pROC (version 1.3.2)

plot.ci: Plot confidence intervals

Description

This function adds confidence intervals to a ROC curve plot, either as bars or as a confidence shape.

Usage

## S3 method for class 'ci.thresholds':
plot(x, length=.01*ifelse(attr(x,
  "roc")$percent, 100, 1), col=par("fg"), ...)
## S3 method for class 'ci.sp':
plot(x, type=c("bars", "shape"), length=.01*ifelse(attr(x,
"roc")$percent, 100, 1), col=ifelse(type=="bars", par("fg"),
"gainsboro"), no.roc=FALSE, ...)
## S3 method for class 'ci.se':
plot(x, type=c("bars", "shape"), length=.01*ifelse(attr(x,
"roc")$percent, 100, 1), col=ifelse(type=="bars", par("fg"),
"gainsboro"), no.roc=FALSE, ...)

Arguments

x

a confidence interval object from the functions ci.thresholds, ci.se or ci.sp.

type

type of plot, bars or shape. Can be shortened to b or s. shape is only available for ci.se and ci.sp, not for ci.thresholds

length

the length (as plot coordinates) of the bar ticks. Only if type="bars".

no.roc

if FALSE, the ROC line is re-added over the shape. Otherwise if TRUE, only the shape is plotted. Ignored if type="bars"

col

color of the bars or shape.

...

further arguments for segments (if type="bars") or polygon (if type="shape").

Value

• This function returns the confidence interval object invisibly.

encoding

UTF-8

Warnings

With type="shape", the warning Low definition shape is issued when the shape is defined by less than 15 confidence intervals. In such a case, the shape is not well defined and the ROC curve could pass outside the shape. To get a better shape, increase the number of intervals, for example with: plot(ci.sp(rocobj, sensitivities=seq(0, 1, .01)), type="shape")

Details

This function adds confidence intervals to a ROC curve plot, either as bars or as a confidence shape, depending on the state of the type argument. The shape is plotted over the ROC curve, so that the curve is re-plotted unless no.roc=TRUE. Graphical functions are called with suppressWarnings.

See Also

plot.roc, ci.thresholds, ci.sp, ci.se

Examples

data(aSAH)
# Start a ROC plot
rocobj <- plot.roc(aSAH$outcome, aSAH$s100b)
plot(rocobj)
# Thresholds
ci.thresolds.obj <- ci.thresholds(rocobj)
plot(ci.thresolds.obj)
# Specificities
plot(rocobj) # restart a new plot
ci.sp.obj <- ci.sp(rocobj, boot.n=500)
plot(ci.sp.obj)
# Sensitivities
plot(rocobj) # restart a new plot
ci.se.obj <- ci(rocobj, of="se", boot.n=500)
plot(ci.se.obj)

# Plotting a shape. We need more
ci.sp.obj <- ci.sp(rocobj, sensitivities=seq(0, 1, .01), boot.n=100)
plot(rocobj) # restart a new plot
plot(ci.sp.obj, type="shape", col="blue")

# Direct syntax (response, predictor):
plot.roc(aSAH$outcome, aSAH$s100b,
         ci=TRUE, of="thresholds")