[R-meta] Follow-up: Interpreting variance components in rma.mv

[Yuhang Hu]

Hello All,

I wanted to ask a follow-up on my previous post (
https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2022-August/004139.html).

I'm currently fitting the following model (cat_mod = categorical mod):

rma.mv(yi ~ 0 + cat_mod * time + covariates, random = ~ 1 | study/effect)

with a total heterogeneity in sd unit = 0.699.

"cat_mod" levels' means at time0 are very different from each other. As
such, I have computed the gains (i.e., time1 - time0) for each level of
cat_mod:

Gain (cat1) = 0.27
Gain (cat2) = 0.33

***Question: I wonder whether I can say the following or not?***

"The probability that a gain from time0 to time1 in cat1 is 0 or larger is:
pnorm(0,.27, .699, lower.tail = FALSE)
> [1] 0.650

"The probability that a gain from time0 to time1 in cat2 is 0 or larger is:
pnorm(0,.33, .699, lower.tail = FALSE)
> [1] 0.68

Thank you for your attention.

Yuhang Hu

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