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

[John Mahas]

Hi All,

Please disregard my previous message - I figured it out. I isolated my generated yi and vi from my dataset and ran the following code.

#load z results
datum=read.csv(file.choose())
Z=datum

#transform z to r
Z_r=transf.ztor(Z)

Once this was done, I added this data to a csv to perform my analyses with the back-transformed r instead of my original Fisher's r-to-z transformed correlation coefficient



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

CAUTION: Email Originated Outside of Auburn.

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

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