plot.ci

From pROC v1.16.2 by Xavier Robin

Plot confidence intervals

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

Keywords: hplot, utilities, nonparametric, aplot, univar, ROC

Usage

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

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.

Value

This function returns the confidence interval object invisibly.

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")

References

Xavier Robin, Natacha Turck, Alexandre Hainard, et al. (2011) ``pROC: an open-source package for R and S+ to analyze and compare ROC curves''. BMC Bioinformatics, 7, 77. DOI: 10.1186/1471-2105-12-77.

Examples

# NOT RUN {
data(aSAH)
# }
# NOT RUN {
# 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")
# }

Documentation reproduced from package pROC, version 1.16.2, License: GPL (>= 3)

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