[R-meta] Meta-analysis of prevalence data: back-transformation and polytomous data

This paper argues for modelling the within-study variance directly as binomial (https://pubmed.ncbi.nlm.nih.gov/18083461/)  and provides a SAS program to do so. I think R can do it too with glmer, though I don't have a handy program. But see https://journals.lww.com/epidem/Fulltext/2020/09000/Meta_analysis_of_Proportions_Using_Generalized.16.aspx , specifically the appendices for R code. I haven't come across a multinomial version that doesn't use WinBUGS.

Francesca

-----Original Message-----
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> On Behalf Of R?ver, Christian
Sent: 24 February 2022 08:43
To: jakub.ruszkowski at gumed.edu.pl; r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Meta-analysis of prevalence data: back-transformation and polytomous data

This email was sent to you by someone outside the University.
You should only click on links or attachments if you are certain that the email is genuine and the content is safe.

Dear Jakub,

I think Schwarzer et al. (2019; https://doi.org/10.1002/jrsm.1348) have a valid point, and that the double arcsine transform is not really suitable for meta-analysis purposes. The approach by Barendregt et al.
(2013; https://doi.org/10.1136/jech-2013-203104) seems to me more like a kind of workaround, and I am not sure whether it will actually work generally, or would only "fix" the issue (or at least won't fail
immediately) in some cases.

I guess a quick and simple solution might be to go for the ("simple") arcsine transformation instead, or otherwise check out one of the more appropriate alternative approaches that were pointed out by Schwarzer et al. (2019).

Cheers,

Christian

Dear Community,

I am trying to do a meta-analysis of prevalence according to the
recommendations arising from the current literature. I have two
problems that I cannot handle on my own.

1. I found that there are controversies about a back-transformation
method for the Freeman-Tukey double arcsine transformation (Schwarzer
et al., doi:
10.1002/jrsm.1348). However, there is a probable resolution that
incorporates inverse variance instead of harmonic mean (Barendregt-Doi
implementation, clearly explained in Supplementary Materials in doi:
10.1111/jebm.12445;
older version introducing it: 10.1136/jech-2013-203104).
Unfortunately, I am
not proficient in programming, so I am not sure how to implement this
solution on my own. Is there an R implementation of Barendregt-Doi
back-transformation available or is it possible to add this method to
the metafor?

2. Are there any available examples of R code to meta-analyze
ordinal/multinomial prevalence data (e.g., mild, moderate, severe
severity)?
I found one method implemented in MetaXL that used double arcsine
transformation (mentioned earlier doi: 10.1136/jech-2013-203104), and
one Bayesian method using the Dirichlet-multinomial model (doi:
10.1080/03610918.2021.1887229). Unfortunately, the R code is not
supplemented with the latter article.


Kind regards

_______________________________________________
R-sig-meta-analysis mailing list
R-sig-meta-analysis at r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th? ann an Oilthigh Dh?n ?ideann, cl?raichte an Alba, ?ireamh cl?raidh SC005336.