Plot a ROC with CI95

Plots a ROC curve with bootstrapped 95% confidence interval boundary overlay.

Usage

plot_boot_roc(
  truth,
  predicted,
  pos_class,
  shade_color = "black",
  nboot = 1000,
  r_seed = 101,
  add = FALSE,
  ...
)

Arguments

truth

character(n) or factor(n). A vector of true class names. In most instances you will have to also pass a pos_class argument defining the positive/event class.

predicted

numeric(n). A numeric vector of class probabilities.

pos_class

character(1). Name of the "positive" or "event" class.

shade_color

The color for the bootstrap shaded region. Passed as a fill argument to downstream ggplot2 machinery.

nboot

integer(1). The number of bootstrap estimates to perform.

r_seed

`integer(1). The value of the random seed if reproducibility is desired.

add

Logical. Should a plotting layer be added to an existing plot?

...

Additional arguments passed to geom_roc(), e.g. color =.

See also

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

Author

Stu Field, Amanda Hiser

Examples

n <- 75
true <- rep(c("control", "disease"), each = n)
pred <- withr::with_seed(1, c(rnorm(n, 0.2, 0.3), rnorm(n, 0.8, 0.3)))
plot_boot_roc(true, pred, pos_class = "disease", nboot = 200, color = "blue")


# add layer
pred2 <- withr::with_seed(1, c(rnorm(n, 0.2, 0.3), rnorm(n, 0.5, 0.3)))
plot_boot_roc(true, pred, pos_class = "disease", nboot = 200,
              shade_color = "blue", color = "blue") +
plot_boot_roc(true, pred2, pos_class = "disease", nboot = 200,
              shade_color = "green", color = "red", add = TRUE)