[R-meta] multivariate fixed-effect meta-analysis
jepu@to @end|ng |rom gm@||@com
Wed Nov 24 17:47:44 CET 2021
The term "multivariate" is used in several different ways in the
meta-analysis (and mixed-effects models) literature. The metafor
documentation usually uses it in the broadest sense of a model with
more than one effect size estimate per independent sample. I think
Luke was referring to the stricter sense of a model for a set of
multi-variate effect size estimates (where each study contributes at
most one effect size estimate to each of several distinct categories).
More on disambiguation here:
On Wed, Nov 24, 2021 at 7:45 AM Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> >-----Original Message-----
> >From: Luke Martinez [mailto:martinezlukerm using gmail.com]
> >Sent: Tuesday, 23 November, 2021 20:38
> >To: Viechtbauer, Wolfgang (SP)
> >Cc: Filippo Gambarota; R meta
> >Subject: Re: [R-meta] multivariate fixed-effect meta-analysis
> >Dear Wolfgang,
> >Strictly, the model is fixed-effects multivariate (i.e., MANOVA type)
> >if Filippo has one effect size per outcome, right?
> I don't know what you mean by that. If you only specify V and no random effects, one could call it a multivariate fixed-effects model, just like used for example in this chapter:
> Whether one has one effect size per outcome or 20 is not relevant as long as V captures the covariance between the sampling errors of the estimates.
> >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)?
> Again, I can't follow your reasoning here.
> >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.
> >> Best,
> >> Wolfgang
> >> >-----Original Message-----
> >> >From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org]
> >> >Behalf Of Filippo Gambarota
> >> >Sent: Tuesday, 23 November, 2021 20:07
> >> >To: R meta
> >> >Subject: [R-meta] multivariate fixed-effect meta-analysis
> >> >
> >> >Hi!
> >> >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:
> >> >```
> >> >rma.mv(
> >> > 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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