[R-meta] R2 in rma.mv() with missing pre-tests

[Zhouhan Jin]

Hello all,

I have ~40% of my longitudinal studies missing pre-tests. As a result, I can't compute the gain effects (ex. SMCCs) directly from these studies or if I do, I will lose them.

Out of necessity, I meta-analyzed the effects at each time (i.e., SMDs) using the best empirically fitting model:

MODEL <- rma.mv<http://rma.mv/>(yi ~ time * mod, V = V, random = ~1|study/effect)

and then computed the gains posthoc using the emmeans package:

gain <- contrast(emmprep(MODEL), list(c(1,-1,0,0))) and similar for various categories of `mod`.

Question: Am I right that R2 from this MODEL can't tell us the extent `mod` explains the heterogeneity in gains?

If not, what alternatives do I have to get an insight into the heterogeneity in the gains explained by `mod`?

Thanks in advance!

Best wishes,

Zhouhan


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