Type: Package

Title: Generate Useful ROC Curve Charts for Print and Interactive Use

Version: 2.3.3

Date: 2025年08月22日

Maintainer: Michael C. Sachs <sachsmc@gmail.com>

Description: Most ROC curve plots obscure the cutoff values and inhibit interpretation and comparison of multiple curves. This attempts to address those shortcomings by providing plotting and interactive tools. Functions are provided to generate an interactive ROC curve plot for web use, and print versions. A Shiny application implementing the functions is also included.

License: MIT + file LICENSE

Encoding: UTF-8

URL: https://sachsmc.github.io/plotROC/

BugReports: https://github.com/sachsmc/plotROC/issues/

Depends: R (≥ 3.0.0), ggplot2

Imports: methods, grid, gridSVG, shiny, plyr, rlang

Suggests: knitr, testthat, stringr, survivalROC, rmarkdown

VignetteBuilder: knitr

RoxygenNote: 7.3.2

NeedsCompilation: no

Packaged: 2025年08月25日 10:51:54 UTC; micsac

Author: Michael C. Sachs [aut, cre], Robert W. Corty [ctb], Luis Crouch [ctb] (Modification to calc_auc)

Repository: CRAN

Date/Publication: 2025年08月25日 11:30:03 UTC

D.ex <- rbinom(50, 1, .5)
rocdata <- data.frame(D = c(D.ex, D.ex), 
 M = c(rnorm(50, mean = D.ex, sd = .4), rnorm(50, mean = D.ex, sd = 1)), 
 Z = c(rep("A", 50), rep("B", 50)))
ggplot(rocdata, aes(m = M, d = D)) + geom_roc() + geom_rocci()
ggplot(rocdata, aes(m = M, d = D)) + geom_roc() + style_roc()
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc() + geom_rocci()
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc() + geom_rocci(sig.level = .01)
ggplot(rocdata, aes(m = M, d = D)) + geom_roc(n.cuts = 0) + 
geom_rocci(ci.at = quantile(rocdata$M, c(.1, .25, .5, .75, .9)))
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc() + geom_rocci(linetype = 1)
rocplot <- ggplot(rocdata, aes(m = M, d = D)) + geom_roc()
plot_interactive_roc(rocplot)
plot_interactive_roc(rocplot + aes(color = Z))
plot_interactive_roc(rocplot + facet_wrap( ~ Z))

GeomRoc
geom_roc(
 mapping = NULL,
 data = NULL,
 stat = "roc",
 n.cuts = 10,
 arrow = NULL,
 lineend = "butt",
 linejoin = "round",
 linemitre = 1,
 linealpha = 1,
 pointalpha = 1,
 pointsize = 0.5,
 labels = TRUE,
 labelsize = 3.88,
 labelround = 1,
 na.rm = TRUE,
 cutoffs.at = NULL,
 cutoff.labels = NULL,
 position = "identity",
 show.legend = NA,
 inherit.aes = TRUE,
 ...
)

mapping

Set of aesthetic mappings created by aes() . If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot() .

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

Use to override the default connection between geom_roc and stat_roc.

n.cuts

Number of cutpoints to display along each curve

arrow

Arrow specification, as created by arrow

lineend

Line end style (round, butt, square)

linejoin

Line join style (round, mitre, bevel)

linemitre

Line mitre limit (number greater than 1)

linealpha

Alpha level for the lines, alpha.line is deprecated

pointalpha

Alpha level for the cutoff points, alpha.point is deprecated

pointsize

Size of cutoff points, size.point is deprecated

labels

Logical, display cutoff text labels

labelsize

Size of cutoff text labels

labelround

Integer, number of significant digits to round cutoff labels

na.rm

Remove missing values from curve

cutoffs.at

Vector of user supplied cutoffs to plot as points. If non-NULL, it will override the values of n.cuts and plot the observed cutoffs closest to the user-supplied ones.

cutoff.labels

vector of user-supplied labels for the cutoffs. Must be a character vector of the same length as cutoffs.at.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

• The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

• A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

• For more information and other ways to specify the position, see the layer position documentation.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them.

...

Other arguments passed on to layer() 's params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

• Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

• When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

• Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

• The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

D.ex <- rbinom(50, 1, .5)
rocdata <- data.frame(D = c(D.ex, D.ex), 
 M = c(rnorm(50, mean = D.ex, sd = .4), rnorm(50, mean = D.ex, sd = 1)), 
 Z = c(rep("A", 50), rep("B", 50)))
ggplot(rocdata, aes(m = M, d = D)) + geom_roc()
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc()
ggplot(rocdata, aes(m = M, d = D)) + geom_roc() + facet_wrap(~ Z)
ggplot(rocdata, aes(m = M, d = D)) + geom_roc(n.cuts = 20)
ggplot(rocdata, aes(m = M, d = D)) + geom_roc(cutoffs.at = c(1.5, 1, .5, 0, -.5))
ggplot(rocdata, aes(m = M, d = D)) + geom_roc(labels = FALSE)
ggplot(rocdata, aes(m = M, d = D)) + geom_roc(size = 1.25)

StatRoc
stat_roc(
 mapping = NULL,
 data = NULL,
 geom = "roc",
 position = "identity",
 show.legend = NA,
 inherit.aes = TRUE,
 na.rm = TRUE,
 max.num.points = 1000,
 increasing = TRUE,
 ...
)

mapping

Set of aesthetic mappings created by aes() . If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot() .

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use to display the data for this layer. When using a ⁠stat_*()⁠ function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

• A Geom ggproto subclass, for example GeomPoint.

• A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".

• For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

• The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

• A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

• For more information and other ways to specify the position, see the layer position documentation.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them.

na.rm

Remove missing observations

max.num.points

maximum number of points to plot

increasing

TRUE (default) if M is positively associated with Pr(D = 1), if FALSE, assumes M is negatively associated with Pr(D = 1)

...

Other arguments passed on to layer() 's params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

• Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

• When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

• Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

• The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

D.ex <- rbinom(50, 1, .5)
rocdata <- data.frame(D = c(D.ex, D.ex), 
 M = c(rnorm(50, mean = D.ex, sd = .4), rnorm(50, mean = D.ex, sd = 1)), 
 Z = c(rep("A", 50), rep("B", 50)))
ggplot(rocdata, aes(m = M, d = D)) + stat_roc()

StatRocci
stat_rocci(
 mapping = NULL,
 data = NULL,
 geom = "rocci",
 position = "identity",
 show.legend = NA,
 inherit.aes = TRUE,
 ci.at = NULL,
 sig.level = 0.05,
 na.rm = TRUE,
 ...
)

mapping

Set of aesthetic mappings created by aes() . If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot() .

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

geom

The geometric object to use to display the data for this layer. When using a ⁠stat_*()⁠ function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

• A Geom ggproto subclass, for example GeomPoint.

• A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".

• For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

• The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

• A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

• For more information and other ways to specify the position, see the layer position documentation.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them.

ci.at

Vector of cutoffs at which to display confidence regions. If NULL, will automatically choose 3 evenly spaced points to display the regions

sig.level

Significance level for the confidence regions

na.rm

Remove missing observations

...

Other arguments passed on to layer() 's params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

• Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

• When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

• Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

• The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

D.ex <- rbinom(50, 1, .5)
rocdata <- data.frame(D = c(D.ex, D.ex), 
 M = c(rnorm(50, mean = D.ex, sd = .4), rnorm(50, mean = D.ex, sd = 1)), 
 Z = c(rep("A", 50), rep("B", 50)))
ggplot(rocdata, aes(m = M, d = D)) + geom_roc() + stat_rocci()
ggplot(rocdata, aes(m = M, d = D)) + geom_roc() + 
stat_rocci(ci.at = quantile(rocdata$M, c(.1, .3, .5, .7, .9)))

calc_auc(ggroc)

ggroc

A ggplot object that contains a GeomRoc layer

D.ex <- rbinom(50, 1, .5)
rocdata <- data.frame(D = c(D.ex, D.ex),
 M = c(rnorm(50, mean = D.ex, sd = .4), rnorm(50, mean = D.ex, sd = 1)),
 Z = c(rep("A", 50), rep("B", 50)))
ggroc <- ggplot(rocdata, aes(m = M, d = D)) + geom_roc()
calc_auc(ggroc)
ggroc2 <- ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc()
calc_auc(ggroc2)

calculate_multi_roc(data, M_string, D_string)

data

data frame containing at least 1 marker and the common class labels, coded as 0 and 1

M_string

vector of marker column names

D_string

class label column name

calculate_roc(M, D, ci = FALSE, alpha = 0.05)

M

continuous marker values or predictions of class labels

D

class labels, must be coded as 0 and 1. If not numeric with 0/1, then plotROC assumes the first level in sort order is healthy status, with a warning.

ci

Logical, if true, will calculate exact joint confidence regions for the TPF and FPF

alpha

Confidence level, ignored if ci = FALSE

direct_label(
 ggroc_p,
 labels = NULL,
 label.angle = 45,
 nudge_x = 0,
 nudge_y = 0,
 size = 6,
 ...
)

ggroc_p

A ggplot object that contains a geom_roc layer

labels

vector of labels to add directly to the plot next to the curves. If multiple curves, must be in the same order as the grouping factor. If NULL, attempts to determine labels from the ggroc_p object

label.angle

angle of adjustment for the direct labels

nudge_x, nudge_y

Horizontal and vertical adjustment to nudge labels by. These can be scalars or vectors the same length as the number of labels

size

Size of labels

...

Other arguments passed to annotate

export_interactive_roc(
 ggroc_p,
 add.cis = TRUE,
 hide.points = FALSE,
 prefix = "a",
 width = 6,
 height = 6,
 omit.js = FALSE,
 style = style_roc(theme = theme_grey()),
 ...
)

ggroc_p

A ggplot object with a GeomRoc layer and optionally a GeomRocci layer as returned by geom_roc and/or geom_rocci. It can be modified with annotations, themes, etc.

add.cis

Logical, if true, removes the current confidence interval layer (if present) and replaces it with a denser layer of confidence regions

hide.points

Logical, if true, hides points layer so that points with cutoff values are only visible when hovering. Recommended for plots containing more than 3 curves.

prefix

A string to assign to the objects within the svg. Enables unique identification by the javascript code

width, height

Width and height in inches of plot

omit.js

Logical. If true, omit inclusion of javascript source in output. Useful for documents with multiple interactive plots

style

A call to the function style_roc

...

Other arguments passed to geom_rocci when add.cis = TRUE

geom_rocci(
 mapping = NULL,
 data = NULL,
 stat = "rocci",
 ci.at = NULL,
 sig.level = 0.05,
 na.rm = TRUE,
 alpha.box = 0.3,
 labels = TRUE,
 labelsize = 3.88,
 labelround = 1,
 position = "identity",
 show.legend = NA,
 inherit.aes = TRUE,
 ...
)
GeomRocci

mapping

Set of aesthetic mappings created by aes() . If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot() .

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

Use to override the default connection between geom_rocci and stat_rocci.

ci.at

Vector of values in the range of the biomarker where confidence regions will be displayed

sig.level

Significance level for the confidence regions

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

alpha.box

Alpha level for the confidence regions

labels

If TRUE, adds text labels for the cutoffs where the confidence regions are displayed

labelsize

Size of cutoff text labels

labelround

Integer, number of significant digits to round cutoff labels

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

• The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.

• A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".

• For more information and other ways to specify the position, see the layer position documentation.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them.

...

Other arguments passed on to layer() 's params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

• Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

• When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

• Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

• The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

D.ex <- rbinom(50, 1, .5)
rocdata <- data.frame(D = c(D.ex, D.ex), 
 M = c(rnorm(50, mean = D.ex, sd = .4), rnorm(50, mean = D.ex, sd = 1)), 
 Z = c(rep("A", 50), rep("B", 50)))
ggplot(rocdata, aes(m = M, d = D)) + geom_roc() + geom_rocci()
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc() + geom_rocci()
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc() + geom_rocci(sig.level = .01)
ggplot(rocdata, aes(m = M, d = D)) + geom_roc(n.cuts = 0) + 
geom_rocci(ci.at = quantile(rocdata$M, c(.1, .25, .5, .75, .9)))
ggplot(rocdata, aes(m = M, d = D, color = Z)) + geom_roc() + geom_rocci(linetype = 1)

getD3()

ggroc(
 rocdata,
 fpf_string = "FPF",
 tpf_string = "TPF",
 c_string = "c",
 ci = FALSE,
 label = NULL,
 label.adj.x = 0,
 label.adj.y = 0,
 label.angle = 45,
 plotmath = FALSE,
 xlabel = "False positive fraction",
 ylabel = "True positive fraction"
)

rocdata

Data frame containing true and false positive fractions, and cutoff values

fpf_string

Column name identifying false positive fraction column

tpf_string

Column name identifying true positive fraction column

c_string

Column name identifying cutoff values

ci

Logical, not supported

label

Not supported

label.adj.x

Not supported

label.adj.y

Not supported

label.angle

Not supported

plotmath

Not supported

xlabel

Defaults to "False positive fraction"

ylabel

Defaults to "True positive fraction"

melt_roc(data, d, m, names = NULL)

data

Data frame containing disease status and biomarkers stored in columns

d

Column containing binary disease status. Can be a column name or index

m

Vector of column names or indices identifying biomarkers

names

Optional vector of names to assign to the biomarkers. If NULL, names will be taken from the column names

D.ex <- rbinom(50, 1, .5)
widedata <- data.frame(D = D.ex, M1 = rnorm(50, mean = D.ex, sd = 1), 
 M2 = rnorm(50, mean = D.ex, sd = .5))
longdata <- melt_roc(widedata, "D", c("M1", "M2"))
ggplot(longdata, aes(d = D, m = M, color = name)) + geom_roc()

multi_ggroc(
 datalist,
 fpf_string = rep("FPF", length(datalist)),
 tpf_string = rep("TPF", length(datalist)),
 c_string = rep("c", length(datalist)),
 label = NULL,
 legend = TRUE,
 label.adj.x = rep(0, length(datalist)),
 label.adj.y = rep(0, length(datalist)),
 label.angle = rep(45, length(datalist)),
 plotmath = FALSE,
 xlabel = "False positive fraction",
 ylabel = "True positive fraction"
)

datalist

List of data frames each containing true and false positive fractions and cutoffs

fpf_string

Column names identifying false positive fraction

tpf_string

Column names identifying true positive fraction

c_string

Column names identifying cutoff values

label

Not supported.

legend

If true, draws legend

label.adj.x

Not supported.

label.adj.y

Not supported.

label.angle

Not supported.

plotmath

Logical. Not supported.

xlabel

Defaults to "False positive fraction"

ylabel

Defaults to "True positive fraction"

plot_interactive_roc(ggroc, file = NULL, ...)

ggroc

An object as returned by ggroc or multi_ggroc. It can be modified with annotations, themes, etc.

file

A path to save the result to. If NULL, will save to a temporary directory

...

arguments passed to export_interactive_roc

plot_journal_roc(
 ggroc_p,
 font.size = 3,
 n.cuts = 20,
 ci.at = NULL,
 opacity = 0.3,
 lty = NULL,
 color = NULL,
 lwd = NULL,
 legend = FALSE
)

ggroc_p

An object as returned by ggroc or multi_ggroc. It can be modified with annotations, themes, etc.

font.size

Not supported

n.cuts

Not supported

ci.at

Not supported

opacity

Not supported

lty

Not supported

color

Not supported

lwd

Not supported

legend

Not supported

roc_key(data, params, size)

data

Data created by stat

params

parameters

size

Size

shiny_plotROC()

style_roc(
 major.breaks = c(0, 0.1, 0.25, 0.5, 0.75, 0.9, 1),
 minor.breaks = c(seq(0, 0.1, by = 0.01), seq(0.9, 1, by = 0.01)),
 guide = TRUE,
 guide_col = NULL,
 xlab = "False positive fraction",
 ylab = "True positive fraction",
 theme = theme_bw
)

major.breaks

vector of breakpoints for the major gridlines and axes

minor.breaks

vector of breakpoints for the minor gridlines and axes

guide

logical, if TRUE draws diagonal guideline

guide_col

character, if guide is TRUE sets colour of diagonal guideline. Takes precedence over colour set by a theme.

xlab

X-axis label

ylab

Y-axis label

theme

Theme function compatible with ggplot2

D.ex <- rbinom(50, 1, .5)
fakedata <- data.frame(M1 = rnorm(50, mean = D.ex), 
 D = D.ex)
ggplot(fakedata, aes(m = M1, d = D)) + geom_roc() + style_roc()
ggplot(fakedata, aes(m = M1, d = D)) + geom_roc() + style_roc(xlab = "1 - Specificity")
ggplot(fakedata, aes(m = M1, d = D)) + geom_roc() + style_roc(theme = theme_grey)

verify_d(D)

D

Vector that will be checked for 2-class labels

verify_d(c(1, 0, 1))
## Not run: 
verify_d(c(TRUE, FALSE, TRUE)) #warning
verify_d(c("Dead", "Alive", "Dead")) #warning
verify_d(c("Disease", "Healthy", "Missing")) #error
## End(Not run)