[R-meta] Meta-analysis of prevalence data: back-transformation and polytomous data
j@kub@ru@zkow@k| @end|ng |rom gumed@edu@p|
Wed Feb 23 12:06:17 CET 2022
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
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.
Jakub Ruszkowski, M.D.
Department of Physiopathology | Department of Nephrology, Transplantology and
Medical University of Gdańsk
More information about the R-sig-meta-analysis