[R-meta] Using variance components with effect size transformation
yh342 @end|ng |rom n@u@edu
Wed Dec 14 04:28:55 CET 2022
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 |
I wonder to calculate probabilities from the distribution of effects as
explained in this post (
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?
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