I have fit a few mixed effects models (particularly longitudinal models) using
R but would like to really master the models and the code that goes with them.
However, before diving in with both feet (and buying some books) I want to be sure that I am learning the right library. I have used
lme4 up to now because I just found it easier than
nlme, but if
nlme is better for my purposes then I feel I should use that.
I'm sure neither is "better" in a simplistic way, but I would value some opinions or thoughts. My main criteria are:
- easy to use (I'm a psychologist by training, and not particularly versed in statistics or coding, but I'm learning)
- good features for fitting longitudinal data (if there is a difference here- but this is what I mainly use them for)
- good (easy to interpret) graphical summaries, again not sure if there is a difference here but I often produce graphs for people even less technical than I, so nice clear plots are always good (I'm very fond of the xyplot function in lattice() for this reason).