Skip to contents

The Precision-Recall plot

Source: R/raptools.R
ggprerec.Rd

ggprerec plots Precision (PPV) v Recall (Sensitivity)

Usage

ggprerec(
  x1,
  x2 = NULL,
  y = NULL,
  show_smooth = TRUE,
  smooth_method = "loess",
  smooth_span = 0.75,
  smooth_se = FALSE
)

Arguments

x1

Either a logistic regression fitted using glm (base package) or lrm (rms package) or alculated probabilities (eg through a logistic regression model) of the baseline model. Must be between 0 & 1

x2

Either a logistic regression fitted using glm (base package) or lrm (rms package) or calculated probabilities (eg through a logistic regression model) of the new (alternative) model. Must be between 0 & 1

y

Binary of outcome of interest. Must be 0 or 1 (if fitted models are provided this is extracted from the fit which for an rms fit must have x = TRUE, y = TRUE).

show_smooth

Logical, whether to display smoothed curves (default = TRUE)

smooth_method

Smoothing method for geom_smooth. Options: "loess", "lm", "glm", "gam". Default is "loess"

smooth_span

Span parameter for loess smoothing, controls the degree of smoothing (default = 0.75). Lower values = less smooth

smooth_se

Logical, whether to display confidence interval around smooth (default = FALSE)

Value

A ggplot object displaying the precision-recall curve(s) with recall (sensitivity) on the x-axis and precision (positive predictive value) on the y-axis. If two models are provided, both curves are shown for comparison.