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

From: Andrew Robinson <A.Robinson_at_ms.unimelb.edu.au>
Date: Thu 07 Sep 2006 - 10:03:28 GMT

Hi CG,

I think that the best pair of summary plots are

  1. the fitted values without random effects against the observed response variable, and
  2. fitted values with random effects against the observed response variable.

The first plot gives a summary of the overall quality of the fixed effects of the model, the second gives a summary of the overall quality of the fixed effects and random effects of the model.

eg

fm1 <- lme(distance ~ age, data = Orthodont)

plot(fitted(fm1, level=0), Orthodont$distance) abline(0, 1, col="red")

plot(fitted(fm1, level=1), Orthodont$distance) abline(0, 1, col="red")

I hope that this helps.

Andrew

On Thu, Sep 07, 2006 at 11:35:40AM +0200, CG Pettersson wrote:
> 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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-- 
Andrew Robinson  
Department of Mathematics and Statistics            Tel: +61-3-8344-9763
University of Melbourne, VIC 3010 Australia         Fax: +61-3-8344-4599
Email: a.robinson_at_ms.unimelb.edu.au         http://www.ms.unimelb.edu.au

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Received on Thu Sep 07 20:29:28 2006

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