plot.prodlim {prodlim} | R Documentation |
Function to plot survival and cumulative incidence curves against time.
## S3 method for class 'prodlim': plot(x, type, cause = 1, newdata, add = FALSE, col, lty, lwd, ylim, xlim, xlab = "Time", ylab, legend = TRUE, marktime = FALSE, confint = TRUE, automar, atrisk=ifelse(add,FALSE,TRUE), timeOrigin, axes=TRUE, percent=FALSE,...)
x |
an object of class `prodlim' as returned by the
prodlim function. |
type |
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 incidence function in competing risk models |
cause |
determines the cause of the cumulative incidence function. Currently one cause is allowed at a time, but you may call the function again with add=TRUE to add the lines of the other causes. |
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 plotted by calling the function legend.
Optional arguments of the function legend can be given in the
form legend.x=val where x is the name of the argument and
val the desired value. See also Details. |
marktime |
if TRUE the curves are tick-marked at right censoring
times by invoking the function MarkTime . Optional arguments of the
function MarkTime can be given in the form
confint.x=val as with legend. See also Details. |
confint |
if TRUE pointwise confidence intervals are plotted by
invoking the function ConfInt . Optional arguments of the
function ConfInt can be given in the form
confint.x=val as with legend. See also Details. |
automar |
If TRUE the function trys to get good values for figure margins around the main plotting region. |
atrisk |
if TRUE display numbers of subjects at risk by invoking the function AtRisk . Optional arguments of the
function AtRisk can be given in the form
atrisk.x=val as with legend. See also Details. |
timeOrigin |
Start of the time axis |
axes |
If true axes are drawn. |
percent |
If true the y-axis is labeled in percent. |
... |
graphical parameters that are passed to function
plot . |
From version 1.1.3 on the arguments legend.args, atrisk.args,
confint.args are obsolete and only available for backward
compatibility. Instead arguments for the invoked functions
AtRisk
, legend
, ConfInt
, MarkTime
,
axis
are simply specified as atrisk.cex=2
. The specification is not
case sensitive, thus
AtRisk.cex=2
or atRISK.cex=2
will have the same effect.
The function axis
is called twice, and arguments of the form
axis1.labels
, axis1.at
are used for the time axis
whereas axis2.pos
, axis1.labels
, etc. are used for the
y-axis.
These arguments are processed via ...
of plot.prodlim
and inside by using the function resolveSmartArgs
.
Documentation of these arguments can be found
in the help pages of the corresponding
functions.
The (invisible) object.
Similar functionality is provided by the function
plot.survfit
of the survival library
Thomas Alexander Gerds <tag@biostat.ku.dk>
prodlim
,plot.Hist
,summary.prodlim
,
neighborhood
, AtRisk
, ConfInt
,
MarkTime
## 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) plot(kmfit,percent=TRUE) plot(kmfit,percent=TRUE,axis1.at=c(0,2,5),axis1.pos=0,axis2.pos=0) ### Kaplan-Meier in discrete strata kmfitX <- prodlim(Hist(time, status) ~ X, data = dat) plot(kmfitX) plot(kmfitX,legend.x="bottomleft",AtRisk.cex=1.3) ### 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.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)