R (>= 2.10), survival, boot, MASS, survC1

Juan R González, Virginie Rondeau
<Virginie.Rondeau@isped.u-bordeaux2.fr> and Yassin Mazroui
<Yassin.Mazroui@isped.u-bordeaux2.fr>
Frailtypack now fits several classes of frailty models
using Penalized Likelihood on the hazard function. 1) 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 (the
Andersen-Gill(1982) approach has been implemented for recurrent
events). An automatic choice of the smoothing parameter is
possible using an approximated cross-validation procedure. 2)
Additive frailty models for proportional hazards models with
two correlated random effects (intercept random effect with
random slope). 3) Nested frailty models for hierarchically
clustered data (with 2 levels of clustering) by including two
iid gamma random effects. 4) Joint frailty models in the
context of joint modelling of recurrent events with terminal
event.

Juan R Gonzalez, Virginie Rondeau
<Virginie.Rondeau@isped.u-bordeaux2.fr>,Yassin Mazroui
<Yassin.Mazroui@isped.u-bordeaux2.fr> and Amadou Diakite
<Amadou.Diakite@isped.u-bordeaux2.fr>

General Frailty models using a semi_parametrical penalized
likelihood estimation or a parametrical estimation
Juan R. Gonzalez, Virginie Rondeau
<Virginie.Rondeau@isped.u-bordeaux2.fr>,Yassin Mazroui
<Yassin.Mazroui@isped.u-bordeaux2.fr> and Amadou Diakite
<Amadou.Diakite@isped.u-bordeaux2.fr>
Frailtypack now fits several classes of frailty models
using a penalized likelihood estimation on the hazard function
but also a parametrical estimation. 1) A shared gamma frailty
model and Cox proportional hazard model. Left truncated,
censored data and strata (max=2) are allowed.  Clustered and
recurrent survival times can be studied (the
Andersen-Gill(1982) approach has been implemented for recurrent
events). An automatic choice of the smoothing parameter is
possible using an approximated cross-validation procedure. 2)
Additive frailty models for proportional hazard models with two
correlated random effects (intercept random effect with random
slope). 3) Nested frailty models for hierarchically clustered
data (with 2 levels of clustering) by including two iid gamma
random effects. 4) Joint frailty models in the context of joint
modelling of recurrent events with terminal event.