[R-meta] Why total variation differs in two rma.mv models?
Viechtbauer, Wolfgang (NP)
wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Tue Jan 10 08:12:26 CET 2023
If the moderators account for (at least some of the) heterogeneity, then this is exactly what should happen (in m2, the variance components reflect heterogeneity not accounted for by the moderators).
>I have fit an intercept-only model like:
>m1 = rma.mv(yi ~ 1, V=V, random = ~1|study/effect)
>And then the same model with some moderators:
>m2 = rma.mv(yi ~ mod1*mod2 + X1 + X2, V=V, random = ~1|study/effect)
>When I compare the **total variation** (sum of the variance components)
>across the two models, "m1" has a much larger estimate than "m2".
>I wonder how that could be when both models use the same set of effect
>Thank you so much!
More information about the R-sig-meta-analysis