Message-ID: <CAEJcFY3+1i88Nq2=OxSPrScvh6e8w8EYvjOMrZMCZm+zLLaytw@mail.gmail.com>
Date: 2020-12-14T19:48:41Z
From: Valeria Ivaniushina
Subject: [R-meta] moderator and adjusted effects
In-Reply-To: <9da5b37d19f56111cf86560bdf6d846d8e729e72.camel@med.uni-goettingen.de>
Michael, Christian,
Thank you!
I have just 30 effects in three groups, so the results between two options
are indeed very different. Thank you for explaining what is right and why
:)
Best,
Valeria
On Mon, Dec 14, 2020 at 10:38 PM R?ver, Christian <
christian.roever at med.uni-goettingen.de> wrote:
> Dear Valeria,
>
> another difference between your options (1) and (2) is that in case of
> (1) you get three different, independent estimates of the heterogeneity
> (tau), whereas in (2) you assume a common heterogeneity parameter for
> all three groups.
>
> In case you have "many" studies in each group (say, 20), it may not
> make much of a difference, but if you have "few" studies (say, 5) in
> some, and the assumption of a common heterogeneity parameter seems
> plausible, then borrowing information on the heterogeneity across the
> three groups may help.
>
> Cheers,
>
> Christian
>
>
> On Mon, 2020-12-14 at 18:18 +0000, Michael Dewey wrote:
> > Dear Valeria
> >
> > Comments in-line
> >
> > On 14/12/2020 17:13, Valeria Ivaniushina wrote:
> > > Dear experts,
> > >
> > > In my sample of articles for meta-analysis there are three
> > > categories, or
> > > three conditions, that may influence the effect of interest.
> > >
> > > I am more interested in estimating different effects from these
> > > conditions
> > > than in explaining heterogeneity in effect sizes.
> > > 1) I can do a meta-analysis for each of these conditions separately
> > > and get
> > > three different mean effect sizes.
> > > 2) Or I can do a meta-analysis of the whole sample, then include a
> > > condition as a moderator and calculate adjusted effects as
> > > described here :
> > >
> http://www.metafor-project.org/doku.php/tips:computing_adjusted_effects
> > >
> >
> > I would go for option two as it will give you estimates of the
> > differences between the levels of your moderator.
> >
> > > Which option is better?
> > >
> > > Additional question: when I include a categorical moderator, is it
> > > the
> > > same as including a dummy variable in a regression?
> > > How can I specify that the variable is categorical with 3 levels?
> > >
> >
> > If you make the moderator a factor then R will take care of this for
> > you.
> >
> > > Best,
> > > Valeria
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > R-sig-meta-analysis mailing list
> > > R-sig-meta-analysis at r-project.org
> > > https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
> > >
> >
> >
>
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