Description Usage Arguments Author(s) References See Also Examples
For Cox regression models, this function generates timedependent ROC plot(s) (true positive rate vs false positive rate) for a given alpha
at the timepoint(s) provided based on median predicted risk.
Provided that the eNetXplorer
object was generated with survAUC=T
, the crossvalidated
median AUC and 95% CI are shown in the default title.
For more details, see Heagerty et al and package survivalROC
.
1 2 3 4  plotSurvROC(x, alpha.index=NULL, survAUC_time,
xlab="False positive rate (1  Specificity)",
ylab="True positive rate (Sensitivity)", cex.lab=1, main=NULL, col.main="black",
cex.main=0.95, status0="censored", status1="events", ...)

x 

alpha.index 
Integer indices to select alpha values. Default is 
survAUC_time 
Timepoint(s) of interest. Must be in the same time units as the survival time
provided to build the 
xlab 
Custom xaxis label. 
ylab 
Custom yaxis label. 
cex.lab 
Axis label size. 
main 
Custom title. 
col.main 
Title color. 
cex.main 
Title size. 
status0 
Title label for censoring ("status"=0). 
status1 
Title label for events ("status"=1). 
... 
Additional parameters. 
Julian Candia and John S. Tsang
Maintainer: Julian Candia julian.candia@nih.gov
Blanche P, Dartigues JF and JacqminGadda H. Estimating and comparing timedependent areas under receiver operating characteristic curves for censored event times with competing risks, Statistics in Medicine (2013) 32:53815397.
1 2 3 4  data(breastCancerSurv)
fit = eNetXplorer(x=breastCancerSurv$predictor, y=breastCancerSurv$response, family="cox",
n_run=25, n_perm_null=15, seed=111, survAUC=TRUE, survAUC_time=c(1,5)*365)
plot(x=fit, plot.type="survROC", survAUC_time=c(1,5)*365, status0="censored", status1="deaths")

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