Douglas Bates <[EMAIL PROTECTED]> writes: > > (Sorry, I'm a little rusty on the syntax, but just follow the example > > in P&B) > > > > AFAIR, it also works with random=list(a=~1,one=~b) and vice versa. > > Not sure about that.
Sorry. It's certainly not correct as written. It has to be something like list(a=1,one=pdIdent(form=~b-1)) otherwise you get a general symmetric covariance for the effect of b. > > (The model is the same but you get different DF calculations, none of > > which are correct in the completely balanced case...) > > I realize that it is awkward to use lme to fit models with crossed > random effects. As Saikat DebRoy and I described in a recent preprint > http://www.stat.wisc.edu/~bates/reports/MultiComp.pdf .../MixedComp.pdf, right? > we now have a good handle on the computational methods for > mixed-effects models with nested or crossed or partially crossed > random effects. > > Both the nlme and the lme4 packages are based on structures that are > tuned to nested random effects and do not easily accomodate crossed > random effects. I have a draft of the contents of classes and methods > for fitting linear mixed-effects models with nested or crossed or > ... but it is a long way from the draft to working, tested code. > Although it will take some time to get all the pieces in place I do > offer some encouragement that this awkward phrasing of crossed random > effects will some day be behind us. Looking forward to it... :-) -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
