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

Gladys Barragan-Jason g|@dou86 @end|ng |rom gm@||@com
Tue May 4 11:17:26 CEST 2021

Hi all,
Thanks a lot for your responses.
Actually, I did not specify it before but I am using the 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
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.

Le lun. 3 mai 2021 à 20:18, Viechtbauer, Wolfgang (SP) <
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
> 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] 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

Station d'Ecologie Théorique et Expérimentale (SETE)

CNRS de Moulis

[image: image.png][image: image.png]

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