[R] Odd diagnostic plots in mixed-effects models

[Andrew Robinson]

John,

thanks for your response.  The fixed effect is estimated at the innermost level.

Andrew
--
Andrew Robinson                      Ph: 208 885 7115
Department of Forest Resources       Fa: 208 885 6226
University of Idaho                  E : andrewr at uidaho.edu
PO Box 441133                        W : http://www.uidaho.edu/~andrewr
Moscow ID 83843                      Or: http://www.biometrics.uidaho.edu
No statement above necessarily represents my employer's opinion.



----- Original Message -----
From: John Maindonald <john.maindonald at anu.edu.au>
Date: Tuesday, April 19, 2005 4:32 am
Subject: [R] Odd diagnostic plots in mixed-effects models

> Is the fixed effect estimated at the innermost level?  If not,
> plots of residuals at that level are surely of limited interest.
> qqplots, to be relevant, surely need to assess normality of
> effects (rather than residuals) at the level that matters for
> the intended inferences.
> 
> If the fixed effect is estimated at the level of the random
> effect, then of course there are just 12 effects that should
> appear in any qq or suchlike plot.
> 
> John Maindonald             email: john.maindonald at anu.edu.au
> phone : +61 2 (6125)3473    fax  : +61 2(6125)5549
> Centre for Bioinformation Science, Room 1194,
> John Dedman Mathematical Sciences Building (Building 27)
> Australian National University, Canberra ACT 0200.
> 
> On 19 Apr 2005, at 8:03 PM, r-help-request at stat.math.ethz.ch wrote:
> 
> > From: Andrew Robinson <andrewr at uidaho.edu>
> > Date: 19 April 2005 12:41:24 PM
> > To: r-help at stat.math.ethz.ch
> > Subject: [R] Odd diagnostic plots in mixed-effects models
> >
> > Dear R community,
> >
> > In the excellent nlme package the default diagnostic plot graphs 
> the 
> > innermost residuals against innermost fitted values.  I recently 
> fit a 
> > mixed-effects model in which there was a very clear positive 
> linear 
> > trend in this plot.
> >
> > I inferred that this trend occurred because my fixed effect was 
> a 
> > two-level factor, and my random effect was a 12-level factor. 
> The 
> > negative residuals were associated with negative random effects 
> > (because of shrinkage, I assume), and the positive with 
> positive.  The 
> > fixed effects explained little varaition. Therefore plotting the 
> > innermost residuals against the innermost fitted values had the 
> > negative residuals to the left and the positive residuals to the 
> > right, occasioning a trend.
> >
> > My questions are: is it (as I suspect) harmless, or does it 
> suggest 
> > that the model is lacking?  And, is this effect likely to 
> compromise 
> > the interpretation of any of the other standard diagnostic plots 
> (eg 
> > qqnorm)?
> >
> > Thanks much for any thoughts,
> >
> > Andrew
> > --
> > Andrew Robinson                      Ph: 208 885 7115
> > Department of Forest Resources       Fa: 208 885 6226
> > University of Idaho                  E : andrewr at uidaho.edu
> > PO Box 441133                        W : 
> http://www.uidaho.edu/~andrewr> Moscow ID 83843                    
>  Or: 
> > http://www.biometrics.uidaho.edu
> 
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