frailtypack (version 2.8.3)

plot.longiPenal: Plot Method for a joint model for longitudinal data and a terminal event.

Description

Plots estimated baseline survival and hazard functions for a terminal outcome from an object of class 'longiPenal'. Confidence bands are allowed.

Usage

## S3 method for class 'longiPenal':
plot(x, type.plot = "Hazard", conf.bands=TRUE, pos.legend="topright",
 cex.legend=0.7, main, color, ...)

Arguments

x

A joint model for longitudinal outcome and a terminal event, i.e. a longiPenal class object (output from calling longiPenal function).

type.plot

a character string specifying the type of curve for the terminal event. Possible value are "Hazard", or "Survival". The default is "Hazard". Only the first words are required, e.g "Haz", "Su"

conf.bands

Logical value. Determines whether confidence bands will be plotted. The default is to do so.

pos.legend

The location of the legend can be specified by setting this argument to a single keyword from the list '"bottomright"', '"bottom"', '"bottomleft"', '"left"', '"topleft"', '"top"', '"topright"', '"right"' and '"center"'. The default is '"topright"'

cex.legend

character expansion factor *relative* to current 'par("cex")'. Default is 0.7

main

title of plot

color

color of the curve (integer)

...

other unused arguments

Value

• Print a plot for the terminal event of the joint model for a longitudinal and survival data.

See Also

longiPenal

Examples

###--- Joint model for longitudinal data and a terminal event ---###

data(colorectal)
data(colorectalLongi)

# Survival data preparation - only terminal events 
colorectalSurv <- subset(colorectal, new.lesions == 0)

# Baseline hazard function approximated with splines
# Random effects as the link function

model.spli.RE <- longiPenal(Surv(time1, state) ~ age + treatment + who.PS 
+ prev.resection, tumor.size ~  year * treatment + age + who.PS ,
colorectalSurv,	data.Longi = colorectalLongi, random = c("1", "year"),
id = "id", link = "Random-effects", left.censoring = -3.33, 
n.knots = 7, kappa = 2)
pdf(file = "/home/agareb1/etudiants/al10/newpack/test/plot_longi.pdf")

# Plot the estimated baseline hazard function with the confidence intervals
plot(model.spli.RE)	

# Plot the estimated baseline hazard function with the confidence intervals
plot(model.spli.RE, type = "Survival")