ceplane.plot.bcea {BCEA}R Documentation

Cost-effectiveness Plane Plot


Produces a scatter plot of the cost-effectiveness plane, together with the sustainability area, as a function of the selected willingness to pay threshold.


## S3 method for class 'bcea'
  comparison = NULL,
  wtp = 25000,
  pos = c(0, 1),
  graph = c("base", "ggplot2", "plotly"),

ceplane.plot(he, ...)



A bcea object containing the results of the Bayesian modelling and the economic evaluation.


Selects the comparator, in case of more than two interventions being analysed. Default as NULL plots all the comparisons together. Any subset of the possible comparisons can be selected (e.g., comparison = c(1,3) or comparison = 2).


The value of the willingness to pay parameter. Not used if graph = "base" for multiple comparisons.


Parameter to set the position of the legend; for a single comparison plot, the ICER legend position. Can be given in form of a string (bottom|top)(right|left) for base graphics and bottom|top|left|right for ggplot2. It can be a two-elements vector, which specifies the relative position on the x and y axis respectively, or alternatively it can be in form of a logical variable, with FALSE indicating to use the default position and TRUE to place it on the bottom of the plot. Default value is c(1,1), that is the topright corner inside the plot area.


A string used to select the graphical engine to use for plotting. Should (partial-) match the two options "base" or "ggplot2". Default value is "base".


Additional arguments


In the plotly version, point_colors, ICER_colors and area_color can also be specified as rgba colours using either the toRGB function or a rgba colour string, e.g. 'rgba(1, 1, 1, 1)'.


If graph = "ggplot2" a ggplot object, or if graph = "plotly" a plotly object containing the requested plot. Nothing is returned when graph = "base", the default.

Grey dots show the simulated values for the joint distribution of the effectiveness and cost differentials. The larger red dot shows the ICER and the grey area identifies the sustainability area, i.e. the part of the plan for which the simulated values are below the willingness to pay threshold. The proportion of points in the sustainability area effectively represents the CEAC for a given value of the willingness to pay. If the comparators are more than 2 and no pairwise comparison is specified, all scatterplots are graphed using different colours.


Gianluca Baio, Andrea Berardi


Baio, G., Dawid, A. P. (2011). Probabilistic Sensitivity Analysis in Health Economics. Statistical Methods in Medical Research. doi:10.1177/0962280211419832.

Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall, London.

See Also

bcea, ceplane_plot_graph


## create the bcea object for the smoking cessation example

m <- bcea(e, c, ref = 4, Kmax = 500, interventions = treats)

## produce the base plot
ceplane.plot(m, wtp = 200, graph = "base")

## select only one comparator
ceplane.plot(m, wtp = 200, graph = "base", comparison = 3)

## use ggplot2
if (requireNamespace("ggplot2")) {
   ceplane.plot(m, wtp = 200, pos = "right", ICER_size = 2, graph = "ggplot2")

## plotly
ceplane.plot(m, wtp = 200, graph = "plotly")
ceplane.plot(m, wtp = 200, comparison = 1, graph = "plotly")

[Package BCEA version 2.4.1 Index]