mce.plot {BCEA}  R Documentation 
Plots the probability that each of the n_int interventions being analysed is the most costeffective.
mce.plot(mce,pos=c(1,0.5),graph=c("base","ggplot2"),...)
mce 
The output of the call to the function 
pos 
Parameter to set the position of the legend. Can be given in form of a string

graph 
A string used to select the graphical engine to use for plotting. Should
(partial)match the two options 
... 
Optional arguments. For example, it is possible to specify the colours to be used
in the plot. This is done in a vector 
mceplot 
A ggplot object containing the plot. Returned only if 
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 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 costeffective graph="base") # using base graphics # if(require(ggplot2)){ mce.plot(mce, # the same plot graph="ggplot2") # using ggplot2 instead }