plot.mixedAn {BCEA}  R Documentation 
Compares the optimal scenario to the mixed case in terms of the EVPI
## S3 method for class 'mixedAn' plot(x, y.limits = NULL, pos=c(0,1), graph=c("base","ggplot2"), ...)
x 
An object of class 
y.limits 
Range of the yaxis for the graph. The default value is 
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 
... 
Arguments to be passed to methods, such as graphical parameters (see 
evi 
A ggplot object containing the plot. Returned only if 
The function produces a graph showing the difference between the ”optimal” version of the EVPI (when only the most costeffective intervention is included in the market) and the mixed strategy one (when more than one intervention is considered in the market).
Gianluca Baio, Andrea Berardi
Baio, G. and Russo, P. (2009).A decisiontheoretic framework for the application of costeffectiveness analysis in regulatory processes. Pharmacoeconomics 27(8), 645655 doi:10.2165/11310250
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 ) # ma < mixedAn(m, # uses the results of the mixed strategy # analysis (a "mixedAn" object) mkt.shares=NULL # the vector of market shares can be defined # externally. If NULL, then each of the T # interventions will have 1/T market share ) # # Can also plot the summary graph plot(ma,graph="base") # # Or with ggplot2 if(require(ggplot2)){ plot(ma,graph="ggplot2") }