[R-meta] Should I fit both the only-intercept and the meta-regression?

[Gabriele Midolo]

 Hi Luca,

I am not properly an expert on metafor too, so better hear from the others
as well!

I think the answer to your question depends on what you want to test? What
I do for my meta-analyses, I run a null-model (without moderators) via rma
or rma.mv (depending on how data are structured) to obtain a mean pooled
estimate of the effect size (i.e. the intercept of the model) which is
something I would report first in the results of a paper. Then, a second
step is to look at moderators in meta-regression as you said, and I guess
you can interpret these as linear mixed effect models. So, the intercept in
this case tells you the estimated effect size when your moderator is = 0. I
guess using AIC/BIC/et cetera is a good way to select models when you have
multiple moderators. In general, you might also be interested to look at
"omnibus test of moderators" statistic provided in metafor which assess the
importance of moderatos in a model and if they significanlty contribute to
reduce heterogeneity?.

I don't know if this help and hope people agree with what I've put above!

Gabriele

On 20 March 2018 at 08:28, Luca Santini <luca.santini.eco at gmail.com> wrote:

> Dear all,
>
> I’m totally new to meta-analytical approaches, I am running my first
> meta-analysis using "metafor" but I am now a bit confused about the
> interpretation.
>
> I am running 2 mixed-effect meta-analyses (only-intercept models) on
> correlation coefficients (models A and B). I have an hypothesis for a
> possible continuous moderator for both of the mixed-effect models.
> When I run the meta-analyses without the moderator, the intercept of model
> A is significant and supports the hypothesis. When I run the meta-analyses
> with the moderator (metaregressions), both the intercept and the moderator
> coefficients of model B are significant, whereas neither of the
> coefficients of model A are significant.
> In other words, my conclusions change if I use the simple mixed-effect
> meta-analysis, or the mixed-effect meta-analyis with the moderator
> (metaregression).
>
> So my question is,
> - should I run both of them and use only-intercept model to test my
> hypothesis and the metaregression just as a test for the moderator variable?
> OR
> - should I only run the metaregression and interpret both the intercept
> and the moderator coefficient?
> OR
> - should I run the meta-regression directly but only retain moderators if
> supported by information criteria (AIC, BIC, DIC or similar?)
>
> Note that if I apply the third option using AIC, the moderator of model A
> is excluded whereas the moderator of model B is retained, resulting in both
> models being significant.
>
> I found both cases in the literature, authors that use the simple
> meta-analysis and separately the metaregression to test the effect of
> moderators and authors that only run the metaregression, so I’m a bit
> confused.
>
> Would you be so kind to share your expert opinion on this? Thanks in
> advance.
>
> Best regards
>
> Luca
>
>
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