BCEA (version 2.3-1.1)

sim.table: Table of simulations for the health economic model

Description

Using the input in the form of MCMC simulations and after having run the health economic model, produces a summary table of the simulations from the cost-effectiveness analysis

Usage

sim.table(he, wtp = 25000)

Arguments

he

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

wtp

The value of the willingness to pay threshold to be used in the summary table.

Value

Produces the following elements:

Table

A table with the simulations from the economic model

names.cols

A vector of labels to be associated with each column of the table

wtp

The selected value of the willingness to pay

ind.table

The index associated with the selected value of the willingness to pay threshold in the grid used to run the analysis

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

Examples

# NOT RUN {
# 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)
)
#
# Now can save the simulation exercise in an object using sim.table()
st <- sim.table(m, # uses the results of the economic evalaution 
                   #  (a "bcea" object)
        wtp=25000  # selects the particular value for k
)
#
# The table can be explored. For example, checking the 
#  element 'Table' of the object 'st'
# }