[R-meta] Studies with independent samples of participants
jepu@to @end|ng |rom gm@||@com
Mon Jun 21 22:24:00 CEST 2021
I would recommend using the first strategy, in which you create an
additional ID variable to distinguish independent samples nested within a
study. Just as a matter of coding, this is a better representation of the
structure of your data. You can always then simplify to get the data you'd
have from the other strategy (where you ignore the study/sample
distinction). But if you follow the second strategy, there's not an easy
way to add in the study and sample IDs without going back to recode.
How you ultimately approach modeling the data is an empirical question.
With only two studies that have multiple samples, it is probably not
reasonable to include random effects at both the study level and the sample
level. But you could consider using either ~ 1 | studyID or ~ 1 | sampleID
(assuming that sample has a unique value for every unique sample). The
former assumes that the true effect for a given study is constant across
samples nested within that study. The latter assumes that the true effects
from samples in the same study are no more closely related than the true
effects from different studies.
On Mon, Jun 21, 2021 at 1:13 PM Jack Solomon <kj.jsolomon using gmail.com> wrote:
> Hello All,
> I have come across a couple of primary studies in my meta-analytic pool
> that have used independent samples of participants in them (e.g., high
> schoolers & middle schoolers).
> Question: I was wondering how exactly I should code these studies to
> account for their use of independent samples of participants?
> Should I create a new column ('sample') to distinguish between studies'
> samples (see below)? OR with just two such multi-sample studies, basically
> that is not worth it in which case the question becomes:
> Should I code each independent sample as an independent study (which
> ignores the correlation between true effect sizes from samples under each
> study)? see below.
> Thanks, Jack
> ***consider 'sampel' in coding:
> study sample es
> 1 1 .1
> 1 1 .2
> 1 2 .3
> 1 2 .4
> 2 1 .5
> 2 2 .6
> 3 1 .7
> ***ignore 'sample' in coding:
> study es
> 1 .1
> 1 .2
> 2 .3
> 2 .4
> 3 .5
> 4 .6
> 5 .7
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