R: Calculate the empirical Receiver Operating Characteristic...

StatRoc {plotROC}

R Documentation

Calculate the empirical Receiver Operating Characteristic curve

Description

Given a binary outcome d and continuous measurement m, computes the empirical ROC curve for assessing the classification accuracy of m

Usage

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, ...)

Arguments

`mapping`	Set of aesthetic mappings created by `aes` or `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.
`geom`	The geometric object to use display the data
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function.
`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.
`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. `borders`.
`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`. These are often aesthetics, used to set an aesthetic to a fixed value, like `color = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.

Format

An object of class StatRoc (inherits from Stat, ggproto) of length 5.

Aesthetics

stat_roc understands the following aesthetics (required aesthetics are in bold):

m The continuous biomarker/predictor
d The binary outcome, if not coded as 0/1, the smallest level in sort order is assumed to be 0, with a warning
alpha Controls the label alpha, see also linealpha and pointalpha
color
linetype
size Controls the line weight, see also pointsize and labelsize

Computed variables

false_positive_fraction: estimate of false positive fraction
true_positive_fraction: estimate of true positive fraction
cutoffs: values of m at which estimates are calculated

Examples

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()

[Package plotROC version 2.2.1 Index]