prodlim (version 1.0.5)

plot.prodlim: Plotting event probabilities over time

Description

Function to plot survival and cumulative incidence curves against time.

Usage

## S3 method for class 'prodlim':
plot(x, what, cause = 1, newdata, add = FALSE, col, lty, lwd,
             ylim, xlim, xlab = "Time", ylab, legend = TRUE,
             legend.args= NULL, mark.time = FALSE, cex.mark.time = 1.5,
             conf.int = TRUE, conf.int.args = list(col = "gray"),
             atrisk, atrisk.args, timeOrigin,...)

Arguments

x

an object of class `prodlim' as returned by the prodlim function.

what

controls what part of the object is plotted. Defaults to "survival" for the Kaplan-Meier estimate of the survival function in two state models and to "incidence" for the Aalen-Johansen estimate of the cumulative incid

cause

Determines the cause of the cumulative incidence function. When there are strata defined by newdata only one cause is possible.

newdata

a data frame containing strata for which plotted curves are desired.

add

if 'TRUE' curves are added to an existing plot.

col

color for curves defaults to 1:number(curves)

lty

line type for curves defaults to 1

lwd

line width for all curves

ylim

limits of the y-axis

xlim

limits of the x-axis

ylab

label for the y-axis

xlab

label for the x-axis

legend

if TRUE a legend is be plotted automatically

legend.args

list of arguments that is passed to the function legend

mark.time

if TRUE the curves are tick-marked at right censoring times

cex.mark.time

cex for the tick-marks if mark.time is set TRUE

conf.int

if TRUE pointwise confidence intervals are plotted

conf.int.args

list with extra arguments like col, lty, etc. used for the pointwise confidence intervals. Extra argument time determines time points at which confidence intervals are plotted.

atrisk

if TRUE display numbers of subjects at risk. if data are cluster correlated also the number of clusters with at least one subject at risk is given.

atrisk.args

list of extra arguments for plotting of the numbers at risk. Recognized extra arguments are: times: at which time points numbers are plotted. labels vector of labels, e.g. "No. Patients".

timeOrigin

Start of the time axis

...

graphical parameters that are passed to function plot

Value

• NULL

Details

See examples.

See Also

prodlim,plot.Hist,summary.prodlim, neighborhood

Examples

## simulate right censored data from a two state model 
dat <- data.frame(time=rexp(100),status=rbinom(100,1,.3),X=rbinom(100,1,.5),Z=rnorm(100,10,3),patnr=sample(1:10,size=100,replace=TRUE))
with(dat,plot(Hist(time,status)))

### marginal Kaplan-Meier estimator
kmfit <- prodlim(Hist(time, status) ~ 1, data = dat)
plot(kmfit)

### Kaplan-Meier in discrete strata
kmfitX <- prodlim(Hist(time, status) ~ X, data = dat)
plot(kmfitX)

### Kaplan-Meier in continuous strata
kmfitZ <- prodlim(Hist(time, status) ~ Z, data = dat)
plot(kmfitZ,newdata=data.frame(Z=c(5,7,12)))

### Cluster-correlated data
kmfitC <- prodlim(Hist(time, status) ~ cluster(patnr), data = dat)
plot(kmfitC,atrisk.args=list(labels=c("Units","Patients")))

## simulate right censored data from a competing risk model 
datCR <- data.frame(time=rexp(100),status=rbinom(100,2,.3),X=rbinom(100,1,.5),Z=rnorm(100,10,3))
with(datCR,plot(Hist(time,status)))

### marginal Aalen-Johansen estimator
ajfit <- prodlim(Hist(time, status) ~ 1, data = datCR)
plot(ajfit)

### conditional Aalen-Johansen estimator
ajfitXZ <- prodlim(Hist(time, status) ~ X+Z, data = datCR)
plot(ajfitXZ,newdata=data.frame(X=c(1,1,0),Z=c(4,10,10)))
plot(ajfitXZ,newdata=data.frame(X=c(1,1,0),Z=c(4,10,10)),cause=2)