BCEA (version 2.4.1)

ceaf.plot.pairwise: Cost-Effectiveness Acceptability Frontier (CEAF) plot

Description

Produces a plot the Cost-Effectiveness Acceptability Frontier (CEAF) against the willingness to pay threshold.

Usage

# S3 method for pairwise
ceaf.plot(mce, graph = c("base", "ggplot2"), ...)
ceaf.plot(mce, ...)

Value

ceaf

A ggplot object containing the plot. Returned only if graph="ggplot2".

Arguments

mce

The output of the call to the function multi.ce

graph

A string used to select the graphical engine to use for plotting. Should (partial-) match the two options "base" or "ggplot2". Default value is "base".

...

Additional arguments

Author

Gianluca Baio, Andrea Berardi

References

Baio G, Dawid AP. (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, multi.ce

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)
      plot=FALSE            # inhibits graphical output
)

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

# \donttest{
ceaf.plot(mce)              # plots the CEAF 
# }

# \donttest{
ceaf.plot(mce, graph = "g") # uses ggplot2 
# }

# \donttest{
# Use the smoking cessation dataset
data(Smoking)
m <- bcea(e, c, ref = 4, intervention = treats, Kmax = 500, plot = FALSE)
mce <- multi.ce(m)
ceaf.plot(mce)
# }