[R-meta] (no subject)

Garance Delagneau g@r@nce@de|@gne@u @end|ng |rom mon@@h@edu
Fri Jun 18 02:52:33 CEST 2021

Hi everyone,

I'm a bit stuck and would really appreciate any help on my issue.

I'm doing a meta analysis (using R). There are several instances where
authors reported multiple effect sizes (e.g., reported effect sizes for
different timepoints) that I need to combine. I've tried to aggregate my
multiple effect sizes using both the metafor package and the formula in
Borenstein's manual (chapter 24 - using the mean effect size weighted
according to the sample size and the formula attached to this email to
calculate the variance). While variances using these two techniques are
quite similar, the computed effect sizes are very different.

*My questions are: *

   - Why/how does yi (combined effect size) change quite a lot based on the
   value of rho when using the metafor package?
   - Are the yi's that we get when using the metafor package correct?
   - The combined effect sizes using these methods are quite different from
   using the mean effect size. Is it correct to use the Metafor package?

This is the example I've been working on

Authors N Time corr
Polanska  2017 337 2 -0.09
Polanska  2017 219 1 -0.02
Using R's metafor package, I obtained a combined effect size of  -0.0718.
Using Borenstein's method, I obtain an effect size of -0.06255.

Note. I often have fewer than 10 articles to combine in my meta-analyses
(it varies between 3 and 10). I expect heterogeneity to be moderate to high
in most of my analyses.

Thank you very much,
PhD Student (Clinical Neuropsychology)

M: 0452 323 762
E: g <elinor.fraser using monash.edu>arance.delagneau using monash.edu

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