[R-sig-ME] Question on random effect

[Joaquín Aldabe]

Thankyou all for your valious comments.
All the best,
Joaquín.

2017-07-12 8:07 GMT-03:00 Anthony R. Ives <arives at wisc.edu>:

> I find that the easiest way to think about this is in terms of the
> covariance matrix of the residuals. For LMMs, the random effects (which
> themselves are independent) produce block-diagonal covariance matrices,
> with positive covariances among residuals within the same level of a random
> effect. Phylogenetic relationships will also produce positive off-diagonal
> elements in the covariance matrix. Focusing on the structure of the
> covariance matrix of residuals often gives the clearest picture of the
> overall assumptions of a model.
>
> Cheers, Tony
>
> On 7/12/17, 3:43 AM, "R-sig-mixed-models on behalf of Viechtbauer Wolfgang
> (SP)" <r-sig-mixed-models-bounces at r-project.org on behalf of
> wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
>
>     Another example where random effects are not assumed to be independent
> is phylogenetic models. Based on a phylogeny, we can construct a
> correlation matrix that indicates the phylogenetic relatedness of the
> species. Random effects for species are then assumed to be correlated
> accordingly.
>
>     Best,
>     Wolfgang
>
>     --
>     Wolfgang Viechtbauer, Ph.D., Statistician | Department of Psychiatry
> and
>     Neuropsychology | Maastricht University | P.O. Box 616 (VIJV1) | 6200
> MD
>     Maastricht, The Netherlands | +31 (43) 388-4170 |
> http://www.wvbauer.com
>
>     >-----Original Message-----
>     >From: R-sig-mixed-models [mailto:r-sig-mixed-models-
> bounces at r-project.org]
>     >On Behalf Of Thierry Onkelinx
>     >Sent: Wednesday, July 12, 2017 10:03
>     >To: Ben Bolker
>     >Cc: r-sig-mixed-models
>     >Subject: Re: [R-sig-ME] Question on random effect
>     >
>     >Dear Joaquin and Ben,
>     >
>     >AFAIK have most random effects a term which is i.i.d. The random
> effects
>     >in
>     >nlme and lme4 directly use the i.i.d. term: x_i ~ N(0, \sigma), hence
> the
>     >random effect itself is i.i.d. INLA has some other constructs
> available.
>     >e.g. a first order random walk where x_i - x_{i-1} ~ N(0, \sigma).
> Here
>     >the
>     >difference between to consecutive random effects is i.i.d. but the
> random
>     >effect itself isn't. The available options are listed at
>     >http://www.r-inla.org/models/latent-models
>     >
>     >Best regards,
>     >
>     >ir. Thierry Onkelinx
>     >Instituut voor natuur- en bosonderzoek / Research Institute for
> Nature and
>     >Forest
>     >team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
>     >Kliniekstraat 25
>     >1070 Anderlecht
>     >Belgium
>     >
>     >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
>     >data.
>     >~ John Tukey
>     >
>     >2017-07-11 13:22 GMT+02:00 Ben Bolker <bbolker at gmail.com>:
>     >
>     >> Yes, the assumption is that the random effects are (conditionally)
>     >> independent.  It can help to specify covariates  (such as
>     >> latitude/longitude or eastings/northings, or environmental
> conditions
>     >> [temperature, elevation, etc.]) for sites to mop up some of the
>     >> independence. It is theoretically possible, although I don't know of
>     >> an easy off-the-shelf way to do it, to impose (e.g.) spatial
>     >> correlation structures at the level of the random effects ...  or
> you
>     >> could examine the spatial dependence of the conditional modes/random
>     >> effects and try to convince yourself it was weak ...
>     >>
>     >> On Tue, Jul 11, 2017 at 7:14 AM, Joaquín Aldabe
>     >> <joaquin.aldabe at gmail.com> wrote:
>     >> > Hi all, when working with mixed models, do the levels of the
> random
>     >> effect
>     >> > have to be independent? For example, if my random effect is the
>     >identity
>     >> of
>     >> > sites and it is associated to the intercept, do sites have to be
>     >> > independent?
>     >> >
>     >> > I appreciate comments and bibliographic references.
>     >> >
>     >> > Thank you very much in advanced,
>     >> >
>     >> > Joaquin
>     >> >
>     >> > --
>     >> > *Joaquín Aldabe*
>     >> >
>     >> > *Grupo Biodiversidad, Ambiente y Sociedad*
>     >> > Centro Universitario de la Región Este, Universidad de la
> República
>     >> > Ruta 15 (y Ruta 9), Km 28.500, Departamento de Rocha
>     >> >
>     >> > *Departamento de Conservación*
>     >> > Aves Uruguay
>     >> > BirdLife International
>     >> > Canelones 1164, Montevideo
>     >> >
>     >> > https://sites.google.com/site/joaquin.aldabe
>     >> > <https://sites.google.com/site/perfilprofesionaljoaquinaldabe>
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-- 
*Joaquín Aldabe*

*Grupo Biodiversidad, Ambiente y Sociedad*
Centro Universitario de la Región Este, Universidad de la República
Ruta 15 (y Ruta 9), Km 28.500, Departamento de Rocha

*Departamento de Conservación*
Aves Uruguay
BirdLife International
Canelones 1164, Montevideo

https://sites.google.com/site/joaquin.aldabe
<https://sites.google.com/site/perfilprofesionaljoaquinaldabe>

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