ggdecision: The Decision curve
In raptools: Risk Assessment Plot and Reclassification Metrics

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ggdecision

R Documentation

The Decision curve

Description

ggdecision plots decision curves to assess the net benefit at different thresholds

Usage

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

ggdecision(
  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 calculated 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

References

Vickers AJ, van Calster B, Steyerberg EW. A simple, step-by-step guide to interpreting decision curve analysis. Diagn Progn Res 2019;3(1):18. 2. Zhang Z, Rousson V, Lee W-C, et al. Decision curve analysis: a technical note. Ann Transl Med 2018;6(15):308-308.

raptools documentation built on Oct. 1, 2026, 5:12 p.m.