mixedAn<- {BCEA} | R Documentation |

Runs the cost-effectiveness analysis, but accounts for the fact that more than one intervention is present on the market.

```
mixedAn(he) <- value
```

`he` |
A |

`value` |
A vector of market shares associated with the interventions. Its size is the same as the number of possible comparators. By default, assumes uniform distribution for each intervention. |

Creates an object in the class `mixedAn`

, a subclass of `bcea`

which contains the results of the health economic evaluation in the mixed analysis case:

`Ubar` |
An array with the simulations of the ”known-distribution” mixed utilities, for each value of the discrete grid approximation of the willingness to pay parameter |

`OL.star` |
An array with the simulations of the distribution of the Opportunity Loss for the mixed strategy, for each value of the discrete grid approximation of the willingness to pay parameter |

`evi.star` |
The Expected Value of Information for the mixed strategy, for each value of the discrete grid approximation of the willingness to pay parameter |

`mkt.shares` |
The vector of market shares associated with each available intervention |

Gianluca Baio

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 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)
```

[Package *BCEA* version 2.4.4 Index]