evi.plot.mixedAn {BCEA}R Documentation

EVI Plot of the Health Economic Analysis For Mixed Analysis

Description

Compares the optimal scenario to the mixed case in terms of the EVPI.

Usage

## S3 method for class 'mixedAn'
evi.plot(he, y.limits = NULL, pos = c(0, 1), graph = c("base", "ggplot2"), ...)

Arguments

he

An object of class mixedAn, a subclass of bcea, given as output of the call to the function mixedAn.

y.limits

Range of the y-axis for the graph. The default value is NULL, in which case the maximum range between the optimal and the mixed analysis scenarios is considered.

pos

Parameter to set the position of the legend (only relevant for multiple interventions, ie more than 2 interventions being compared). 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.

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".

...

Arguments to be passed to methods, such as graphical parameters (see par).

Value

evi

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

The function produces a graph showing the difference between the ”optimal” version of the EVPI (when only the most cost-effective intervention is included in the market) and the mixed strategy one (when more than one intervention is considered in the market).

Author(s)

Gianluca Baio, Andrea Berardi

References

Baio, G. and Russo, P. (2009). A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes. Pharmacoeconomics 27(8), 645-655 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 Also

bcea, mixedAn

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
)

mixedAn(m) <- NULL      # uses the results of the mixed strategy 
                        #  analysis (a "mixedAn" object)
                        # the vector of market shares can be defined 
                        #  externally. If NULL, then each of the T 
                        #  interventions will have 1/T market share
                        # produces the plots
evi.plot(m)

evi.plot(m, graph="base")

# Or with ggplot2
if (require(ggplot2)) {
   evi.plot(m, graph="ggplot2")
}


[Package BCEA version 2.4.1 Index]