Oh, the question might have been more precisely formulated I guess... "update" surely helps a lot in the practical work at the computer. But that is not my problem. The problem is where and how to introduce the variables in the command.
I´ve tried things like: random = ~ P.AL | Trial/Block as the random call, looking for some sort of direct effect from the soil analysis P.AL. That results in a worse model than without the term, possibly becouse the effect of the soil already is, implicitlely, inside the term Trial. What I am looking for is a way of evaluating several factors that have just one observation for each Trial, still having the the nice Trial/Block structure present in the model. Or am I just stupid? /CG ------------------- > Might "update" help? spencer graves > > CG Pettersson wrote: > > >Hello everybody! > >I´m working with a dataset from twelve fertilizer trials, where the > >technical fertilizer product and application method, but not the > >intensity of fertilization, is varied. (I´m using R1.7.1 and W2000.) > > > >The call: > > > >ejna1t4b.lme <- lme( Yield ~ TrCode, data = ejna1t4, > >+ random = ~ 1 | Trial/Block) > > > >works as far as I can understand well, the Block structure of the > >trials is used efficiently and everything looks nice according to > >plots of the object. > > > >Now I want to evaluate the influence of observations from the > >different experimental places (for example soil analyses or rainfall) > >- Could I do that without skipping the Trial/Block structure, or do I > >have to start from scratch again? The observed values will naturally > >only have one level for each Trial, so the term Trial/Block will host > >the effects of all observed (and unobserved) phenomena in each trial. > >Now I want to know where the effects come from. > > > >I´ve been looking for a text on this, both in MASS and Pinheiro & > >Bates, without finding any. Any hints of where to look? > > > >Thanks > >/CG > > > >CG Pettersson, MSci, PhD Stud. > >Swedish University of Agricultural Sciences > >Dep. of Ecology and Crop Production. Box 7043 > >SE-750 07 Uppsala > > > >______________________________________________ > >[EMAIL PROTECTED] mailing list > >https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > > > > CG Pettersson, MSci, PhD Stud. Swedish University of Agricultural Sciences Dep. of Ecology and Crop Production. Box 7043 SE-750 07 Uppsala ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help