Yes, adding this variable as a covariate is indeed meta-regression with a dichotomous predictor. This assumes that the amount of heterogeneity is the same within the two subgroups. If you subgroup, then you automatically allow the amount of heterogeneity to differ between the two groups. This is discussed here:
http://www.metafor-project.org/doku.php/tips:comp_two_independent_estimates
When combining this with RVE, things are a bit different though. RVE doesn't make assumptions about the underlying variance structure (in fact, the whole point of RVE is that it works (asymptotically) even if the var-cov structure is misspecified). So, even if tau^2 differs across the two groups, RVE in the context of a meta-regression model is still going to provide valid inferences.
Best,
Wolfgang
-----Original Message-----
From: Ioana Cristea [mailto:ioana.alina.cristea at gmail.com]
Sent: Thursday, 03 December, 2020 9:31
To: Viechtbauer, Wolfgang (SP)
Cc: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Subgroup analysis with RVE
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 at 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 at r-
On Behalf Of Ioana Cristea
Sent: Wednesday, 25 November, 2020 15:43
To: r-sig-meta-analysis at 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
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