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Plot a ROC Curve

geom_roc.Rd

Create a "geom" layer to generate a receiver operator criterion (ROC) curve in the ggplot2 style grammar of graphics. Its primary input is the output of roc_xy(), and is used primarily used in support of the wrapper plot_emp_roc().

Usage

geom_roc(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = FALSE,
  shape = NULL,
  size = 2,
  lwd = 1,
  outline = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

geom_rocfit(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...
)

Arguments

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

A data.frame containing "x" and "y" coordinates corresponding to an empirical ROC curve. This is result of a call to roc_xy(), and corresponds to the 1 - "tnr" and "tpr" values respectively.

stat

The statistical transformation to use on the data for this layer. When using a geom_*() function to construct a layer, the stat argument can be used to override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

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

na.rm

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

shape

numeric(1). Shape of points (between 0 and 25), similar to pch of graphics::points(). See ggplot2::geom_point().

size

numeric(1). Size of points. Similar to cex of graphics::points(). Modifying size will not affect the plot if shape is set to NULL (the default). See [geom_point())].

[geom_point())]: R:geom_point())

lwd

numeric(1). Line width (see par()).

outline

logical(1). Should black outlines be drawn around the main plot line?

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. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().

...

Additional arguments passed to ggplot2::layer(), often lty, shape, lwd, etc.

Functions

  • geom_rocfit(): Add a fitted line (layer) to ROC.

See also

roc_xy(), calc_roc_fit(), ggplot2::geom_line(), ggplot2::layer()

Other ROC: calc_roc_fit(), create_roc_data(), plot_boot_roc(), plot_emp_roc(), roc_xy()

Author

Stu Field, Amanda Hiser

Examples

library(ggplot2)

# Generate dummy data
true <- rep(c("control", "disease"), each = 10)
pred <- withr::with_seed(8,
  c(rnorm(10, mean = 0.4, sd = 0.2),
    rnorm(10, mean = 0.6, sd = 0.2))
)
rocxy <- roc_xy(true, pred, "disease") |> data.frame()

# Plotting options
ggplot(rocxy, aes(x = x, y = y)) + geom_roc()

ggplot(rocxy, aes(x = x, y = y)) + geom_roc(col = "blue")

ggplot(rocxy, aes(x = x, y = y)) + geom_roc(col = "blue", outline = FALSE)


# Draw a fit line with `geom_rocfit()`
# (to add a fit-layer, you *must* pass the data argument)
ggplot(rocxy, aes(x = x, y = y)) + geom_rocfit(data = rocxy)


# Layer a fit line over a ROC curve
ggplot(rocxy, aes(x = x, y = y)) +
  geom_roc(col = "blue") +
  geom_rocfit(data = rocxy, col = "red", linetype = "dashed")


# Multiple curves can be drawn on the same plot.
# First, generate a 2nd set of dummy data
true2 <- rep(c("control", "disease"), each = 20)
pred2 <- withr::with_seed(9,
  c(rnorm(20, mean = 0.4, sd = 0.2),
    rnorm(20, mean = 0.8, sd = 0.2))
)

# Cast input to a data frame (this is required for ggplot)
rocxy2 <- roc_xy(true2, pred2, "disease") |> data.frame()

# The 2nd line can be added via standard `+` ggplot2 syntax,
# but the data argument must be passed for each geom, as each curve was
# generated from a unique dataset
ggplot() +
  geom_roc(aes(x = x, y = y), data = rocxy, col = "red") +
  geom_roc(aes(x = x, y = y), data = rocxy2, col = "blue")