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

From: CG Pettersson <cg.pettersson_at_vpe.slu.se>
Date: Thu 07 Sep 2006 - 09:35:40 GMT


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?

Cheers
/CG

-- 
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@vpe.slu.se

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Received on Thu Sep 07 19:42:18 2006

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