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 ??20:18, Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer at maastrichtuniversity.nl
<mailto:wolfgang.viechtbauer at maastrichtuniversity.nl>> a ?crit?:
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 at r-project.org
<mailto:r-sig-meta-analysis-bounces at r-project.org>] On
>Behalf Of Dr. Gerta R?cker
>Sent: Monday, 03 May, 2021 20:09
>To: Gladys Barragan-Jason
>Cc: R meta
>Subject: Re: [R-meta] Compiling different design in the same
>
>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.
>have all what you are interested in. However, in your
>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
>
>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
>> different. They are comparable but of course differ in term of ci
>> since the number of studies, participants are different. I
>> to know whether we can make obtain an overall effect size while
>> controlling for design. So maybe the answer is no.
>> Thanks
>> Gladys