plot.nestedPenal

lines.nestedPenal

A nested model, more generaly an object of class <code>frailtyPenal for Nested frailty models</code> (output from calling <code>frailtyPenal</code>
    function).

Other graphical parameters like those in <code><a href="/link/plot.frailtyPenal?package=frailtypack&version=2.4.1" rd-options="" data-mini-rdoc="frailtypack::plot.frailtyPenal">plot.frailtyPenal</a></code>

Plots estimated baseline survival and hazard functions (output from an object of class `frailtyPenal' for nested frailty models). Confidence bands are allowed.

methods

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.

plot.nestedPenal: Plot Method for a Nested frailty model.

Description

Usage

Arguments

Value

See Also

Examples