[R-meta] weight in rmv metafor

Thu, Jun 11, 2020 6:33 AM

Dear Norman,

To give a simple example: When (some of the) studies contribute multiple estimates, the dataset has a multilevel structure (with estimates nested within studies). A common way to deal with this is to fit a multilevel model with random effects for studies and estimates within studies. Like this:

http://www.metafor-project.org/doku.php/analyses:konstantopoulos2011

However, multiple estimates from the same study are actually often computed based on the same sample of subjects. In that case, the sampling errors are also correlated. The multilevel model does not capture this. For this, one would ideally want to fit a model that also allows for correlated sampling errors. Like this:

http://www.metafor-project.org/doku.php/analyses:berkey1998

However, computing the covariances between the sampling errors within a study is difficult and requires information that is often not available.

We can ignore those correlations and use the multilevel model as a working model that is an approximation to the model that also accounts for correlated sampling errors. After fitting the multilevel model with rma.mv(), one can then use cluster robust inference methods to 'fix things up'.

Quite a bit of this has been discussed at length in previous posts on this mailing list. You might want to search the archives for some of these posts.

Best,
Wolfgang

________________________________________
De: "Wolfgang Viechtbauer" <wolfgang.viechtbauer at maastrichtuniversity.nl>
?: "Norman DAURELLE" <norman.daurelle at agroparistech.fr>, "r-sig-meta-
analysis" <r-sig-meta-analysis at r-project.org>
Envoy?: Jeudi 11 Juin 2020 22:34:55
Objet: RE: [R-meta] weight in rmv metafor

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

-----Original Message-----
From: Norman DAURELLE [mailto:norman.daurelle at agroparistech.fr]
Sent: Thursday, 11 June, 2020 14:13
To: r-sig-meta-analysis
Cc: Viechtbauer, Wolfgang (SP)
Subject: Re: [R-meta] weight in rmv metafor

Hi all,

I read this discussion and one question came to my mind : I also had some
studies that contributed multiple effect sizes in the meta-analysis that I
recently ran thanks to Dr Viechtbauer's advice.
For now I only used the rma function, but should I have used rma.mv because
of these stuides that had multiple effect sizes ?

Thank you !

Norman

________________________________________
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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