As part of the work she’s doing for her PhD, Christina has done some (fairly major, I’d say!) review of the literature about prevalence studies on PCOS $-$ that’s a rather serious, albeit probably fair to say quite under-researched area.
When it came to analysing the data she had collected, naturally I directed her towards doing some Bayesian modelling. In many cases, these are not too complicated $-$ often the outcome is binary and so “fixed” or “random” effect models are fairly simple to structure and run.
Last week, Anna was at the “Autumn Meeting on Latent Gaussian Models” in Trondheim (Norway), where she presented our work on using INLA to estimate the Expected Value of Partial Perfect Information (EVPPI) in health economic evaluation (here’s a working paper).
Good news is she won a prize for best poster! I wonder whether this will make up for the fact the she forgot to acknowledge her EPSRC funding?…
I think I’ve already mentioned this work here and here: after much tribulation, mostly due to the fact that we had to co-ordinate a relatively large number of papers in a single journal issue, we are very close to the publication of our work on the Stepped Wedge cluster-randomised in Trials.
Interestingly, we’re having a launch party (academic-style, of course, ie in the form of a symposium) to celebrate the special issue.
This is an interesting post just advertised at Imperial College London by Marta.
Department of Epidemiology and Biostatistics
School of Public Health
Research Associate in Biostatistics
Salary: £33,410 to £42,380 per annum
Duration: 3 years fixed term
This is an exciting opportunity for a researcher with a PhD in statistics, biostatistics or a related quantitative subject to join the research team at the national MRC-PHE Centre for Environment and Health (http://www.
This Wednesday I’ve been invited to give a talk at the London Machine Learning Meetup $-$ I don’t have a lot of experience of these meetings but I’m told that the audience is typically industry practitioners and some academics, ranging from novices to experienced Machine Learning experts.
I will give my introduction to INLA (although I’ve made a few changes to the slides I presented in Rotterdam and then in Girona a while back).
Slightly later than last year, but, like every year, that time is coming. Yes: Eurovision again. From our point of view, it’s of course being a lot quieter than last year, although the paper is still going strong.
But we’ve had two nice surprises: first we’ve been asked to give a radio interview on Australian radio. Why on earth, do you say? I’m glad you asked! Well, apparently, Australians looove the ESC $-$ just to give you an idea, I think the radio programme is usually focussed on serious elections, but this week they dedicated the whole show to the ESC!
Disclaimer: I’m fully aware of the obvious conflict of interest here, but also I think that this looks really good, so I’ll write about it anyway.
This post is to highlight that Marta’s and Michela’s book on Spatial and Spatio-temporal Bayesian Models with R - INLA is finally out (I think it can be pre-ordered although it will be officially available early in May). I think the book is really good as it describes the underlying theory of INLA and makes the effort of presenting a unified framework, including examples and R code.
[This is a rather long joint post with Roberto Cerina and compounds our paper in the April 2015 issue of Significance]
1. Prelude (kind-of unrelated to what follows). Last week, Marta and I finished watching the last series of House of Cards, the Netflix adaptation of the original BBC series (which I may have liked even more… I’ve not decided yet). The show is based around the US politics and the fictional President Underwood.
The other night, Channel 4 has broadcast this programme. That’s some sort of spin-off from the trial we’re working on at UCL (Valerie Curran is the principal investigator $-$ the whole group is really good and all nice people to work with!). The idea of the TV programme was to have a bunch of celebrities to try different forms of cannabis, to explore the hypothesis that it is the actual composition of cannabis that can make it harmful.
The beginning of the new year has been particularly busy, as I’m working on several interesting projects. On the bright side, some of these are starting to give their fruits and, coincidentally, in the last few days we’ve had a few papers finalised (ie published, accepted for publication or submitted to the arxiv in an advanced status).
The first one has been published in Cost Effectiveness and Resource Allocation (the open access version is here).