[R-meta] Back-transforming Fisher's r-to-z transformed correlation coefficient to r in funnel and forest plots results

Mon, Aug 21, 2023 12:58 AM

Dear John,

That would be one way of doing this, but then your analysis uses raw correlation coefficients. The forest() and funnel() functions have the 'atransf' arguments for back-transforming the x-axes.

Best,
Wolfgang

________________________________
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> on behalf
of John Mahas via R-sig-meta-analysis <r-sig-meta-analysis at r-project.org>
Sent: Wednesday, August 16, 2023 2:36 PM
To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-
project.org>
Cc: John Mahas <jwm0055 at auburn.edu>
Subject: [EXT] [R-meta] Back-transforming Fisher's r-to-z transformed correlation
coefficient to r in funnel and forest plots results

Hi All,

I performed a random-effect summary meta-analysis where study was used as a
random effect. Here, I used the rma.mv function using the Fisher's r-to-z
transformed correlation coefficient effect size (see code below).

CODE: results=rma.mv(yi,vi,data=datum,method="REML",random=~1|Study)

I can use then use the below code to create funnel and forest plots.

CODE: forest(results)
CODE: funnel(results)

The x axis for these plots would be my effect size (Fisher's r-to-z transformed
correlation coefficient). My question is, what must I do in order to back
transform my Fisher's r-to-z transformed correlation coefficient here in the
plots so that they are displayed as the Pearson's correlation coefficient (r).

Thanks,

John

[R-meta] Back-transforming Fisher's r-to-z transformed correlation coefficient to r in funnel and forest plots results

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