[R-meta] multivariate fixed-effect meta-analysis
m@rt|nez|ukerm @end|ng |rom gm@||@com
Tue Nov 23 20:38:15 CET 2021
Strictly, the model is fixed-effects multivariate (i.e., MANOVA type)
if Filippo has one effect size per outcome, right?
I mean to the extent that this is not the case, then will this model
diverge from a fixed-effect multivariate model and become more like
marginal models (i.e., nlme::gls() type)?
On Tue, Nov 23, 2021 at 1:22 PM Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> With method="FE", 'random' is also ignored. You will see in the output that it says "Variance Components: none".
> If 'cov_mat' captures the sampling error covariances, then this could be argued to be a fixed-effects version of a multivariate model.
> >-----Original Message-----
> >From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
> >Behalf Of Filippo Gambarota
> >Sent: Tuesday, 23 November, 2021 20:07
> >To: R meta
> >Subject: [R-meta] multivariate fixed-effect meta-analysis
> >I'm performing a multivariate meta-analysis with metafor, however I'm
> >not sure how to obtain the fixed-effect version. Given that I have not
> >enough data I'm not interested in estimating tau for each outcome and
> >the correlation among outcomes but only taking into account the
> >sampling error dependence. I'm using this function:
> > yi = eff_size,
> > V = cov_mat,
> > mods = ~ 0 + outcome,
> > struct = "UN",
> > random = ~ outcome|paper_id,
> > method = "FE",
> > data = data)
> >Of course, the struct argument is no more relevant (as the warning
> >message said) but I'm wondering if the result is what I'm looking for
> >because from the rma.mv documentation the method = "FE" is not
> >mentioned combined with a multivariate parametrization.
> >Thank you!
> >Filippo Gambarota
> >PhD Student - University of Padova
> >Department of Developmental and Social Psychology
> >Website: filippogambarota.netlify.app
> >Research Group: Colab Psicostat
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