BCEA (version 2.3-1.1)

Vaccine: Data set for the Bayesian model for the cost-effectiveness of influenza vaccination

Description

This data set contains the results of the Bayesian analysis used to model the clinical output and the costs associated with an influenza vaccination.

Usage

data(Vaccine)

Format

A data list including the variables needed for the influenza vaccination. The variables are as follows:

c

a matrix of simulations from the posterior distribution of the overall costs associated with the two treatments

cost.GP

a matrix of simulations from the posterior distribution of the costs for GP visits associated with the two treatments

cost.hosp

a matrix of simulations from the posterior distribution of the costs for hospitalisations associated with the two treatments

cost.otc

a matrix of simulations from the posterior distribution of the costs for over-the-counter medications associated with the two treatments

cost.time.off

a matrix of simulations from the posterior distribution of the costs for time off work associated with the two treatments

cost.time.vac

a matrix of simulations from the posterior distribution of the costs for time needed to get the vaccination associated with the two treatments

cost.travel

a matrix of simulations from the posterior distribution of the costs for travel to get vaccination associated with the two treatments

cost.trt1

a matrix of simulations from the posterior distribution of the overall costs for first line of treatment associated with the two interventions

cost.trt2

a matrix of simulations from the posterior distribution of the overall costs for second line of treatment associated with the two interventions

cost.vac

a matrix of simulations from the posterior distribution of the costs for vaccination

c.pts

a matrix of simulations from the posterior distribution of the clinical benefits associated with the two treatments

e

a matrix of simulations from the posterior distribution of the clinical benefits associated with the two treatments

e.pts

a matrix of simulations from the posterior distribution of the clinical benefits associated with the two treatments

N

the number of subjects in the reference population

N.outcomes

the number of clinical outcomes analysed

N.resources

the number of health-care resources under study

QALYs.adv

a vector from the posterior distribution of the QALYs associated with advert events

QALYs.death

a vector from the posterior distribution of the QALYs associated with death

QALYs.hosp

a vector from the posterior distribution of the QALYs associated with hospitalisation

QALYs.inf

a vector from the posterior distribution of the QALYs associated with influenza infection

QALYs.pne

a vector from the posterior distribution of the QALYs associated with penumonia

treats

a vector of labels associated with the two treatments

vaccine

a rjags object containing the simulations for the parameters used in the original model

vaccine_mat

a matrix containing the simulations for the parameters used in the original model

References

Baio, G., Dawid, A. P. (2011). Probabilistic Sensitivity Analysis in Health Economics. Statistical Methods in Medical Research doi:10.1177/0962280211419832.

Examples

# NOT RUN {
data(Vaccine)

# }
# NOT RUN {
m=bcea(e,c,ref=1,interventions=treats)
# }