plot_clinical_impact: Plot the clinical impact curve from a DecisionCurve object.

Description Usage Arguments Examples

View source: R/plot_functions_main.R

Description

For a given population size, plot the number of subjects classified as high risk, and the number of subjects classified high risk with the outcome of interest at each high risk threshold.

Usage

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plot_clinical_impact(x, population.size = 1000, cost.benefit.axis = TRUE,
  n.cost.benefits = 6, cost.benefits, confidence.intervals, col = "black",
  lty = 1, lwd = 2, xlim, ylim, xlab, ylab,
  cost.benefit.xlab = "Cost:Benefit Ratio", legend.position = c("topright",
  "right", "bottomright", "bottom", "bottomleft", "left", "topleft", "top",
  "none"), ...)

Arguments

x

decision_curve object to plot. Assumes output from function 'decision_curve'

population.size

Hypothetical population size (default 1000).

cost.benefit.axis

logical (default TRUE) indicating whether to print an additional x-axis showing relative cost:benefit ratios in addition to risk thresholds.

n.cost.benefits

number of cost:benefit ratios to print if cost.benefit.axis = TRUE (default n.cost.benefit = 6).

cost.benefits

Character vector of the form c("c1:b1", "c2:b2", ..., "cn:bn") with integers ci, bi corresponding to specific cost:benefit ratios to print. Default allows the function to calculate these automatically.

confidence.intervals

logical indicating whether to plot confidence intervals.

col

vector of length two indicating the color for the number high risk and the second to the number high risk with outcome, respectively.

lty

vector of linetypes. The first element corresponds to the number high risk and the second to the number high risk with outcome.

lwd

vector of linewidths. The first element corresponds to the number high risk and the second to the number high risk with outcome.

xlim

vector giving c(min, max) of x-axis. Defaults to c(min(thresholds), max(thresholds)).

ylim

vector giving c(min, max) of y-axis.

xlab

label of main x-axis.

ylab

label of y-axis.

cost.benefit.xlab

label of cost:benefit ratio axis.

legend.position

character vector giving position of legend. Options are "topright" (default), "right", "bottomright", "bottom", "bottomleft", "left", "topleft", "top", or "none".

...

other options directly send to plot()

Examples

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#'data(dcaData)
set.seed(123)
baseline.model <- decision_curve(Cancer~Age + Female + Smokes,
                                data = dcaData,
                                thresholds = seq(0, .4, by = .001),
                                bootstraps = 25) #should use more bootstrap replicates in practice!

#plot the clinical impact
plot_clinical_impact(baseline.model, xlim = c(0, .4),
                    col = c("black", "blue"))

mdbrown/DecisionCurve documentation built on Oct. 19, 2018, 5:27 a.m.