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

[Rafael Rios Moura]

Dear Wolfgang,

Thank you very much for the reply. I tried to add standard errors as a
fixed predictor in the repeatability test, but I obtained these errors:

Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,:
unable to evaluate scaled gradient
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,:
Problem with Hessian check (infinite or missing values?)

I used an optimizer, but It did not work. I do not know exactly if I need
to account for standard errors in the repeatability test. It seems that the
residuals are enough, but I would be grateful if you can share with me your
thoughts about it. I ran a random-effects multilevel meta-analysis using
effect size ID, study ID, species ID, and phylogenetic correlations as
random effects. Then, I extracted standard residuals to use as a response
variable in the repeatability test using rptR package. The test is a
general linear mixed model which measures the among-group variance
attributed to a particular random variable (corresponding to spatial
replicates, for example) divided by the sum of the within-group residual
variance and the among-group variance to calculate a R statistic. rpt
function of rptR package also performs bootstrapping methods to calculate
confidence intervals and P-values. Do you think that I need to include
another variable within the repeatability model? Thank you in advance.

Stoffel et al. 2007:
https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12797%4010.1111/%28ISSN%292041-210X.CODEVI2018

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
<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 ter., 8 de dez. de 2020 às 11:20, Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> escreveu:

> I am not familiar with repeatability tests, so I cannot comment on that
> part.
>
> However, if you use residuals for further analyses, you may want to
> account for differences in their standard errors and the fact that they are
> correlated. As decribed, you can get their standard errors via rstandard()
> and you can get their whole var-cov matrix with vcov(..., type="resid").
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: Rafael Rios Moura [mailto:biorafaelrm using gmail.com]
> >Sent: Tuesday, 08 December, 2020 13:45
> >To: Viechtbauer, Wolfgang (SP)
> >Cc: r-sig-meta-analysis using r-project.org
> >Subject: Re: Extracting residuals from rma.mv function
> >
> >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
> >Research Gate: https://www.researchgate.net/profile/Rafael_Rios_Moura2
> >Rios de Ciência: https://www.youtube.com/channel/UCu2186wIJKji22ai8tvlUfg
> >
> >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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