# Finish line (nearly)

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

We are very close to the finish line $-$ that’s being able to finally submit the BCEA book to the editor (Springer).**Gianluca Baio's blog**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

This has been a rather long journey, but I think the current version (I dread using the word “final” just yet…) is very good, I think. We’ve managed to respond to all the reviewers’ comments, which to be fair were rather helpful and so this should have improved the book.

Anna and Andrea have done very good work and I didn’t even have to play the bad, control freak guy to have them prepare their bits quickly $-$ in fact, I think at several points, I’ve been late in doing mine…

Here’s the (somewhat simplified to only sections and sub-sections) table of content:

- Bayesian analysis in health economics
- Introduction
- Bayesian inference and computation
- Basics of health economic evaluation
- Doing Bayesian analysis and health economic evaluation in R
- Case studies
- Introduction
- Preliminiaries: computer configuration
- Vaccine
- Smoking cessation
- BCEA – a R package for Bayesian Cost-Effectiveness Analysis
- Introduction
- Economic analysis: the bcea function
- Basic health economic evaluation: the summary command
- Cost-effectiveness plane
- Expected Incremental Benefit
- Contour plots
- Health economic evaluation for multiple comparators and the efficiency frontier
- Probabilistic Sensitivity Analysis using BCEA
- Introduction
- Probabilistic sensitivity analysis for parameter uncertainty
- Value of information analysis
- PSA applied to model assumptions and structural uncertainty
- BCEAweb: a user-friendly web-app to use BCEA
- Introduction
- BCEAweb: a user-friendly web-app to use BCEA

Throughout the book we use a couple of examples of full Bayesian modelling and the relevant R code to run the analysis and then use BCEA to do the “final part” of the cost-effectiveness analysis.

We’ve tried to avoid unnecessary complications in terms of maths, but we do include explanations and formulae when necessary. It was difficult to strike a balance for the audience $-$ especially as it was complicated to define what the audience would be… I think we’re aiming for statisticians who want to get to work in health economic evaluations and health economists who need to use more principled statistical methods and software (I couldn’t resist in several points moving my tanks to invade

*Excelland*and replace the local government with*R officials.*..).The final chapter also present and discuss the use of graphical front-ends to R-based models (eg as in SAVI) $-$ we have a BCEA front-end too. I think these may be helpful, but they can’t replace making people in the “industry” more familiar with full modelling and away from spreadsheets and stuff (these work when the models are simple. But the models that are required are not very often

*that*simple…).We also present lots of work on value of information (including our recent work), which is also linked to our short course. May be it’s time to link BMHE and this to do a long course… (there’s more on this to come!)

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 about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.