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

Presentation

Frailtypack now fits several classes of frailty models using Penalized Likelihood 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., 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
Juan Ramon Gonzalez

Inserm U897
146 rue Léo Saignat
33076 Bordeaux Cedex
France

Contact

E-mail: Virginie.Rondeau@isped.u-bordeaux2.fr.
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