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. and Russo, P. (2009). A decision-theoretic framework for the application of cost-effectiveness analysis in regulatory processes. Pharmacoeconomics 27(8), 645-655 doi:10.2165/11310250

Baio, G., Dawid, A. P. (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 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 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 2.4.1 Index]