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frailtypack (version 2.5.1)
General Frailty models: shared, joint and nested frailty models
with prediction
Description
Frailtypack now fits several classes of frailty models
using a penalized likelihood estimation on the hazard function
but also a parametric estimation. 1) A shared frailty
model (with gamma or log-normal frailty distribution) and
Cox proportional hazard model. Clustered and
recurrent survival times can be studied. 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 for recurrent events with terminal event for clustered
data or not. Prediction values are available. Left truncated (not for Joint model),
right-censored data, interval-censored data (only for Cox proportional
hazard and shared frailty model) and strata (max=2) are allowed. In each model,
the random effects have a gamma distribution, but you can switch to a log-normal
in shared and joint models. Now, you can also consider time-varying
covariates effects in Cox, shared and joint models. The package includes concordance
measures for Cox proportional hazards models and for shared frailty models.