Institut de Santé Publique,
d'Épidémiologie et de Développement
 

Centre Inserm U897
Equipe Biostatistique

R package « FRAILTYPACK »
General frailty models using maximum penalized likelihood estimation or parametrical estimation.

Modèles généraux à fragilité en utilisant une estimation par maximum de vraisemblance ou une approche paramétrique.


Presentation

Frailtypack now fits several classes of frailty models on the hazard function.

  • A shared gamma frailty model and Cox proportional hazards model. Left truncated, censored data and strata (max=2) are allowed. Clustered and recurrent survival times can be studied approach has been implemented for recurrent events). An automatic choice of the smoothing parameter is possible using an approximated cross-validation procedure.
  • Additive frailty models for proportional hazards models with two correlated random effects (intercept random effect with random slope).
  • Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects.
  • Joint frailty models in the context of joint modelling of recurrent events with terminal event.

References

  • Rondeau, V., Mazroui, Y., & Gonzalez, J. R. (2012). FRAILTYPACK: An R package for the analysis of correlated data with frailty models using the penalized likelihood estimation Journal Of Statistical Software: 4-5.
  • Liquet B, Timsit J-FF, Rondeau V (2012). Investigating hospital heterogeneity with a multi-state frailty model : application to nosocomial pneumonia disease in intensive care units. BMC medical research methodology 12(1):79.
  • Rondeau V, Pignon J-P, Michiels S (2011). A joint model for the dependence between clustered times to tumour progression and deaths: A meta-analysis of chemotherapy in head and neck cancer. Statistical methods in medical research. 2011;897:1–19.
  • Rondeau, V., Mazroui, Y., & Gonzalez, J. R. FRAILTYPACK: An R package for the analysis of correlated data with frailty models using the penalized likelihood estimation Journal Of Statistical Software, in press 2011.
  • Rondeau, V., S. Michiels, et al. (2008). "Investigating trial and treatment heterogeneity in an individual patient data meta-analysis of survival data by means of the penalized maximum likelihood approach." Stat Med 27(11): 1894-91.
  • Rondeau, V., S. Mathoulin-Pelissier, et al. (2007). "Joint frailty models for recurring events and death using maximum penalized likelihood estimation: application on cancer events." Biostatistics 8(4): 708-21.
  • Rondeau, V., L. Filleul, et al. (2006). "Nested frailty models using maximum penalized likelihood estimation." Statistics in Medicine 25(23): 4036-52.
  • Rondeau, V. and J. R. Gonzalez (2005). "frailtypack: a computer program for the analysis of correlated failure time data using penalized likelihood estimation." Comput Methods Programs Biomed 80(2): 154-64.
  • Rondeau, V., D. Commenges, et al. (2003). "Maximum penalized likelihood estimation in a gamma-frailty model.Lifetime Data Analysis 9(2): 139-53.

Author

Rondeau Virginie Yassin Mazroui
Amadou Diakité
Alexandre Laurent
Juan Ramon Gonzalez

Inserm U897
146 rue Léo Saignat
33076 Bordeaux Cedex
France

Contact

E-mail: Virginie.Rondeau@isped.u-bordeaux2.fr.
We are interested in feed-back but can not guarantee support.

Licence

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.


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