plot.ci  R Documentation 
This function adds confidence intervals to a ROC curve plot, either as bars or as a confidence shape.
## 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, ...)
x 
a confidence interval object from the functions

type 
type of plot, “bars” or “shape”. Can be
shortened to “b” or “s”. “shape” is only available for

length 
the length (as plot coordinates) of the bar ticks. Only
if 
no.roc 
if 
col 
color of the bars or shape. 
... 
further arguments for 
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 replotted unless no.roc=TRUE
.
Graphical functions are called with suppressWarnings.
This function returns the confidence interval object invisibly.
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")
Xavier Robin, Natacha Turck, Alexandre Hainard, et al. (2011) “pROC: an opensource package for R and S+ to analyze and compare ROC curves”. BMC Bioinformatics, 7, 77. DOI: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1186/147121051277")}.
plot.roc
, ci.thresholds
, ci.sp
, ci.se
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")
## End(Not run)
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