Finally, I got round to find some time to work out all the problems in compiling the BCEA (Bayesian Cost-Effectiveness Analysis) package.

I developed it as part of the work for the book. In a nutshell, what it does is the following: first, you need to specify, code and run a Bayesian model for your health economic problem. This may be based on individual level data, or be a decision-analytical model. Typically, this would be coded in JAGS/BUGS and linked to R using the usual libraries (R2jags/R2WinBUGS, etc). Either way, you end up with simulations from the posterior distributions of some suitable parameters, which you can combine in order to produce suitable variables of cost ($c$) and clinical benefit ($e$).

At this, point, you load the library BCEA and a set of functions becomes available to produce standardised post-processing and economic analysis. I have coded some specific methods to produce plots and summary tables. Most of it is really simple stuff, but some are quite cool (IMHO!).

I’ll produce more examples and try to post them online, here.

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** Gianluca Baio's blog**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...