plot_clinical_impact: Plot the clinical impact curve from a DecisionCurve object. In DecisionCurve: Calculate and Plot Decision Curves

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

 1 2 3 4 5 6 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

 1 2 3 4 5 6 7 8 9 10 #'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"))

DecisionCurve documentation built on July 15, 2017, 1:01 a.m.