[R-sig-ME] Modelling random effects with SITE, YEAR and SPECIES
Thierry.ONKELINX at inbo.be
Tue May 12 11:57:30 CEST 2009
The error you get with A*SPECIES indicates that you have to few data.
Probabily because not all the combination of A and SPECIES exist in your
dataset. Which was what I feared would happen.
As I meantioned before, adding A as a random slope to the random effect
will give you opnly info on the variability of A between the different
species, but not estimates per species. That's the difference between
random effects and mixed effects.
If the info per species is that important, then I would suggest to build
a model for each species.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
~ John Tukey
Van: CL Pressland [mailto:Kate.Pressland at bristol.ac.uk]
Verzonden: maandag 11 mei 2009 17:53
Aan: ONKELINX, Thierry; R Mixed Models
Onderwerp: RE: [R-sig-ME] Modelling random effects with SITE, YEAR and
thank you for you informative reply. I have had a go at your suggestions
but have been stumped:
--On 07 May 2009 10:16 +0200 "ONKELINX, Thierry"
<Thierry.ONKELINX at inbo.be>
> Dear Kate,
> Adding SPECIES as a random effect indicates that you want to take the
> effect of SPECIES into account but not need to know the effect of the
> individual SPECIES. If you do want to know that effect then you have
> add species to fixed effects. Examining the effect of A, B and C on
> species (as a fixed effect) requires interactions between them. The
> model then looks like (A + B + C) * SPECIES + Year + (1|SITE) +
> This will only work if you have sufficiend data.
I tried this approach with data I have that is SPECIES recorded as SITES
over YEARS but when I tried A*SPECIES as a fixed factor I received this
"Error in mer_finalize(ans) : Downdated X'X is not positive definite,
I've searched for what this error means but I cannot understand it.
This was written by Douglas Bates in response to [Re: [R] lme4, error in
mer_finalize(ans)] posted 05 Dec 2008:
"That, admittedly obscure, error message relates to the fixed-effects
specification rt ~ length + length:pos being rank deficient. If you look
the summary of the linear model fit you will see that there are 3
coefficients that are not determined because of singularities. The lm
function detects the singularities and fits a lower-rank model. The
function is not as sophisticated. It just detects the singularities and
I am unsure what this means or how it translates to my data. In my
I have 78 "SPECIES" (factor, coded as numbers) and "A" is ordered data
1, 2. The y variable is number/m. You wrote that this would only work is
you had sufficient data - each species is not recorded each time, so is
this reduced data the cause i.e. not enough observations for n?
> Another option is to keep species as a random effect and add random
> slopes according to A, B and C. This will allow a different effect of
> B anc C for each species. The model would look like A + B + C + Year +
> (1|SITE) + (1|YEAR) + (A + B + C|SPECIES)
I have tried this way also but I am unsure of the output - it does not
species specific information and therefore I cannot work out which
is more affected by A, only if SPECIES as a whole are affected or not by
each category of A. This is not useful to me as I would like to
given the random effects, if A 0, 1, or 2 affect which species in the
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature
> and Forest
> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> methodology and quality assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> tel. + 32 54/436 185
> Thierry.Onkelinx at inbo.be
> To call in the statistician after the experiment is done may be no
> than asking him to perform a post-mortem examination: he may be able
> say what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data.
> ~ Roger Brinner
> The combination of some data and an aching desire for an answer does
> ensure that a reasonable answer can be extracted from a given body of
> ~ John Tukey
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