CEriskav_assign {BCEA}

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 explicitly accounted for.

Default vector of risk aversion parameters: 1e-11, 2.5e-6, 5e-6

Usage

CEriskav(he) <- value

## S3 replacement method for class 'bcea'
CEriskav(he) <- value

## Default S3 replacement method:
CEriskav(he) <- value

Arguments

he

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

value

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.

Value

An object of the class CEriskav containing the following elements:

Ur

An 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

Urstar

An 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

IBr

An 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

eibr

An array containing the Expected Incremental Benefit for each value of the willingness to pay parameter and for all the possible values of r

vir

An 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

evir

An array containing the Expected Value of Information for each value of the willingness to pay parameter and for all the possible values of r

R

The number of possible values for the parameter of risk aversion r

r

The vector containing all the possible values for the parameter of risk aversion r

Author(s)

Gianluca Baio

References

Baio G, Dawid aP (2011). “Probabilistic sensitivity analysis in health economics.” Stat. Methods Med. Res., 1–20. ISSN 1477-0334, doi:10.1177/0962280211419832, https://pubmed.ncbi.nlm.nih.gov/21930515/.

Baio G (2013). Bayesian Methods in Health Economics. CRC.

See Also

bcea()

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=eff,c=cost,     # 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(1e-10, 0.005, 0.020, 0.035) 

# Run the cost-effectiveness analysis accounting for risk aversion

# uses the results of the economic evaluation 
# if more than 2 interventions, selects the 
#  pairwise comparison

CEriskav(m) <- r