First, a statistical model is constructed and fitted to estimate relevant population parameters (the red rounded box). These are then fed to an economic model (the grey box), which combines them to obtain suitable summaries that quantify the incremental population average for clinical benefits (e.g. QALYs) and costs (e.g. £). These are the fundamental quantities used to make the decision analysis (orange box). And this is the process that BCEA and

- A spreadsheet, in .csv format, e.g. a file produced by MS Excel. Download an example here;
- Files in 'coda' format. These are typically saved as the results of running MCMC software such as OpenBUGS. Coda produces an 'index' file and one output file for each Markov Chain used in the analysis. Download a .zip file with an example here.
- A R object, available in the current session. This can be a spreadsheet imported in R (e.g. using the
`read.csv`

function). Or the output of a full Bayesian analysis (e.g. performed using OpenBUGS). The resulting data will be pre-processed to eliminate linear dependency across the variables.

An example of such a file can be obtained here. These simulations are uploaded in the 'Economic analysis' tab, where the user can specify some options. Clicking the button

`Run the analysis`

in the 'Economic analysis tab' will run BCEA in the background and create all the relevant economic summaries, including a detailed
Probabilistic Sensitivity Analysis. The tab 'Value of information' also automatically computes the
Expected Value of Perfect Information and allows the user to run an analysis of the Expected Value of Copyright: Gianluca Baio, Polina Hadjipanayiotou, Andrea Berardi, Anna Heath

NB check visually if the Bayesian model has converged

Check visually the value of the Gelman-Rubin statistic. Values below 1.1 are considered to suggest convergence for a given parameter