epade (version 0.2.2)

roc.plot.ade: ROC-curves plot

Description

Function to plot ROC curves with AUC calculation

Usage

roc.plot.ade(pred, event, group=NULL, data=NULL, vnames=NULL,
             main="", xlab="1-Specificity", ylab="Sensitivity",
             digits=3, pdigs=4, lty=1, lwd=2,
             col=NULL, tcol=NULL, bgcol=NULL,
             wall=0, test=FALSE, CC=TRUE, auc=TRUE, diag=TRUE)

Arguments

pred

• a list of numeric predictor variables

a vector of character strings with the names of the predictors in data.frame

item

• event
• a character strings with the names of event variable in data.frame
• group
• a character strings with the names of factor variable in data.frame
• data
• vnames
• main
• xlab
• ylab
• digits
• pdigs
• lty
• lwd
• col
• tcol
• bgcol
• wall
• test
• CC
• auc
• diag

itemize

• a factor to group the curves

Details

if test is TRUE the function perform a DeLong-DeLong test for correlated ROC-curves

Examples

# simple curve
event<-rbinom(1000, size=1, prob=0.3)
pred <- event+rnorm(1000)
roc.plot.ade(pred, event)
# grouped
group=rbinom(1000, 1 ,0.5)
roc.plot.ade(pred, event, group, wall=2)
# comparison of two predictors
pred2 <- event+rnorm(1000, 0, 2)
roc.plot.ade(list(pred, pred2), event, test=TRUE, wall=3)