plot_decision_curve: Decision Curve from Performance Data

In uriahf/rtichoke: rtichoke

Decision Curve from Performance Data

Description

Plot a Precision decision Curve

Usage

plot_decision_curve(
  performance_data,
  chosen_threshold = NA,
  interactive = TRUE,
  color_values = c("#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#07004D", "#E6AB02",
    "#FE5F55", "#54494B", "#006E90", "#BC96E6", "#52050A", "#1F271B", "#BE7C4D",
    "#63768D", "#08A045", "#320A28", "#82FF9E", "#2176FF", "#D1603D", "#585123"),
  size = NULL,
  type = "conventional",
  min_p_threshold = 0,
  max_p_threshold = 1
)

Arguments

performance_data	an rtichoke Performance Data
chosen_threshold	a chosen threshold to display (for non-interactive)
interactive	whether the plot should be interactive plots
color_values	color palette
size	the size of the curve
type	What type of Decision Curve, default choice is "conventional". Alternatives are "interventions avoided" and "combined" for both "conventional" and "interventions avoided" on the same view.
min_p_threshold	The minimum Probability Threshold value to be displayed
max_p_threshold	The maximum Probability Threshold value to be displayed

Examples

## Not run: 


one_pop_one_model %>%
  plot_decision_curve()

one_pop_one_model %>%
  plot_decision_curve(type = "interventions avoided")

one_pop_one_model %>%
  plot_decision_curve(type = "combined")

multiple_models %>%
  plot_decision_curve()

multiple_models %>%
  plot_decision_curve(type = "interventions avoided")

multiple_models %>%
  plot_decision_curve(type = "combined")

multiple_populations %>%
  plot_decision_curve()

multiple_populations %>%
  plot_decision_curve(type = "interventions avoided")

multiple_populations %>%
  plot_decision_curve(type = "combined")

## End(Not run)

uriahf/rtichoke documentation built on Nov. 22, 2023, 1:30 a.m.