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