[R] Model vs. Observed for a lme() regression fit using two variables

CG Pettersson cg.pettersson at vpe.slu.se
Thu Sep 7 11:35:40 CEST 2006

Dear all.

R 2.3.1, W2k.

I am working with a field trial series where, for the moment, I do 
regressions using more than one covariate to explain the protein levels 
in malting barley.

To do this I use lme() and a mixed call, structured by both experiment 
(trial) and repetition in each experiment (block). Everything works 
fine, resulting in nice working linear models using two covariates. But 
how do I visualize this in an efficient and clear way?

What I want is something like the standard output from all multivariate 
tools I have worked with (Observed vs. Predicted) with the least square 
line in the middle. It is naturally possible to plot each covariate 
separate, and also to use the 3d- sqatterplot in Rcmdr to plot both at 
the same time, but I want a plain 2d plot.

Who has made a plotting method for this and where do I find it?
Or am I missing something obvious here, that this plot is easy to 
achieve without any ready made methods?


CG Pettersson, MSci, PhD Stud.
Swedish University of Agricultural Sciences (SLU)
Dept. of Crop Production Ecology. Box 7043.
SE-750 07 UPPSALA, Sweden.
+46 18 671428, +46 70 3306685
cg.pettersson at vpe.slu.se

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