[R-meta] Studies with independent samples of participants
Hi Jack, 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. James
On Mon, Jun 21, 2021 at 1:13 PM Jack Solomon <kj.jsolomon at 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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