I have fit a few mixed effects models (particularly longitudinal models) using lme4 in 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).
As usual, hope this question isn't too vague, and thanks in advance for any wisdom!