plot.roc: Plot a ROC curve

Description

This function plots a ROC curve. It can accept many arguments to tweak the appearance of the plot. Two syntaxes are possible: one object of class roc, or either two vectors (response, predictor) or a formula (response~predictor) as in the roc function.

Usage

## S3 method for class 'roc':
plot(x, ...)
## S3 method for class 'smooth.roc':
plot(x, ...)
## S3 method for class 'roc':
plot.roc(x, add=FALSE, reuse.auc=TRUE,
# Generic arguments for par:
xlim=if(x$percent){c(100, 0)} else{c(1, 0)},
ylim=if(x$percent){c(0, 100)} else{c(0, 1)},
xlab=ifelse(x$percent, "Specificity (%)", "Specificity"),
ylab=ifelse(x$percent, "Sensitivity (%)", "Sensitivity"),
asp=1,
mar=c(4, 4, 2, 2)+.1,
mgp=c(2.5, 1, 0),
# col, lty and lwd for the ROC line only
col=par("col"),
lty=par("lty"),
lwd=2,
type="l",
# Identity line
identity=!add,
identity.col="darkgrey",
identity.lty=1,
identity.lwd=1,
# Print the thresholds on the plot
print.thres=FALSE,
print.thres.pch=20,
print.thres.adj=c(-.05,1.25),
print.thres.col="black",
print.thres.pattern=ifelse(x$percent, "%.1f (%.1f%%, %.1f%%)", "%.3f (%.3f, %.3f)"),
print.thres.cex=par("cex"),
print.thres.pattern.cex=print.thres.cex,
# Print the AUC on the plot
print.auc=FALSE,
print.auc.pattern=NULL,
print.auc.x=ifelse(x$percent, 50, .5),
print.auc.y=ifelse(x$percent, 50, .5),
print.auc.adj=c(0,1),
print.auc.col=col,
print.auc.cex=par("cex"),
# Grid
grid=FALSE,
grid.v={if(is.logical(grid) && grid[1]==TRUE){seq(0, 1, 0.1) * ifelse(x$percent, 100, 1)} else if(is.numeric(grid)) {seq(0, ifelse(x$percent, 100, 1), grid[1])} else {NULL}},
grid.h={if (length(grid) == 1) {grid.v} else if (is.logical(grid) && grid[2]==TRUE){seq(0, 1, 0.1) * ifelse(x$percent, 100, 1)} else if(is.numeric(grid)) {seq(0, ifelse(x$percent, 100, 1), grid[2])} else {NULL}},
grid.lty=3,
grid.lwd=1,
grid.col="#DDDDDD",
# Polygon for the AUC
auc.polygon=FALSE,
auc.polygon.col="gainsboro",
auc.polygon.lty=par("lty"),
auc.polygon.density=NULL,
auc.polygon.angle=45,
auc.polygon.border=NULL,
# Polygon for the maximal AUC possible                           
max.auc.polygon=FALSE,
max.auc.polygon.col="#EEEEEE", 
max.auc.polygon.lty=par("lty"),
max.auc.polygon.density=NULL,
max.auc.polygon.angle=45,
max.auc.polygon.border=NULL,
# Confidence interval
ci=!is.null(x$ci),
ci.type=c("bars", "shape", "no"),
ci.col=ifelse(ci.type=="bars", par("fg"), "gainsboro"),
...)
## S3 method for class 'formula':
plot.roc(x, data, ...)
## S3 method for class 'default':
plot.roc(x, predictor, ...)
## S3 method for class 'smooth.roc':
plot.roc(x, ...)

Arguments

a roc object from the roc function (for plot.roc.roc), a formula (for plot.roc.formula) or a response vector (for plot.roc.default).

predictor, data

arguments for the roc function.

add

if TRUE, the ROC curve will be added to an existing plot. If FALSE (default), a new plot will be created.

reuse.auc

if TRUE (default) and the roc object contains an auc field, re-use these specifications for the test. See details.

xlim, ylim, xlab, ylab, asp, mar, mgp

Generic arguments for the plot. See plot and plot.window for more details. Only used if add=FALSE.

col,lty, lwd

color, line type and line width for the ROC curve. See par for more details.

type

type of plotting as in plot.

identity

logical: whether or not the identity line (no discrimination line) must be displayed. Default: only on new plots.

identity.col, identity.lty, identity.lwd

color, line type and line width for the identity line. Used only if identity=TRUE. See par for more details.

print.thres

Should a selected set of thresholds be displayed on the ROC curve? FALSE, NULL or no: no threshold is displayed. TRUE or best: the threshold with the highest sum sensitivity + spe

print.thres.pch, print.thres.adj, print.thres.col, print.thres.cex

the plotting character (pch), text string adjustment (adj), color (col) and character expansion factor (cex) parameters for the printing of the thresholds. See points and par f

print.thres.pattern

the text pattern for the thresholds, as a sprintf format. Three numerics are passed to sprintf: threshold, specificity, sensitivity.

print.thres.pattern.cex

the character expansion factor (cex) for the threshold text pattern. See par for more details.

print.auc

boolean. Should the numeric value of AUC be printed on the plot?

print.auc.pattern

the text pattern for the AUC, as a sprintf format. If NULL, a reasonable value is computed that takes partial AUC, CI and percent into account. If the CI of the AUC was computed, three numerics are passed to

print.auc.x, print.auc.y

x and y position for the printing of the AUC.

print.auc.adj, print.auc.cex, print.auc.col

the text adjustment, character expansion factor and color for the printing of the AUC. See par for more details.

grid

boolean or numeric vector of length 1 or 2. Should a background grid be added to the plot? Numeric: show a grid with the specified interval between each line; Logical: show the grid or not. Length 1: same values are taken for horizontal and ve

grid.v, grid.h

numeric. The x and y values at which a vertical or horizontal line (respectively) must be drawn. NULL if no line must be added.

grid.lty, grid.lwd, grid.col

the line type (lty), line width (lwd) and color (col) of the lines of the grid. See par for more details. Note that you can pass vectors of length 2, in which case it specifies the vertical (1) and horizontal (2

auc.polygon

boolean. Whether or not to display the area as a polygon.

auc.polygon.col, auc.polygon.lty, auc.polygon.density, auc.polygon.angle, auc.polygon.border

color (col), line type (lty), density, angle and border for the AUC polygon. See polygon and par for more details.

max.auc.polygon

boolean. Whether or not to display the maximal possible area as a polygon.

max.auc.polygon.col, max.auc.polygon.lty, max.auc.polygon.density, max.auc.polygon.angle, max.auc.polygon.border

color (col), line type (lty), density, angle and border for the maximum AUC polygon. See polygon and par for more details.

boolean. Should we plot the confidence intervals?

ci.type, ci.col

type and col arguments for plot.ci. The special value no disables the plotting of confidence intervals.

...

further arguments passed to or from other methods, especially arguments for roc and plot.roc.roc when calling plot.roc.default or plot.roc.formula. Note that the

Value

This function returns a list of class roc invisibly. See roc for more details.

encoding

UTF-8

AUC specification

For print.auc, auc.polygon and max.auc.polygon arguments, an AUC specification is required. By default, the total AUC is plotted, but you may want a partial AUCs. The specification is defined by:

theaucfield in therocobject ifreuse.aucis set toTRUE(default). It is naturally inherited from any call torocand fits most cases.
passing the specification toaucwith...(argumentspartial.auc,partial.auc.correctandpartial.auc.focus). In this case, you must ensure either that therocobject do not contain anaucfield (if you calledrocwithauc=FALSE), or setreuse.auc=FALSE.

If reuse.auc=FALSE the auc function will always be called with ... to determine the specification, even if the roc object do contain an auc field.

As well if the roc object do not contain an auc field, the auc function will always be called with ... to determine the specification.

Warning: if the roc object passed to plot.roc contains an auc field and reuse.auc=TRUE, auc is not called and arguments such as partial.auc are silently ignored.

Details

This function is typically called from roc when plot=TRUE (not by default). plot.roc.formula and plot.roc.default are convenience methods that build the ROC curve (with the roc function) before calling plot.roc.roc. You can pass them arguments for both roc and plot.roc.roc. Simply use plot.roc that will dispatch to the correct method.

The plotting is done in the following order:

A new plot is created ifadd=FALSE.
The grid is added ifgrid.vandgrid.hare not NULL.
The maximal AUC polygon is added ifmax.auc.polygon=TRUE.
The CI shape is added ifci=TRUE,ci.type="shape"andx$ciisn't aci.auc.
The AUC polygon is added ifauc.polygon=TRUE.
The identity line ifidentity=TRUE.
The actual ROC line is added.
The CI bars are added ifci=TRUE,ci.type="bars"andx$ciisn't aci.auc.
The selected thresholds are printed ifprint.thresisTRUEor numeric.
The AUC is printed ifprint.auc=TRUE.

Graphical functions are called with suppressWarnings.

Examples

Run this code

data(aSAH)

# Syntax (response, predictor):
plot.roc(aSAH$outcome, aSAH$s100b)

# With a roc object:
rocobj <- roc(aSAH$outcome, aSAH$s100b)
# identical:
plot(rocobj)
plot.roc(rocobj)

# Add a smoothed ROC:
plot.roc(smooth(rocobj), add=TRUE, col="blue")
legend("bottomright", legend=c("Empirical", "Smoothed"),
       col=c(par("fg"), "blue"), lwd=2)

# With more options:
plot(rocobj, print.auc=TRUE, auc.polygon=TRUE, grid=c(0.1, 0.2),
     grid.col=c("green", "red"), max.auc.polygon=TRUE,
     auc.polygon.col="blue", print.thres=TRUE)

# To plot a different partial AUC, we need to ignore the existing value
# with reuse.auc=FALSE:
plot(rocobj, print.auc=TRUE, auc.polygon=TRUE, partial.auc=c(1, 0.8),
     partial.auc.focus="se", grid=c(0.1, 0.2), grid.col=c("green", "red"),
     max.auc.polygon=TRUE, auc.polygon.col="blue", print.thres=TRUE,
     reuse.auc=FALSE)

# Add a line to the previous plot:
plot.roc(aSAH$outcome, aSAH$wfns, add=TRUE)

# Alternatively, you can get the plot directly from roc():
roc(aSAH$outcome, aSAH$s100b, plot=TRUE)

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