BCEA (version 2.2-2)

mce.plot: Plots the probability that each intervention is the most cost-effective

Description

Plots the probability that each of the n_int interventions being analysed is the most cost-effective.

Usage

mce.plot(mce,pos=c(1,0.5),graph=c("base","ggplot2"))

Arguments

mce

The output of the call to the function multi.ce.

pos

Parameter to set the position of the legend. 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 posit

graph

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".

Value

• mceplot
  A ggplot object containing the plot. Returned only if graph="ggplot2".

References

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

Examples

# See Baio G., Dawid A.P. (2011) for a detailed description of the 
# Bayesian model and economic problem
#
# Load the processed results of the MCMC simulation model
data(Vaccine)
# 
# Runs the health economic evaluation using BCEA
m <- bcea(e=e,c=c,          # defines the variables of 
                            #  effectiveness and cost
      ref=2,                # selects the 2nd row of (e,c) 
                            #  as containing the reference intervention
      interventions=treats, # defines the labels to be associated 
                            #  with each intervention
      Kmax=50000,           # maximum value possible for the willingness 
                            #  to pay threshold; implies that k is chosen 
                            #  in a grid from the interval (0,Kmax)
      plot=FALSE            # inhibits graphical output
)
#
mce <- multi.ce(m)          # uses the results of the economic analysis 
#
mce.plot(mce,               # plots the probability of being most cost-effective
      graph="base")         #  using base graphics
#
if(require(ggplot2)){
mce.plot(mce,               # the same plot
      graph="ggplot2")      #  using ggplot2 instead
}