# EVI Plot of the Health Economic Analysis For Mixed Analysis

Source:`R/evi.plot.mixedAn.R`

`evi.plot.mixedAn.Rd`

Compares the optimal scenario to the mixed case in terms of the EVPI.

## Arguments

- he
An object of class

`mixedAn`

, a subclass of`bcea`

, given as output of the call to the function`mixedAn()`

.- y.limits
Range of the y-axis for the graph. The default value is

`NULL`

, in which case the maximum range between the optimal and the mixed analysis scenarios is considered.- 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

`(bottom|top)(right|left)`

for base graphics and`bottom|top|left|right`

for ggplot2. It can be a two-elements vector, which specifies the relative position on the x and y axis respectively, or alternatively it can be in form of a logical variable, with`FALSE`

indicating to use the default position and`TRUE`

to place it on the bottom of the plot.- 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"`

.- ...
Arguments to be passed to methods, such as graphical parameters (see

`par()`

).

## Value

- evi
A ggplot object containing the plot. Returned only if

`graph="ggplot2"`

.

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).

## 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.

## 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")
}
```