[R-meta] Subgroup analysis with RVE

Ioana Cristea |o@n@@@||n@@cr|@te@ @end|ng |rom gm@||@com
Thu Dec 3 09:31:08 CET 2020


Hi
Thank you, sorry I did not explain clearly. I estimated effects within
subgroups with RVE (intercept only model in each), but I did not do a
between-groups test of significance. I did fit a model with a between
groups covariate (subgroups coded dichotomously: high/low), which I took to
be the equivalent of a meta-regression with a dichotomous predictor.
Best
Ioana

On Thu, Dec 3, 2020 at 9:20 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> Dear Ioana,
>
> I am not sure why you think that a test of that moderators is not useful
> when the number of effect sizes is so different between the two groups. All
> else equal, power will indeed be lower as opposed to the case where k is
> similar for the two groups, but that will be the case no matter how you
> analyze the data (via meta-regression or subgrouping).
>
> This aside, I am a bit confused by your question. A subgroup analysis is
> just that: Fitting a particular model in a subgroup of the studies. That
> can be done with or without RVE. You seem to have done this already ("I
> estimated effects in the high and low subgroup separately").
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org]
> >On Behalf Of Ioana Cristea
> >Sent: Wednesday, 25 November, 2020 15:43
> >To: r-sig-meta-analysis using r-project.org
> >Subject: [R-meta] Subgroup analysis with RVE
> >
> >Dear all
> >I am running a meta-analysis with robust variance estimation (RVE) and my
> >focus is on a categorical variable (a risk of bias domain variable, coded
> >dichotomously, high vs low, in the database "0" for low risk and "1" for
> >high risk). I estimated effects in the high and low subgroup separately,
> >each in an intercept only model. I also ran the RVE model estimating the
> >between-study effect of covariates, including my predictor (which is a
> >between study variable) as a covariate (it was not significant). I think a
> >big problem is that the two subgroups delineated by the categorical
> >variable are very uneven in terms of the information contained (one has 45
> >effect sizes, one 13) and in my view a test of significance for
> differences
> >between them is not useful.
> >One of my co-authors would also like us to run a subgroup analysis. I am
> >not sure how to do that, if it is possible with RVE and if it adds
> anything
> >to the model estimating between-study covariates, which I already ran.
> >Thank you!
> >Ioana
> >
> >--
> >Ioana-Alina Cristea, Ph.D.
> >Assistant Professor
> >Department of Brain and Behavioral Sciences
> >University of Pavia, Piazza Botta 11, 27100 Pavia, Italy
> >
> >Research affiliate
> >METRICS (Meta-research Innovation Center at Stanford)
> >Stanford University, California, USA
> >Editorial Advisory Board Lancet Psychiatry
> ><https://www.thelancet.com/journals/lanpsy/home>
> >International Editorial Board BJPsych Open
> ><https://www.cambridge.org/core/journals/bjpsych-open>
> >
> >ORCid: http://orcid.org/0000-0002-9854-7076
> >Publons: https://publons.com/author/1196647/ioana-alina-cristea#profile
> >Researchgate: https://www.researchgate.net/profile/Ioana_Cristea
> >Twitter: https://twitter.com/IoanaA_Cristea
>


-- 
Ioana-Alina Cristea, Ph.D.
Assistant Professor
Department of Brain and Behavioral Sciences
University of Pavia, Piazza Botta 11, 27100 Pavia, Italy

Research affiliate
METRICS (Meta-research Innovation Center at Stanford)
Stanford University, California, USA
Editorial Advisory Board Lancet Psychiatry
<https://www.thelancet.com/journals/lanpsy/home>
International Editorial Board BJPsych Open
<https://www.cambridge.org/core/journals/bjpsych-open>

ORCid: http://orcid.org/0000-0002-9854-7076
Publons: https://publons.com/author/1196647/ioana-alina-cristea#profile
Researchgate: https://www.researchgate.net/profile/Ioana_Cristea
Twitter: https://twitter.com/IoanaA_Cristea

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