CEriskav: Cost-effectiveness analysis including a parameter of risk aversion

Description

Extends the standard cost-effectiveness analysis to modify the utility function so that risk aversion of the decision maker is accounted for explicitly

Usage

CEriskav(he, r = NULL, comparison = 1)
## S3 method for class 'fn':
CEriskav(he, r = NULL, comparison = 1)
## S3 method for class 'default':
CEriskav(he, r = NULL, comparison = 1)

Arguments

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

A vector of values for the risk aversion parameter. If NULL, default values are assigned by R. The first (smallest) value (r -> 0) produces the standard analysis with no risk aversion

comparison

In case of more than 2 interventions being analysed, selects which plot should be made. By default chooses the first possible as the comparator

Value

An object of the class "CEriskav" containing the following elements
UrAn array containing the simulated values for all the ''known-distribution'' utilities for all interventions, all the values of the willingness to pay parameter and for all the possible values of r
UrstarAn array containing the simulated values for the maximum ''known-distribution'' expected utility for all the values of the willingness to pay parameter and for all the possible values of r
IBrAn array containing the simulated values for the distribution of the Incremental Benefit for all the values of the willingness to pay and for all the possible values of r
eibrAn array containing the Expected Incremental Benefit for each value of the willingness to pay parameter and for all the possible values of r
virAn array containing all the simulations for the Value of Information for each value of the willingness to pay parameter and for all the possible values of r
evirAn array containing the Expected Value of Information for each value of the willingness to pay parameter and for all the possible values of r
RThe number of possible values for the parameter of risk aversion, r
rThe vector containing all the possible values for the parameter of risk aversion, r

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

Examples

Run this code

# 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)
)
#
# Define the vector of values for the risk aversion parameter, r, eg:
r <- c(0.000000000001,0.005,0.020,0.035) 
#
# Run the cost-effectiveness analysis accounting for risk aversion
cr <- CEriskav(m,     # uses the results of the economic evalaution 
                      #  (a "bcea" object)
        r=r,          # defines the vector of values for the risk 
                      #  aversion parameter
        comparison=1  # if more than 2 interventions, selects the 
                      #  pairwise comparison 
)