[R-meta] Extracting residuals from rma.mv function

[Rafael Rios Moura]

 Dear Wolfgang,

Thank you for the reply. My idea is to obtain unbiased weighted outcomes to
test their repeatability in spatial and temporal replicates. I conducted
random-effects multilevel meta-analyses using rma.mv function (weighted by
the inverse of variance) controlling for phylogenetic relatedness. Then, I
extracted residuals using residuals(my model, type = "response") and used
the outcomes in the repeatability tests. Do you see any problem with this
approach?

All the best,

Rafael.
_______________________________________________________

*Prof. Dr. Rafael Rios Moura*

*scientia amabilis *
Núcleo de Extensão e Pesquisa em Ecologia e Evolução (NEPEE)
Departamento de Ciência Biológicas
UEMG Ituiutaba

ORCID: http://orcid.org/0000-0002-7911-4734
Currículo Lattes: http://lattes.cnpq.br/4264357546465157
<http://orcid.org/0000-0002-7911-4734>
<http://lattes.cnpq.br/4264357546465157>
<http://lattes.cnpq.br/4264357546465157>Research Gate:
https://www.researchgate.net/profile/Rafael_Rios_Moura2
<http://orcid.org/0000-0002-7911-4734>
Rios de Ciência: https://www.youtube.com/channel/UCu2186wIJKji22ai8tvlUfg
<http://orcid.org/0000-0002-7911-4734>


Em seg., 7 de dez. de 2020 às 04:53, Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> escreveu:

> Dear Rafael,
>
> I don't understand the details of what you are trying to do, but you can
> obtain residuals from a 'rma.mv' model with resid(). However, that will
> only give you the residuals and no indication of their precision. With
> rstandard(), you can get get the residuals ('resid') and the corresponding
> standard errors ('se'). If the model you have fitted accounted for
> phylogenetic non-independence and differences in the precision of the
> effect sizes, then so will the residuals and corresponding standard errors.
>
> However, note that residuals are not independent (that is even the case in
> simple regression models outside of the meta-analytic context). With:
>
> vcov(res, type="resid")
>
> (assuming the model object is called 'res') you can get the full var-cov
> matrix of the residuals. You will note that this is not a diagonal matrix.
> The standard errors are just the square root of the diagonal elements:
>
> sqrt(diag(vcov(res, type="resid")))
>
> So, whatever you intend to do with the residuals may require that you not
> only account for differences in their precision, but also their covariances.
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: Rafael Rios Moura [mailto:biorafaelrm using gmail.com]
> >Sent: Saturday, 05 December, 2020 18:26
> >To: r-sig-meta-analysis using r-project.org; Viechtbauer, Wolfgang (SP)
> >Subject: Extracting residuals from rma.mv function
> >
> >Dear Dr. Wolfgang and All,
> >
> >I want to extract unbiased residuals of a rma.mv function to use in a
> >repeatability analysis for another random variable in the rptR package.
> >Thus, I want to control for precision (or weight) for each effect size and
> >phylogenetic non-independence. Which kind of residuals should be more
> >appropriate to do that in a mixed-effects multilevel meta-analysis and how
> >can I extract them from the rma.mv function? Any help is welcome.
> >
> >All the best,
> >_______________________________________________________
> >
> >Prof. Dr. Rafael Rios Moura
> >scientia amabilis
> >Núcleo de Extensão e Pesquisa em Ecologia e Evolução (NEPEE)
> >Departamento de Ciência Biológicas
> >UEMG Ituiutaba
> >
> >ORCID: http://orcid.org/0000-0002-7911-4734
> >Currículo Lattes: http://lattes.cnpq.br/4264357546465157
> >Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2
> >Rios de Ciência: https://www.youtube.com/channel/UCu2186wIJKji22ai8tvlUfg
>

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