num.id

A character or numeric variable which is supposed to indicate 
the variable identifying individuals

This is a special function used in addition to the <code>cluster()</code> function in the context of survival joint models
for clustered data. This function identifies subject index. It is used on the right hand
side of a 'frailtyPenal' formula. Using <code>num.id()</code> in a formula implies that
a joint frailty model for clustered data is fitted (Rondeau et al. 2011).

misc

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.

num.id: Identify individuals in Joint model for clustered data

Description

Usage

Arguments

References

See Also

Examples