[R] Evaluating outer observations in an lme object.

[CG Pettersson]

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