[R-meta] Compiling different design in the same met-analysis
ph|||ppet@dger @end|ng |rom gm@||@com
Tue May 4 12:04:24 CEST 2021
Thanks Gerta for such a simple and important reminder.
Apart from having test for subgroup differences, which other advantage
can have doing a subgroup analysis (with the moderator in
meta-regression) vs separate meta-analyses?
Just assuming that is a categorical moderator
On 04/05/2021 11:25, Gerta Ruecker wrote:
> 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.
>> 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:
>> 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
>> >-----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
>> >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
>> >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
>> R-sig-meta-analysis mailing list
>> R-sig-meta-analysis using r-project.org
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