Package: frailtypack
Version: 2.2-16
Date: 2010-10-13
Title: Frailty models using maximum penalized likelihood estimation
Author: Juan R Gonz�lez, Virginie Rondeau
<Virginie.Rondeau@isped.u-bordeaux2.fr> and Yassin Mazroui
<Yassin.Mazroui@isped.u-bordeaux2.fr>
Maintainer: Juan R Gonzalez <jrgonzalez@creal.cat>
Depends: R (>= 2.0.0), survival
Description: 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.
License: GPL (>= 2)
URL: http://www.r-project.org
Encoding: latin1
Packaged: 2010-10-13 06:12:03 UTC; jrgonzalez
Repository: CRAN
Date/Publication: 2010-10-13 11:29:33

Author: Juan R Gonzalez, Virginie Rondeau

Title: General Frailty models using a semi_parametrical penalized
likelihood estimation or a parametrical estimation
Author: Juan R. Gonzalez, Virginie Rondeau
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
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.