multi.ce: Cost-effectiveness Analysis With Multiple Comparison

In BCEA: Bayesian Cost Effectiveness Analysis

Cost-effectiveness Analysis With Multiple Comparison

Description

Computes and plots the probability that each of the n_int interventions being analysed is the most cost-effective and the cost-effectiveness acceptability frontier.

Usage

## S3 method for class 'bcea'
multi.ce(he)

Arguments

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

Value

Original bcea object (list) of class "pairwise" with additional:

p_best_interv	A matrix including the probability that each intervention is the most cost-effective for all values of the willingness to pay parameter
ceaf	A vector containing the cost-effectiveness acceptability frontier

Author(s)

Gianluca Baio

See Also

bcea(), ceaf.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=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)
      plot=FALSE            # inhibits graphical output
)

mce <- multi.ce(m)          # uses the results of the economic analysis

ceac.plot(mce)
ceaf.plot(mce)

BCEA documentation built on June 22, 2024, 11:08 a.m.