[R-meta] Subgroup analysis with RVE

Thu, Dec 3, 2020 3:30 AM

Hi Gerta,

Interesting, thanks for this clarification on terminology.

In principle, it is an arbitrary distinction anyway, since one can easily fit a meta-regression model that allows tau^2 to differ across subgroups, which is exactly identical to fitting RE models in the two subgroups.

But this is only true when the only predictor is the factor distinguishing the subgroups. Once the model includes additional predictors, the equivalence breaks down (unless one fits a model that allows the coefficients for the additional predictors to also differ across subgroups).

Best,
Wolfgang

-----Original Message-----
From: Dr. Gerta R?cker [mailto:ruecker at imbi.uni-freiburg.de]
Sent: Thursday, 03 December, 2020 12:15
To: Viechtbauer, Wolfgang (SP); Ioana Cristea
Cc: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Subgroup analysis with RVE

Dear Wolfgang, dear Ioana,

This is only to hint to a different use of the notion "subgroup
analysis" at Cochrane, which may have led to misunderstandings here.
Cochrane uses "subgroup analysis" to denote metaregression with a
nominal covariate (common heterogeneity parameter and between-groups
test), not for separate analyses within groups. See the Cochrane
Handbook for Systematic Reviews of Interventions,
https://training.cochrane.org/handbook/current/chapter-10#section-10-11-2
. Thus, Cochrane's subgroup analysis is a special case of
metaregression. This notion is also used in R package meta.

Best,

Gerta

Am 03.12.2020 um 10:10 schrieb Viechtbauer, Wolfgang (SP):

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-

project.org]

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

big problem is that the two subgroups delineated by the categorical
variable are very uneven in terms of the information contained (one has

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

[R-meta] Subgroup analysis with RVE

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