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.
A data list including the variables needed for the smoking cessation cost-effectiveness analysis. The variables are as follows:
a matrix of 500 simulations from the posterior distribution of the overall costs associated with the four strategies
a dataset containing the characteristics of the smokers in the UK population
a matrix of 500 simulations from the posterior distribution of the clinical benefits associated with the four strategies
a matrix of 500 simulations from the posterior distribution of the life years gained with each strategy
a matrix of 500 simulations from the posterior distribution of the event of smoking cessation with each strategy
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
a matrix obtained by running the network
meta-analysis model based on the data contained in the smoking object
a vector of labels associated with the four strategies
Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall, London