[R-meta] weight in rmv metafor

Thu, Jun 11, 2020 5:34 AM

Dear Norman,

If you only used rma(), then this is not correct. rma.mv() with an appropriately specified model (plus clubSandwich::coef_test() if the working model is only an approximation and doesn't cover all dependencies) would be more appropriate.

Best,
Wolfgang

________________________________________
De: "James Pustejovsky" <jepusto at gmail.com>
?: "Wolfgang Viechtbauer" <wolfgang.viechtbauer at maastrichtuniversity.nl>
Cc: "r-sig-meta-analysis" <r-sig-meta-analysis at r-project.org>, "Huang Wu"
<huang.wu at wmich.edu>
Envoy?: Mercredi 10 Juin 2020 05:08:09
Objet: Re: [R-meta] weight in rmv metafor

Hi Huang,

I've written up some notes that add a bit of further intuition to the
discussion that Wolfgang provided. The main case that I focus on is a model
that is just a meta-analysis (i.e., no predictors) and that includes random
effects to capture both between-study and within-study heterogeneity. I
also say a little bit about meta-regression models with only study-level
predictors.

https://www.jepusto.com/weighting-in-multivariate-meta-analysis/

Best,
James

On Sun, Jun 7, 2020 at 4:11 PM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

Of course the weights "impact the estimated fixed effects". But whether
studies with multiple effect sizes tend to receive more weight depends on
various factors, including the variances of the random effects and the
sampling error (co)variances.

A more detailed discussion around the way weighting works in rma.mv
models can be found here:

http://www.metafor-project.org/doku.php/tips:weights_in_rma.mv_models

Note that weights(res, type="rowsum") currently only works in the 'devel'
version of metafor, so follow
https://wviechtb.github.io/metafor/#installation if you want to reproduce
this part as well.

I hope this clarifies things.

Best,
Wolfgang

[R-meta] weight in rmv metafor

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