evi.plot.mixedAn {BCEA} | R Documentation |
EVI Plot of the Health Economic Analysis For Mixed Analysis
Description
Compares the optimal scenario to the mixed case in terms of the EVPI.
Usage
## S3 method for class 'mixedAn'
evi.plot(he, y.limits = NULL, pos = c(0, 1), graph = c("base", "ggplot2"), ...)
Arguments
he |
An object of class |
y.limits |
Range of the y-axis for the graph. The default value is
|
pos |
Parameter to set the position of the legend (only relevant for
multiple interventions, ie more than 2 interventions being compared).
Can be given in form
of a string |
graph |
A string used to select the graphical engine to use for
plotting. Should (partial-)match the two options |
... |
Arguments to be passed to methods, such as graphical parameters
(see |
Value
evi |
A ggplot object containing the plot. Returned only if
|
The function produces a graph showing the difference between the ”optimal” version of the EVPI (when only the most cost-effective intervention is included in the market) and the mixed strategy one (when more than one intervention is considered in the market).
Author(s)
Gianluca Baio, Andrea Berardi
References
Baio G, Russo P (2009). “A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes.” Pharmacoeconomics, 27(8), 5–16. ISSN 20356137, doi:10.1007/bf03320526.
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
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
)
mixedAn(m) <- NULL # uses the results of the mixed strategy
# analysis (a "mixedAn" object)
# the vector of market shares can be defined
# externally. If NULL, then each of the T
# interventions will have 1/T market share
# produces the plots
evi.plot(m)
evi.plot(m, graph="base")
# Or with ggplot2
if (require(ggplot2)) {
evi.plot(m, graph="ggplot2")
}