Description Usage Arguments Details Note Author(s) References See Also Examples
View source: R/plotAUCcurveDiff.R
This function plots the curve of the difference of two timedependent AUCs over time. 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 
object1 
An object of class "ipcwsurvivalROC" or "ipcwcompetingrisksROC"
previously estimated from the 
object2 
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 
ylim 
The range of the yaxis. Default is 
Simultaneous confidence bands can be of particular interest for testing null hypotheses such as "for all time t within an interval, AUC(t) for both markers are equal", by observing whether or not the zero line is contained within the band.
The two markers evluated in objects object1
and
object2
must have been measured on the same subjects.
Paul Blanche [email protected]
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.
plotAUCcurve
for plotting the curve of timedependentAUC: AUC(t) versus t. Confidence intervals and simultaneous confidence bands can also be plotted.
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 48 49 50 51 52 53  ## 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$time,probs=seq(0.2,0.8,0.02)),
iid=TRUE)
ROC.albumin
# plot AUC curve for albumin and bilirunbin with pointwise confidence interval
plotAUCcurve(ROC.albumin,conf.int=TRUE,col="red")
plotAUCcurve(ROC.bili,conf.int=TRUE,col="blue",add=TRUE)
legend("bottomright",c("albumin","bilirunbin"),col=c("red","blue"),lty=1,lwd=2)
#plot the curve of the difference of the two timedependent AUCs over time
plotAUCcurveDiff(ROC.bili,ROC.albumin,conf.int=TRUE,conf.band=TRUE,ylim=c(0.2,0.5))
##With competing risks
data(Melano)
head(Melano)
# Evaluate tumor thickness as a prognostic biomarker for
# death from malignant melanoma.
ROC.thick<timeROC(T=Melano$time,delta=Melano$status,
marker=Melano$thick,cause=1,
times=quantile(Melano$time,probs=seq(0.2,0.8,0.01)),
iid=TRUE)
ROC.thick
ROC.age<timeROC(T=Melano$time,delta=Melano$status,
marker=Melano$age,cause=1,
times=quantile(Melano$time,probs=seq(0.2,0.8,0.01)),
iid=TRUE)
ROC.age
# plot the two AUC curves on the same plot
plotAUCcurve(ROC.thick,FP=2,conf.int=TRUE,col="blue")
plotAUCcurve(ROC.age,FP=2,conf.int=TRUE,col="red",add=TRUE)
legend("bottomright",c("thickness","age"),col=c("blue","red"),lty=1,lwd=2)
# plot the curve of the difference of the two timedependent AUCs over time
plotAUCcurveDiff(ROC.thick,ROC.age,FP=2,conf.int=TRUE,conf.band=TRUE,col="red")
## End(Not run)

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