Here are some random geeky notes that have accumulated over the past few months on my desk.

There are too many articles I have read and have to read to provide a semblance of summary here. Regarding books, my reading list is growing as well. Nevertheless, I’ve been happy with Serious Stats, by Thom Baguley, and Statictics Applied to Clinical Studies, by Cleophas and Zwinderman (bought on http://www.springer.com) as a complement to Statictics Applied to Clinical Trials by the same authors. I also enjoyed Introduction to Psychometric Theory, by Raykov and Marcoulides, since I was looking for a book relying on the Mplus software.

R 3.0 has been released early this year. See also David Smith’s post on Revolutions blog. I’m still using the 2.15.2 version, partly because I have a lot of work in progress and also because I haven’t found any decent way to manage my old packages directory with both versions. I guess at what time I will have to update everything, but I have to wait for a moment.

I just updated to Tex 2013, I bought Stata 13 and I’m playing more and more with Julia. For litterate programming, I will probably be happy with dexy, and also try the Stata filter.

I authored (80%) a new course on the use of statistical software (R and Stata, as far as I was concerned) in medical research. It took me more than 150 hours to produce about 450 pages of slides, exercices and solutions, errata and handouts. What I’ve learned is that it is not writing code or designing a $\LaTeX$ template, or even learning some Stata, that take most time: it is all about finding some good data set!

I was supposed to attend the JSM meeting this year. Unfortunately, I couldn’t make it, so I followed some of the #jsm2013 tweets. I hear about Nat Silver’s talk, and of course I followed the “Data Science” trend in recent months.

The long awaited Applied Predictive Modeling by Max Kuhn and Kjell Johnson is now out. There’s also an R package. I haven’t time to buy and read the book at the moment, but this is just a matter of time.

There was a nice article about Bioconductor in PLoS Comp Bio: Software for Computing and Annotating Genomic Ranges. There was also a great tutorial at UseR! 2013 on the Analysis and Comprehension of High-Throughput Genomic Data.1