BCEA (version 2.3-1.1)

Smoking: Data set for the Bayesian model for the cost-effectiveness of smoking cessation interventions

Description

This data set contains the results of the Bayesian analysis used to model the clinical output and the costs associated with the health economic evaluation of four different smoking cessation interventions.

Usage

data(Smoking)

Format

A data list including the variables needed for the smoking cessation cost-effectiveness analysis. The variables are as follows:

c

a matrix of 500 simulations from the posterior distribution of the overall costs associated with the four strategies

data

a dataset containing the characteristics of the smokers in the UK population

e

a matrix of 500 simulations from the posterior distribution of the clinical benefits associated with the four strategies

life.years

a matrix of 500 simulations from the posterior distribution of the life years gained with each strategy

pi

a matrix of 500 simulations from the posterior distribution of the event of smoking cessation with each strategy

smoking

a data frame containing the inputs needed for the network meta-analysis model. The data.frame object contains: nobs: the record ID number, s: the study ID number, i: the intervention ID number, r_i: the number of patients who quit smoking, n_i: the total number of patients for the row-specific arm and b_i: the reference intervention for each study

smoking_output

a rjags object obtained by running the network meta-analysis model based on the data contained in the smoking object

smoking_mat

a matrix obtained by running the network meta-analysis model based on the data contained in the smoking object

treats

a vector of labels associated with the four strategies

References

Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall, London

Examples

# NOT RUN {
data(Smoking)

# }
# NOT RUN {
m=bcea(e,c,ref=4,interventions=treats,Kmax=500)
# }