[R-meta] weight in rmv metafor

Norman DAURELLE norm@n@d@ure||e @end|ng |rom @grop@r|@tech@|r
Fri Jun 12 01:08:31 CEST 2020

Dear all, Dr Viechtbauer, Dr Del Ponte,thank you for your answers ! I will look into what you advised me to read, and also go and read more of the archive.If I have more questions I will come back and ask them.Once again, thank you for developing the package metafor in R Dr Viechtbauer, and for creating this mailing list.Have a nice week-end,Norman
----- Mail d'origine -----
De: Emerson Del Ponte <delponte using ufv.br>
�: Norman DAURELLE <norman.daurelle using agroparistech.fr>
Cc: Wolfgang Viechtbauer <wolfgang.viechtbauer using maastrichtuniversity.nl>, r-sig-meta-analysis <r-sig-meta-analysis using r-project.org>
Envoy�: Thu, 11 Jun 2020 15:43:05 +0200 (CEST)
Objet: Re: [R-meta] weight in rmv metafor

Dear Norman
You may want to check reproducible examples of my previous work on this exact application context as a starting point. 

On Thu, 11 Jun 2020 at 10:06 Norman DAURELLE <norman.daurelle using agroparistech.fr> wrote:

Thank you. 

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 ? 

Thank you, 


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 

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. 



>-----Original Message----- 

>From: Norman DAURELLE [mailto:norman.daurelle using 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 ! 





>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 


>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 








>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: 


>> 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 

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Emerson M. Del Ponte
Universidade Federal de Vi�osa, Brazil
Chair of the Graduate Studies in Plant PathologyEIC for Tropical Plant Pathology Co-Founder of Open Plant PathologyMy websites: Twitter | GitHub | Google Scholar | ResearchGateTel +55 31 36124830

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