Message-ID: <CAGSN_DVJypGxaSxyDFu1X2c=jTU3ENTLCEosvRGpJHTpDhOp0A@mail.gmail.com>
Date: 2019-12-12T14:34:26Z
From: Lior Abramson
Subject: [R-meta] A question regarding the 'metafor package' : Standardized regression coefficients as outcome measures
In-Reply-To: <6a8223b63bb74128bf4eb1bf96f57ac0@UM-MAIL3214.unimaas.nl>
Dear Wolfgang,
Thank you very much for the response.
You are right, I am looking at ACE-type models. However, the way I
extracted the genetic coefficients (h) was simply by looking at the
correlations of MZ and DZ twins in each study, and than using Falconer's
formula to extract the coefficient from these correlations (i.e., the
square root of 2*(rMZ-rDZ)). This was the only way to assure that the
summary effects do not depend on researchers' degrees of freedom and
statistical decisions, since many of the studies reported h after model
fitting .
Is there a way to extract the sampling variance in this case?
Alternatively, do you think it is reasonable to perform Fisher Z
transformation on the coefficients and then use the sampling variance
formula that considers only the N of the total sample?
Thank you again,
Lior
On Wed, Dec 11, 2019 at 11:57 PM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
> Dear Lior,
>
> 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().
>
> Best,
> Wolfgang
>
> -----Original Message-----
> From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces at r-project.org] On Behalf Of Lior Abramson
> Sent: Wednesday, 11 December, 2019 17:11
> To: r-sig-meta-analysis at 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,
> Lior
>
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