[R-meta] weight in rmv metafor
norm@n@d@ure||e @end|ng |rom @grop@r|@tech@|r
Thu Jun 11 15:05:15 CEST 2020
I am not sure I understand exactly what you mean by " i f the working model is only an approximation and doesn't cover all dependencies ".
Could you please explain it ?
For now I used the rma() function to synthesize the available literature existing on the blackleg - oil seed rape disease-yield relationship, using slopes as effect-sizes.
the models that gave me the slopes I used in the meta-analysis are all Y = a + bX, simple linear regressions with Y being the yield and X being the diseqse severity.
So my slopes, b, are all negative, and I have obtained a "summary" effect size through the rma() function.
But I indeed have two studies that for now contribute to most of the effect-sizes that are included in my meta-analysis.
So why exactly is it necessary to use the rma.mv() function ?
What exactly does the "multivariate" qualificative refer to ?
De: "Wolfgang Viechtbauer" <wolfgang.viechtbauer using maastrichtuniversity.nl>
�: "Norman DAURELLE" <norman.daurelle using agroparistech.fr>, "r-sig-meta-analysis" <r-sig-meta-analysis using r-project.org>
Envoy�: Jeudi 11 Juin 2020 22:34:55
Objet: RE: [R-meta] weight in rmv metafor
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.
>From: Norman DAURELLE [mailto:norman.daurelle using agroparistech.fr]
>Sent: Thursday, 11 June, 2020 14:13
>Cc: Viechtbauer, Wolfgang (SP)
>Subject: Re: [R-meta] weight in rmv metafor
>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 !
>De: "James Pustejovsky" <jepusto using gmail.com>
>�: "Wolfgang Viechtbauer" <wolfgang.viechtbauer using maastrichtuniversity.nl>
>Cc: "r-sig-meta-analysis" <r-sig-meta-analysis using r-project.org>, "Huang Wu"
><huang.wu using wmich.edu>
>Envoy�: Mercredi 10 Juin 2020 05:08:09
>Objet: Re: [R-meta] weight in rmv metafor
>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
>On Sun, Jun 7, 2020 at 4:11 PM Viechtbauer, Wolfgang (SP) <
>wolfgang.viechtbauer using 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:
>> 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.
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