icmstate (version 0.2.0)

plot_surv: Plot the transition specific survival probabilities for a fitted npmsm model

Description

For a fitted npmsm model plot the transition specific survival probabilities. These are given by the product integral of the hazard increments estimated for a single transition. This is equivalent to a Kaplan-Meier estimator ignoring the existence of all other transitions.

Usage

plot_surv(npmsmlist, landmark, support = FALSE, sup_cutoff = 1e-08)

Value

A plot will be produced in the plotting window. When assigning the output to an object, the underlying data frame used for plotting and a 'ggplot' object will be returned in a list.

Arguments

npmsmlist

An "npmsm" object or a list containing multiple "npmsm" objects

landmark

A landmark time indicating from which time on survival should be determined. If missing, the smallest time in the first "npmsm" object will be used.

support

Should the support regions be displayed as rectangles?

sup_cutoff

Cutoff to be used for determining the support intervals.

Examples

require(mstate)
require(ggplot2)
#Generate from an illness-death model with exponential transitions with 
#rates 1/2, 1/10 and 1 for 10 subjects over a time grid.
gd <- sim_weibmsm(tmat = trans.illdeath(), shape = c(1,1,1),
                  scale = c(2, 10, 1), n_subj = 10, obs_pars = c(2, 0.5, 20), 
                  startprobs = c(0.9, 0.1, 0))
mod1 <- npmsm(gd, trans.illdeath(), maxit = 4)
mod2 <- npmsm(gd, trans.illdeath(), maxit = 20)

#Plot the transition specific Kaplan-Meier estimators and their numerically 
#determined support sets.
plot_surv(list(mod1, mod2), support = TRUE)