Description Usage Arguments Author(s) References See Also Examples
This function plots the curve of timedependentAUC: AUC(t) versus t. Pointwise and simultaneous confidence bands for this curve can also be plotted when inverse probability of censoring weights are computed from a KaplanMeier estimator.
1 2  plotAUCcurve(object, FP = 2, add = FALSE, conf.int = FALSE,
conf.band = FALSE, col = "black")

object 
An object of class "ipcwsurvivalROC" or "ipcwcompetingrisksROC"
previously estimated from the 
FP 
In the competing risks setting, a numeric value that indicates which
definition of AUC is plotted. 
add 
A logical value that indicates if you want to add the AUC curve to a preexisting plot. Default is 
conf.int 
A logical value that indicates whether or not you want to plot the bands
of pointwise confidence intervals. Default is 
conf.band 
A logical value that indicates whether or not you want to plot the simultaneous confidence bands. Default is 
col 
The color to plot the AUC curve. Default is 
Paul Blanche pabl@sund.ku.dk
Blanche, P., Dartigues, J. F., & JacqminGadda, H. (2013). Estimating and comparing timedependent areas under receiver operating characteristic curves for censored event times with competing risks. Statistics in medicine, 32(30), 53815397.
Hung, H. and Chiang, C. (2010). Estimation methods for timedependent AUC with survival data. Canadian Journal of Statistics, 38(1):826
confint
for confidence intervals and confidence bands computation of timedependentAUC.
plotAUCcurveDiff
for plotting the curve of the
difference of two timedependent AUCs over time
with eventually confidence intervals and
simultaneous confidence bands.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47  ## Not run:
## computation times is roughly 10 seconds
##Without competing risks
library(survival)
data(pbc)
head(pbc)
pbc<pbc[!is.na(pbc$trt),] # select only randomised subjects
pbc$status<as.numeric(pbc$status==2) # create event indicator: 1 for death, 0 for censored
# we evaluate bilirubin as a prognostic biomarker for death.
ROC.bili<timeROC(T=pbc$time,
delta=pbc$status,marker=pbc$bili,
cause=1,weighting="marginal",
times=quantile(pbc$time,probs=seq(0.2,0.8,0.02)),
iid=TRUE)
ROC.bili
# we evaluate bilirubin as a prognostic biomarker for death.
ROC.albumin<timeROC(T=pbc$time,
delta=pbc$status,marker=pbc$albumin,
cause=1,weighting="marginal",
times=quantile(pbc$time,probs=seq(0.2,0.8,0.02)),
iid=TRUE)
ROC.albumin
# plot AUC curve for albumin only with pointwise confidence intervals
# and simultaneous confidence bands
plotAUCcurve(ROC.albumin,conf.int=TRUE,conf.band=TRUE)
# plot AUC curve for albumin and bilirunbin with pointwise confidence intervals
plotAUCcurve(ROC.albumin,conf.int=TRUE,col="red")
plotAUCcurve(ROC.bili,conf.int=TRUE,col="blue",add=TRUE)
legend("bottomright",c("albumin","bilirunbin"),col=c("red","blue"),lty=1,lwd=2)
##With competing risks
data(Melano)
head(Melano)
# Evaluate tumor thickness as a prognostic biomarker for
# death from malignant melanoma.
ROC.thick<timeROC(T=Melano$time,delta=Melano$status,
marker=Melano$thick,cause=1,
times=quantile(Melano$time,probs=seq(0.2,0.8,0.01)),
iid=TRUE)
ROC.thick
# plot AUC curve for tumor thickness with pointwise confidence intervals
# and simultaneous confidence bands
plotAUCcurve(ROC.thick,FP=2,conf.int=TRUE,conf.band=TRUE)
## End(Not run)

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