Douglas Bates <bates <at> stat.wisc.edu> writes: > It is not easy to decide what "predict" should return for a linear > mixed model, let alone the more complicated cases. Do you want > predictions based on the fixed-effects only or based on a combination > of the fixed-effects and the random-effects? For the lme function in > the nlme package we allowed "levels" of predictions but that won't > work for all models that can be fit with lme4.
I do actually think there's a reasonable way to specify this -- an indicator specifying which random effects should have their conditional modes included in the prediction (the default could be either 'none' or 'all'). Further discussion should presumably move to r-sig-mixed-models. > > On Tue, Mar 23, 2010 at 9:18 AM, Markus Loecher wrote: > > Dear mixed effects modelers, > > I seem unable to find a predict method for mer objects in the package lme4. > > Am I not seeing the forest for the trees ? In the meantime you can construct your own model matrices and use them to generate the predictions by hand -- see http://glmm.wikidot.com/local--files/examples/Owls.pdf http://glmm.wikidot.com/local--files/examples/Owls.Rnw for a bit of a worked example. Ben Bolker ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
