plot.jointNestedPenal {frailtypack}

Plot method for a joint nested frailty model.

Description

Plots estimated baseline survival and hazard functions of a joint nested frailty model (output from an object of class 'jointNestedPenal' for joint nested frailty models) for each type of event (terminal or recurrent). Confidence bands are allowed.

Usage

## S3 method for class 'jointNestedPenal'
plot(x, event = "Both", type.plot = "Hazard",
conf.bands = FALSE, pos.legend="topright", cex.legend = 0.7, ylim, main,
color = 2, median=TRUE, Xlab = "Time", Ylab = "Hazard function", ...)

Arguments

x

A joint nested model, i.e. an object of class jointNestedPenal for joint nested frailty model (output from calling frailtyPenal function).

event

a character string specifying the type of curve. Possible value are "Terminal", "Recurrent", or "Both". The default is "Both".

type.plot

a character string specifying the type of curve. Possible value are "Hazard", or "Survival". The default is "Hazard". Only the first letters 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

ylim

y-axis limits

main

plot title

color

curve color (integer)

median

Logical value. Determines whether survival median will be plotted. Default is TRUE.

Xlab

Label of x-axis. Default is '"Time"'

Ylab

Label of y-axis. Default is '"Hazard function"'

...

other unused arguments

Value

Print a plot of the baseline survival or hazard functions for each type of event or both with the confidence bands or not (conf.bands argument)

See Also

frailtyPenal

Examples

## Not run: 

#-- here is generated cluster (30 clusters)
readmissionNested <- transform(readmission,group=id%%30+1)

# Baseline hazard function approximated with splines with calendar-timescale

model.spli.AG <- frailtyPenal(formula = Surv(t.start, t.stop, event) 
~ subcluster(id) + cluster(group) + dukes + terminal(death), 
formula.terminalEvent = ~dukes, data = readmissionNested, recurrentAG = TRUE,
 n.knots = 8, kappa = c(9.55e+9, 1.41e+12),initialize = TRUE)

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

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

## End(Not run)