of the Expected Prognostic Observed Cross-Entropy (EPOCE) for evaluating predictive accuracy of joint models.
dataNested

Simulated data with two levels of grouping
frailtyCmprsk

Fit a Weibull Competing Risks Model with Optional Shared Frailty
event2

Identify event2 indicator
dataOvarian

Advanced Ovarian Cancer dataset
dataNCC

Simulated data for recurrent events and a terminal event with weigths using nested case-control design
dataAdditive

Simulated data as a gathering of clinical trials databases
colorectalLongi

Follow-up of metastatic colorectal cancer patients : longitudinal measurements of tumor size
dataMultiv

Simulated data for two types of recurrent events and a terminal event
frailtyDesign

Sample Size calculation and Power Analysis using Gamma-Frailty Models