[R-meta] multilevel meta-analysis using metafor

Wolfgang Viechtbauer wolfgang.viechtbauer at maastrichtuniversity.nl
Wed Aug 30 13:07:29 CEST 2017

Yes, that would be appropriate/sufficient, assuming there is no overlap 
in the subjects used to compute the various correlation coefficients 
within the same study. But I suspect that may not be the case. If so, 
the covariances of the correlations are not 0 (as is assumed by the 
model below).


On 08/30/2017 11:54 AM, brauldeq wrote:
Dear fellow researchers,

I am currently conducting a meta-analysis for my master's thesis in
psychology. For that matter, I stumbled upon your metafor package which
has been very helpful for me!

However, I have some trouble implementing the right R code for my
analysis. I am running a meta-analysis on the relationship between
self-efficacy and scholastic achievement (using correlation
coefficients). It will be analyzed using multilevel analysis using a
random-effects model because I have several articles with multiple
effect sizes which I want to include individually controlling for their
dependency. Therefore, I have (dependant) effect sizes that are nested
within (independent) samples.
Each independent sample is coding with an unique number in the variable
"sample_nr" and each dependant effect size for a certain sample is coded
with an unique number in "effect_nr". So, a sample with multiple effect
sizes would be coded with an identical "sample_nr" and different
"effect_nr" for each effect size. My R code is as follows:

rma.mv(yi, vi, random = ~ 1 | sample_nr/effect_nr, data = se_ach)

Is this the right code for my purpose?

Thank you for your advice.

Best regards,
Denise Braul

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