[R-meta] Compiling different design in the same met-analysis

Gerta Ruecker ruecker @end|ng |rom |mb|@un|-|re|burg@de
Tue May 4 11:25:15 CEST 2021

Hi Gladys,

Note that separate meta-analyses is not the same as subgroup analysis. 
If you do a subgroup analysis (in the Cochrane sense), you have design 
as a moderator and obtain a treatment-design interaction test, which you 
don't get if conducing separate analyses. Therefore I would prefer to 
present all in one.



Am 04.05.2021 um 11:17 schrieb Gladys Barragan-Jason:
> Hi all,
> Thanks a lot for your responses.
> Actually, I did not specify it before but I am using the rma.mv 
> <http://rma.mv> function since I can have several estimates from 
> several studies of the same lab  (random=~1|lab/study/estid). 
> Following your recommendations, I checked whether the type of design 
> had a significant effect on effect sizes and actually it didn't except 
> for one specific type of intervention in which I do not have that much 
> data:  3 papers for each design containing 7 and 4 effect sizes 
> respectively. In this case, meta-analysis of overall estimates is 
> non-significant while when computing them separately, one is 
> significant (control vs. treatment groups) while the other is not 
> (pre- vs. post treatment).
> I do think that would make sense to present the overall meta-analysis 
> as well as the two designs separately ? In any case, we would need 
> more data to conclude for sure.
> Best,
> Gladys
> Le lun. 3 mai 2021 à 20:18, Viechtbauer, Wolfgang (SP) 
> <wolfgang.viechtbauer using maastrichtuniversity.nl 
> <mailto:wolfgang.viechtbauer using maastrichtuniversity.nl>> a écrit :
>     Agree, but I also want to point to this:
>     https://www.metafor-project.org/doku.php/tips:computing_adjusted_effects
>     <https://www.metafor-project.org/doku.php/tips:computing_adjusted_effects>
>     It discusses the concept of computing adjusted effects, which may
>     be what you are looking for, Gladys. However, as noted at the end,
>     some may question the usefulness and interpretability of such an
>     estimate.
>     Best,
>     Wolfgang
>     >-----Original Message-----
>     >From: R-sig-meta-analysis
>     [mailto:r-sig-meta-analysis-bounces using r-project.org
>     <mailto:r-sig-meta-analysis-bounces using r-project.org>] On
>     >Behalf Of Dr. Gerta Rücker
>     >Sent: Monday, 03 May, 2021 20:09
>     >To: Gladys Barragan-Jason
>     >Cc: R meta
>     >Subject: Re: [R-meta] Compiling different design in the same
>     met-analysis
>     >
>     >Hi Gladys,
>     >
>     >You may pool all effects in a meta-analysis, using "design" as a
>     >moderator. In meta-analysis, this is called a subgroup analysis (for
>     >example by Cochrane). You then get both within-subgroup effects and a
>     >pooled effect, and also a test of treatment--design interaction, that
>     >says whether the treatment effect is different between designs.
>     Thus you
>     >have all what you are interested in. However, in your
>     interpretation you
>     >have to account for the different character of the studies: In a
>     >two-group parallel design, if it is randomized (you did not mention
>     >whether it is), you can expect an unbiased estimate of the treatment
>     >effect. In a pre-post design, you must expect all kinds of biases (to
>     >mention only regression to the mean) and also, as Michael said,
>     >different variation. Therefore you have to interpret results with
>     caution.
>     >
>     >Best, Gerta
>     >
>     >Am 03.05.2021 um 19:42 schrieb Gladys Barragan-Jason:
>     >> Hi Gerta and Michael,
>     >> I am not sure to understand. I am not saying the the effect
>     size are
>     >> different. They are comparable but of course differ in term of ci
>     >> since the number of studies, participants are different. I
>     would like
>     >> to know whether we can make obtain an overall effect size while
>     >> controlling for design. So maybe the answer is no.
>     >> Thanks
>     >> Gladys
> -- 
> ------------------------------------------
> Gladys Barragan-Jason, PhD.  Website 
> <https://sites.google.com/view/gladysbarraganjason/home>
> Station d'Ecologie Théorique et Expérimentale (SETE)
> CNRS de Moulis
> image.pngimage.png
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Dr. rer. nat. Gerta Rücker, Dipl.-Math.

Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center - University of Freiburg

Stefan-Meier-Str. 26, D-79104 Freiburg, Germany

Phone:    +49/761/203-6673
Fax:      +49/761/203-6680
Mail:     ruecker using imbi.uni-freiburg.de
Homepage: https://www.uniklinik-freiburg.de/imbi-en/employees.html?imbiuser=ruecker

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