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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.

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Install

install.packages('frailtypack')

Monthly Downloads

1,183

Version

2.5.1

License

GPL (>= 2.0)

Last Published

February 13th, 2014

Functions in frailtypack (2.5.1)