# Summary Methods For Objects in the Class `mixedAn`

(Mixed Analysis)

Source: `R/summary.mixedAn.R`

`summary.mixedAn.Rd`

Prints a summary table for the results of the mixed analysis for the economic evaluation of a given model.

## Usage

```
# S3 method for mixedAn
summary(object, wtp = 25000, ...)
```

## Arguments

- object
An object of the class

`mixedAn`

, which is the results of the function`mixedAn()`

, generating the economic evaluation of a set of interventions, considering given market shares for each option.- wtp
The value of the willingness to pay chosen to present the analysis.

- ...
Additional arguments affecting the summary produced.

## Value

Produces a table with summary information on the loss in expected value of information generated by the inclusion of non cost-effective interventions 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)
)
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
# Prints a summary of the results
summary(m, # uses the results of the mixed strategy analysis
wtp=25000) # (a "mixedAn" object)
#>
#> Analysis of mixed strategy for willingness to pay parameter k = 25000
#>
#> Reference intervention: Vaccination (50.00% market share)
#> Comparator intervention: Status Quo (50.00% market share)
#>
#> Loss in the expected value of information = 0.61
#>
# selects the relevant willingness to pay
# (default: 25,000)
```