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ROC Curve Geom for Causal Inference

Source: R/geom_roc.R
geom_roc.Rd

A ggplot2 geom for plotting ROC curves with optional weighting. Emphasizes the balance interpretation where AUC around 0.5 indicates good balance.

Usage

geom_roc(
  mapping = NULL,
  data = NULL,
  stat = "roc",
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  linewidth = 0.5,
  treatment_level = NULL,
  ...
)

Arguments

mapping

Set of aesthetic mappings. Must include estimate (propensity scores/predictions) and truth (treatment/outcome variable). If specified, inherits from the plot.

data

Data frame to use. If not specified, inherits from the plot.

stat

Statistical transformation to use. Default is "roc".

position

Position adjustment. Default is "identity".

na.rm

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

show.legend

Logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped.

inherit.aes

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

linewidth

Width of the ROC curve line. Default is 0.5.

treatment_level

The level of the outcome variable to consider as the treatment/event. If NULL (default), uses the last level for factors or the maximum value for numeric variables.

...

Other arguments passed on to layer().

Value

A ggplot2 layer.

See also

check_auc() for computing AUC values, stat_roc() for the underlying stat

Other ggplot2 functions: geom_calibration(), geom_ecdf(), geom_mirror_density(), geom_mirror_histogram(), geom_qq2()

Examples

# Basic usage
library(ggplot2)
ggplot(nhefs_weights, aes(estimate = .fitted, truth = qsmk)) +
  geom_roc() +
  geom_abline(intercept = 0, slope = 1, linetype = "dashed")


# With grouping by weight
long_data <- tidyr::pivot_longer(
  nhefs_weights,
  cols = c(w_ate, w_att),
  names_to = "weight_type",
  values_to = "weight"
)

ggplot(long_data, aes(estimate = .fitted, truth = qsmk, weight = weight)) +
  geom_roc(aes(color = weight_type)) +
  geom_abline(intercept = 0, slope = 1, linetype = "dashed")