mixedAn {BCEA}  R Documentation 
Runs the costeffectiveness analysis, but accounts for the fact that more than one intervention is present on the market
mixedAn(he, mkt.shares = NULL, plot = FALSE) ## Default S3 method: mixedAn(he, mkt.shares = NULL, plot = FALSE)
he 
A 
mkt.shares 
A vector of market shares associated with the interventions. Its size is the same as the number of possible comparators. By default, assumes uniform distribution for each intervention. 
plot 
Logical value indicating whether the function should produce graphical output, via

Creates an object in the class mixedAn
which contains the results of the health
economic evaluation in the mixed analysis case
Ubar 
An array with the simulations of the ”knowndistribution” mixed utilities, for each value of the discrete grid approximation of the willingness to pay parameter 
OL.star 
An array with the simulations of the distribution of the Opportunity Loss for the mixed strategy, for each value of the discrete grid approximation of the willingness to pay parameter 
evi.star 
The Expected Value of Information for the mixed strategy, for each value of the discrete grid approximation of the willingness to pay parameter 
k 
The discrete grid approximation of the willingness to pay parameter used for the mixed strategy analysis 
Kmax 
The maximum value of the discrete grid approximation for the willingness to pay parameter 
step 
The step used to form the grid approximation to the willingness to pay 
ref 
The numeric index associated with the intervention used as reference in the analysis 
comp 
The numeric index(es) associated with the intervention(s) used as comparator(s) in the analysis 
mkt.shares 
The vector of market shares associated with each available intervention 
n.comparisons 
The total number of pairwise comparisons available 
interventions 
A vector of labels for all the interventions considered 
evi 
The vector of values for the ”optimal” Expected Value of Information, as a function of the willingness to pay 
The function can also produce 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
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 plot=TRUE # produces the plots )