29-30 June 2020, University College London Training event (29 June): Torrington (1-19) 113 - Public Cluster, 1-19 in Torrington Place (https://goo.gl/maps/RtR3Ypug2Dq), University College London, United Kingdom Main workshop (30 June): Room G12, 1-19 in Torrington Place (https://goo.gl/maps/RtR3Ypug2Dq), University College London, United Kingdom. Background and objectives It is our pleasure to announce a workshop and training event on the use of R for trial and model-based cost-effectiveness analysis (CEA).
Boby Mihaylova has two exciting posts available at the Health Economics Research Centre at the University of Oxford. In particular, she is looking for two R-minded researchers/analysts to develop work on disease modelling/cost-effectiveness using large individual-patients databases. In fact, I think it’s really good that they are explicitly including knowledge of R as part of the job specification — and they even ask R code as part of the application!).
Our editorial on using R in HTA (I talked about it here) has finally been published in Value in Health.
This is nice in the (rather long, I know…) build up to our workshop. And speaking of, we’ve already received quite a few abstracts for contributed talks — this below is the “official” advert we’ve circulated.
This is a reminder that the deadline for abstract submission to the Workshop on R for trial and model-based cost-effectiveness analysis (CEA) is 15th May.
As part of our R for HTA workshop, we have also prepared a kind-of-hackathon, which we are now releasing to the general public (I think “general public” is a bit pretentious, but this afternoon, I’m in the right mood for it, I think…).
Participation is actually open to all (and we’ll advertise more widely on relevant mailing lists) but we expect contributions particularly from anyone attending the workshop, which will be held at UCL on 9th July.
I’ve just updated the GitHub’s version of BCEA. Andrea has done, as usual, some very nice work – this time he’s mainly focussed on the graphical engine underlying the graphs produced by BCEA to post-process the outcome of the economic model.
The main changes are the following:
Added plot rendering via plotly (using the command graph=“plotly”) to each of the functions: ceplane.plot eib.
As I posted recently, I’m involved in a couple of events, later this summer: our annual Summer School and the new(er) tradition of the R for HTA workshop.
I have to say that I’m very happy about how things are proceeding for both of them. The summer school has been first advertise a few months back (I’ve posted on the blog, but we’ve also tried to reach other relevant mailing lists and groups, such as the HTA agencies in the EUnetHTA Network).
Summer is really going to be busy, this year. But in a good way…
In June, I’ll be at our annual summer school in Florence. This year, we have a slight change in the line-up — Nicky has decided to take a break from teaching with us, which is a shame, (although I understand, as she’s so busy). On the other hand, I’m happy that Howard is joining us as part of the “faculty”.
As I’m waiting to catch my flight back from Stockholm (where I had a rather interesting meeting discussing Bayesian network meta-analysis. But I digress…), I am browsing the news — mainly just to keep myself awake. And I find this interesting piece of news in The Guardian. It is the story that data released by the Nigerian Electoral Commission (INEC) and then analysed by the journalists show that
for each of the country’s 36 states and its capital shows that INEC has increased the number of new registered voters by almost exactly the same percentage across all states.
9 July 2019, University College London Training event (8 July): Torrington (1-19) B07 - Teal Room in Torrington Place, 1-19 (https://goo.gl/maps/RtR3Ypug2Dq), University College London, United Kingdom Main workshop (9 July): Anatomy G29 J Z Young Lecture Theatre, UCL Medical Sciences and Anatomy (https://goo.gl/maps/biryoFc9CiL2), University College London, United Kingdom. Background and objectives It is our pleasure to announce a workshop and training event on the use of R for trial and model-based cost-effectiveness analysis (CEA).
This is an annual event organised jointly by a “consortium” of academics and modellers working in health economic evaluation. Academic institutions involved include UCL, the University of Bristol, the University of York, the University of Oxford, Bangor University.
Cost-effectiveness analysis (CEA) and, more generally, health technology assessment (HTA), is often performed using Excel. Despite its (perceived) ease of use, Excel incurs the disadvantages of slow computational speed and, contrary to health economics folk theorem, a lack of transparency.