## Friday, 13 January 2017

### New year resolution

Now that the Christmas break is just a distant memory (Marta would say that I am quite happy with that $-$ she thinks I'm like the Grinch around the Christmas holiday. And she is right), I've given way to my new year's resolution of finally, properly packaging our two R packages that aren't on CRAN yet.

The first one is SWSamp (about which I've already talked here and here) and the second is survHE (which I have also already mentioned here and here).

I've got better at using GitHub and (for survHE) benefited from the help of Peter Konings, who's helped with bits of code and also given me either tips or "forced" me to look into better solutions for the management and potential distribution of the packages, even if they're not directly on the official R repository.

Eventually, this means I've settled for (I think!) a good compromise $-$ I've created a local repository in which I've stored my packages; this in itself doesn't take care of all the dependencies, but it's easy (even for practitioners not too familiar with R) to install the packages and all the others on which they rely to work with very simple commands, for example
install.packages("survHE",
repos=c("http://www.statistica.it/gianluca/R",
"https://cran.rstudio.org",
"https://www.math.ntnu.no/inla/R/stable"),
dependencies=TRUE
)
$-$ this way R uses three repositories (one for survHE, one for all the other dependencies stored on CRAN and one for INLA, which is under its own repository).

We've done some tests and all seems to be working OK, which is great. I've also set in motion a couple of plans for updates to both the packages $-$ I'll post more on this soon! (Incidentally, this also gives way for the development of two more interesting projects: Anthony's work on single arm trial and Andrea's work on missing data for cost-effectiveness analysis. Again, will post more as we have some more output to show for!).

## Friday, 16 December 2016

### Movie stars

Our search for potential alternatives to an academic career, in the face of increasing competition and difficulties in securing grant money has now led Jolene, Marcos and me to seek employment in the show-biz $-$ just in case we fail to recruit enough students for our new MSc in Health Economics & Decision Science...

## Thursday, 15 December 2016

### PhD opportunity!

Applications are invited for a PhD funding opportunity to conduct research in a branch of probability or statistics based in the UCL Department of Statistical Science, commencing in September 2017. This funding is provided by the Engineering and Physical Sciences Research Council (EPSRC).

The requirement for admission to the MPhil/PhD in Statistical Science is a 1st class or high upper 2nd class Bachelor’s degree, or a Master’s degree with merit or distinction, in Mathematics, Statistics, Computer Science, or a related quantitative discipline. Overseas qualifications of an equivalent standard are also acceptable. Further details can be found on the Departmental website. Applicants are expected to prepare an outline proposal of their work. We have some interesting project in our pipeline, including extensions of our work on survHE, or related to evidence synthesis and network meta-analysis, as well as the use of observational data for health economic evaluation.

The studentship will be four years in duration and covers tuition fees at the UK/EU rate plus a stipend of £16,785 per annum for eligible UK residents. EU nationals who have not been ordinarily resident in the UK for 3 years prior to the start of the studentship may still qualify for a fees only award. The studentship may only be awarded to applicants liable to pay tuition fees at the UK/EU rate (i.e. it cannot be used to part-cover overseas tuition fees).

Further information, including details of how to apply, is available here.

### Bayes 2017

We've just opened the call for abstract for the next edition of the Bayes Workshop $-$ this time we're going to Spain and to be more precise to Albacete.

The format is the same as in the past few years $-$ you can send your abstract (including title, authors and not exceeding 300 words) at info@bayes-pharma.org. We're pretty much open to many research areas, as long as they involve Bayesian statistics (I feel I have to say this $-$ in the past we had invariably at least a couple of abstracts that had absolutely nothing to do with a Bayesian analysis!...).

## Friday, 9 December 2016

### Nomen omen

After resisting this for way too long, I've finally decided it was time to release more widely a couple of the R packages I've been working on $-$ I've put them on GitHub, hence the mug...

In both cases, while I think the packages do work nicely, I am still not sure they are ready for an official release on CRAN $-$ effectively, this is mainly due to the fact that documentation may not be super yet, or, more importantly, that I'm still updating some of the basic functions a bit too often.

I knew GitHub was the way to go, but like a grumpy old man I've so far resisted the idea of learning how to manage it. However, because people I wanted to test survHE were struggling to install it (because of its complicated system of dependencies $-$ I'll say a bit more later), I thought this will be a very good alternative.

So, I've created Git repositories for survHE and SWSamp (I've talked about this here) and the packages can be installed by using devtools in R $-$ I think something like this:

install.package("devtools")
install_github("giabaio/survHE")
install_github("giabaio/SWSamp")

I think devtools may fail to install all the dependencies' dependencies under Windows (as far as I understand this is a bug that will be fixed soon) $-$ so the workaround is to use the development version of devtools. Or indulge R and install the missing packages that it requires.

## Friday, 2 December 2016

### Good stuff around

Lately, I've been publicising quite heavily our Summer school and new MSc, but of course, we're not the only one to plan for interesting things worth mentioning $-$ well, of course this is highly subjective... But then again, this blog is (mainly) about Bayesian stuff, so what's the problem with that?...

Anyway, I know of at least a couple of very interesting events:

1) Petros' course on Decision modeling using R, in Toronto, in February 2017. Last year he kindly invited me and I gave some sort of BCEA tutorial, which I really enjoyed.

2) Emmanuel's summer school on advanced Bayesian methods, in Leuven, in September 2017 (I think their website is not live yet, but info will be available at the i-Biostat website). I think they'll do a three-day course on non-parametric Bayesian methods and then a two-day course on Bayesian clinical trials.

## Wednesday, 23 November 2016

### Come & play with us!

We're starting to build up the promotional material for our new MSc in Health Economics and Decision Science. Here's the first of a few videos we've filmed!

## Monday, 21 November 2016

### Summer School: Bayesian Methods in Health Economics

We're finally ready to advertise our new Summer School on Bayesian Methods in Health Economics, in Florence, 12-16 June 2017! This is basically combining the two short courses that we've run in the past few years $-$ the first one on Bayesian modelling for cost-effectiveness analysis using R, BUGS and BCEA, which I have done with Chris and Richard; the second one is the short course on Value of Information we did last summer with Mark, Nicky and Anna.

The five of us have decided we should take these to the next level and so have arranged to merge the two programmes and enjoy a well in late Spring next year in Florence. Now, you may think I'm massively biased (because Florence is my home town) $-$ and partly I am $-$ but the place we chose and managed to book is really awesome.

The programme of the lectures in the summer school is the following:
1. Introduction to health economic evaluations
2. Introduction to Bayesian inference
3. Introduction to Markov Chain Monte Carlo in BUGS
4. Cost and cost-utility data
5. Statistical cost-effectiveness analysis
6. Probabilistic sensitivity analysis (PSA)
8. Model error and structural uncertainty
9. Evidence synthesis (1) - hierarchical models
10. Evidence synthesis (2) - network meta-analysis
11. Markov models
12. Introduction to the theory of the value of information
13. Expected value of partial information (1) - theory & algebraic tricks
14. Expected value of partial information (2) - nested Monte Carlo
15. Expected value of partial information (3) - generalised additive models & GP regression
16. Expected value of partial information (4) - GP regression via integrated nested Laplace approximation
17. Expected value of sample information (1) - conjugated analysis
18. Expected value of sample information (2) - regression-based methods
All the lectures will be followed by computer practicals in which we'll show how use R and BUGS to perform cost-effectiveness analyses and post-process the model outcomes, mainly using BCEA.

We have planned for a maximum of 30 participants $-$ in previous editions, we've had most people coming from the UK. This time we're hoping for an "inverse-Brexit" to branch out more widely to other European countries. Participants will all be able to stay at the Centro Study (there are 10 single and 10 double rooms available, so book quickly if you definitely want a single!).

The registration fee also includes a copy of the three main books used as reference in the course: BMHEThe BUGS Book and Evidence Synthesis for Decision Making in Healthcare. We'll also prepare a full set of handouts and computer code (R and BUGS) that we use in the practicals.

Registration is already available (from now to the end of April) on the UCL Store. We offer a lower rate for students!