A bunch of papers

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). I’ve been involved in this paper with colleagues at UCL. The paper is an economic evaluation of an interesting and rather complex community trial conducted in Malawi, a country with particularly low life expectancy and high rates of HIV. In the paper, we did most of the economic analysis using BCEA.

The second one has also just been published in Pharmacoeconomics and is an “educational” piece that I co-wrote with several colleagues at UCL. I think this too was an interesting piece of work, in that we tried to focus on several statistical issues that are of concern in many economic evaluations $-$ the idea that health economics is in many ways inextricably related to statistics is of course one of my _pieces de resistance _(I guess I’ve showed off enough complicated words for a post…).

The third one is the RDD paper, which we had submitted ages ago to Statistics in Medicine. I had a brilliant experience with the Structural Zeros paper $-$ I submitted the first version in August and the paper was online by November. This time around, we had to struggle a lot more (apparently they couldn’t find suitable reviewers, then the reviews arrived but took some time, then we responded to the comments $-$ long story short, it’s been almost one year). Anyway, finally, they seem to have accepted the paper (which we previously arxived a similar version); we need a couple more changes and we should be good to go (I hope I’m not jinxing it!).

Finally, the last one is part of one of my PhD students (technically, I’m only second-supervising him). In fact, the paper develops a nice Bayesian non-parametric model to perform clustering and model selection simultaneously. We developed the model to handle a real clinical dataset, which records data on patients with lower urinary tract infection. I only knew little about Bayesian NP before working on this, so it was a nice opportunity. William has done a very good job in sorting this out and we have also submitted the full paper to _Statistics in Medicine _(hopefully, we’ll get a quick turnaround!).

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