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Getting more into mixed models, I’ve been playing around with both nlme::lme and lme4::lmer. http://tolstoy.newcastle.edu.au/R/e2/help/06/10/3345.html was quite a good post at explaining the differences, which from what I gather is largely performance based when using crossed or partially crossed ... [Read more...]

I’m highly excited to announce that influence.ME is now available. Influence.ME is a new software package for R, providing statistical tools for detecting influential data in mixed models. It has been developed by Rense Nieuwenhuis, Ben Pelzer, a... [Read more...]

The organizing committee of the useR! 2009 conference just informed me, that my submission for presenting my extension package influence.ME, has been accepted! Influence.ME is a new R package that I’m currently developing, with the indispensable ... [Read more...]

There are various ways of getting your output from R to your publication draft. Most of them are highly efficient, but unfortunately I couldn’t find a function that combines the output from several (lmer) models and presents it in a single table.... [Read more...]