[R-meta] Guidance regarding balance in fixed- and random-effects

[Luke Martinez]

Dear Experts,

Forgive my modeling question. But in answering RQs like: what is the
overall effect of X, I often fit an intercept-only model with several
nested levels, like:

(1) rma.mv(yi, vi, random = ~ 1 | lab / study / outcome / time / rowID)

In the above model, all levels reveal heterogeneity in them.

But then in answering other RQs, when I add a couple of moderators,
some of the levels (e.g., "outcome" AND "lab") return ZERO
heterogeneity making me fit a simpler model, like:

(2) rma.mv(yi ~ mod1*mod2, vi, random = ~ 1 | study / time / rowID)

Question: When this happens, does this mean that I should go back and
refit model (1) without "outcome" AND "lab" to uniform the random
specification of model (1) and model (2)?

OR, model (1) is appropriate for RQ1 and model (2) is appropriate for RQ2s?

Thank you for your perspectives,
Luke