Hello dear readers!
I have finally come back from my lethargy with a new exciting posts about why the job of health economists, although inevitably involving some statistics, can be very different from what standard statisticians typically do.
I have finally found some time to update the version for my R package missingHE, for which version 1.2.1 is now available on CRAN. I included two main features to the previous version of the package.
I have been kindly invited by the amazing person Chris Sampson to talk about the work I inlcuded in my PhD thesis for his monthly rubric entitled “Thesis Thursday” on the The Academic Health Economists blog.
I have just come back form my first Health Economists' Study Group (HESG) meeting, which this year was held at the University of East Anglia in the beautiful city of Norwich, south east of England, and where I presented some preliminary results from one of my on-going works.
missingHE is a R package aimed at providing some useful tools to analysts in order to handle missing outcome data under a Full Bayesian framework in economic evaluations. The package relies on the R package R2jags to implement Bayesian methods via the statistical software JAGS.
As member of the Health Economics Analysis and Research Methods Team (HEART), together with my colleagues, on Tuesday 2 July I took part in a 1-day introductory short course entitled “Understanding health economics in clinical trials”, which was designed and delivered by the team.
With [Andrea Manca](https://www.york.ac.uk/che/staff/research/andrea-manca/) and [Gianluca Baio](https://www.ucl.ac.uk/statistics/people/gianlucabaio)
With [Alexina Mason](https://www.lshtm.ac.uk/aboutus/people/mason.alexina) and [Gianluca Baio](https://www.ucl.ac.uk/statistics/people/gianlucabaio)