[R-meta] Using variance components with effect size transformation

[Yuhang Hu]

Dear Meta Community,

I have a 3-level meta-regression model with a categorical moderator (3
levels) plus some covariates fit as:

m6 = rma.mv(r2z_transformed ~ 0 + cat_mod + covariates, random = ~ 1 |
study/effect)

I wonder to calculate probabilities from the distribution of effects as
explained in this post (
https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2022-August/004136.html),
whether I should use the transformed variance components (A) or
back-transformed variance components (B)?

A: confint.rma.mv(m6)   # transformed i.e., 'r2z'
B: confint.rma.mv(m6, transf = transf.ztor) # back-transformed i.e., 'z2r'

Currently, A and B give the same result, and I wonder why?

Thanks,
Yuhang

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