ggdecision: 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
)

Value

a ggplot

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)

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.