BCEA (version 1.0)

eib.plot: Expected Incremental Benefit plot

Description

Plots the Expected Incremental Benefit as a function of the willingness to pay

Usage

eib.plot(he)

Arguments

he

A "bcea" object containing the results of the Bayesian modelling and the economic evaluation

Value

• The function produces a plot of the Expected Incremental Benefit as a function of the discrete grid approximation of the willingness to pay parameter. The break even point (ie the point in which the EIB=0, ie when the optimal decision changes from one intervention to another) is also showed. The value k* is the discrete grid approximation of the ICER

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, ib.plot, ceplane.plot

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)
)
#
# Plots the Expected Incremental Benefit for the "bcea" object m
eib.plot(m)