ROC curve

Plots the receiver operating characteristic (ROC) curve for a binary classifier and reports the area under the curve (AUC). The input can be a fitted binomial glm, a pair of vectors (observed binary outcome and a continuous score), or, to compare several models, a named list of models or of (actual, score) pairs, which are overlaid as colour-coded curves with a legend and a per-curve AUC. An optional bootstrap confidence band can be drawn for the (single-model) curve and its AUC, and the Youden's J operating point can be marked.

Usage

roc_curve_plot(
  x,
  score = NULL,
  colour = depictr_brand(),
  ci = FALSE,
  conf_level = 0.95,
  youden = FALSE,
  legend_inside = FALSE,
  title = NULL
)

Arguments

x

A binomial glm; the vector of observed outcomes (0/1, logical or a two-level factor with the positive class second); or a named list of models / (actual, score) pairs to overlay (see Details).

score

When x is an outcome vector, the matching vector of scores or predicted probabilities. When x is a named list of outcome vectors, a matching named/positional list of score vectors.

colour

Curve colour for the single-model case. Defaults to the depictr brand blue. Ignored when several models are overlaid (the colourblind-aware scale_colour_depictr() palette is used instead).

ci

Bootstrap confidence band for a single ROC curve and its AUC. FALSE (default) draws none; TRUE uses 2000 resamples; a positive integer sets the number of resamples. Ignored when several models are overlaid.

conf_level

Confidence level for the bootstrap band.

youden

Logical; if TRUE, mark the Youden's J operating point (the threshold maximising sensitivity + specificity - 1) on each curve.

legend_inside

When TRUE (and several models are overlaid), draw the legend inside the panel (in the bottom-right corner the curve leaves empty) over a translucent background, instead of in a right-hand margin. Defaults to FALSE.

title

Plot title.

Value

A ggplot2::ggplot object. The AUC(s) are stored in attr(plot, "auc") (a named vector when several models are supplied).

Details

A named list overlays one curve per element, e.g. roc_curve_plot(list("Full" = fit_full, "Reduced" = fit_reduced)). Each element may be a glm, a length-2 list/data frame of (actual, score), or an outcome vector paired with the matching element of a score list. Single-model calls are unchanged.

Examples

gfit <- glm(accuracy ~ word_frequency + condition + RT,
            data = lexical_decision, family = binomial)
roc_curve_plot(gfit)


# Mark the Youden operating point and add a bootstrap band.
roc_curve_plot(gfit, youden = TRUE, ci = 200)


# Compare two models with a colour-coded legend and per-curve AUC.
reduced <- glm(accuracy ~ word_frequency, data = lexical_decision,
               family = binomial)
roc_curve_plot(list(Full = gfit, Reduced = reduced))