plot.idm: Plot method for an illness-death model

In SmoothHazard: Smooth models for interval-censored data with applications to survival and illness-death models

Description

Plot estimated baseline transition intensities from an object of class idm optionally with confidence limits.

Usage

## S3 method for class 'idm'
plot(x, conf.int = FALSE, citype = "shadow", add = FALSE,
  axes = TRUE, col, lwd, lty, xlim, ylim, xlab, ylab, legend = TRUE,
  transition = c("01", "02", "12"), ...)

Arguments

x	a idmWeib class object (output from calling idm with the (default) option intensities="Weib".
conf.int	If TRUE show confidence limits
citype	Type of confidence limits, can be "shadow" or "bars"
add	If TRUE add to existing plot
axes	If TRUE axes are drawn
col	Color of the lines
lwd	Width of the lines
lty	Type of the lines
xlim	Limits for x-axis
ylim	Limits for y-axis
xlab	Label for x-axis
ylab	Label for y-axis
legend	If TRUE a legend is drawn, which can be further controlled via SmartControl.
transition	Choose one of the transition intensities: c("01","02","12").
...	Passed to SmartControl

Value

Print a plot of the baseline transition intensities of an illness-death model estimated using a Weibull approach.

See Also

print.idm,summary.idm,idm,

idm

Examples

library(lava)
library(prodlim)
m <- idmModel(scale.lifetime=1/10,scale.illtime=1/8)
distribution(m,"X") <- binomial.lvm()
regression(m,latent.lifetime~X) <- 0.7
set.seed(30)
d <- sim(m,100)
fit.weib <- idm(formula02=Hist(observed.lifetime,event=seen.exit)~1,
formula01=Hist(time=list(L,R),event=seen.ill)~1,data=d,conf.int=FALSE)
plot(fit.weib)

## Not run: 
## FIXME: the limits for the 01 transition are a bit wide!?
## with bootstrap confidence limits
fit.weib <- idm(formula02=Hist(observed.lifetime,event=seen.exit)~1,
formula01=Hist(time=list(L,R),event=seen.ill)~1,data=d,conf.int=TRUE)
plot(fit.weib)

## End(Not run)

Example output

Loading required package: prodlim

SmoothHazard documentation built on May 2, 2019, 4:43 p.m.