[R-meta] A question regarding the 'metafor package' : Standardized regression coefficients as outcome measures
Viechtbauer, Wolfgang (SP)
wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Wed Dec 11 22:57:14 CET 2019
Sounds like you are running ACE-type models. In any case, I would just meta-analyze the coefficients directly, assuming you can extract a standard error for the coefficient from whatever software you are using to fit those models. Just square the standard error and you have the sampling variance. Then feed the coefficients and corresponding sampling variances to rma().
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Lior Abramson
Sent: Wednesday, 11 December, 2019 17:11
To: r-sig-meta-analysis using r-project.org
Subject: [R-meta] A question regarding the 'metafor package' : Standardized regression coefficients as outcome measures
Dear list members,
I am conducting a meta-analysis on the heritability of a trait as manifested in twin studies. Specifically, in twin studies, it is possible to derive the standardized regression coefficient of genes on a given trait (the genetic component is a latent variable that could not be directly observed). Thus, my outcome measure is a standardized regression coefficient. More specifically, it is a partial standardized regression coefficient since, in all the studies, there are exactly three variables that can affect the trait (genes, shared environment, and non-shared environment).
My question is: Is it possible to use partial standardized regression coefficient as an outcome measure in the 'metafor' package? If so, how can I do it? Is it reasonable to treat it like a correlation in terms of the syntax (i.e., to write measure="ZCOR" / measure ="COR")?
Thank you very much for your time and help,
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