[R-meta] Quantify the amount of residual heterogeneity using the QE value

[max doering]

Dear R-sig-meta-analysis community,

I am currently conducting a meta analysis using metafor.
For this, I want to compare a model with no moderators and one with
all moderators:

no_mods = rma.mv(yi, vi, random = ~1|DOI/individual_level, data = data)
all_mods = rma.mv(yi, vi, random = ~1|DOI/individual_level, mods =
~mod1 + mod2 + ..., data = data)

I would like to answer the question, how much of the residual
heterogeneity in the no_mod model can be explained by adding all the
moderators. In the end, I want to say something like "the moderators
account for X% of the residual heterogeneity".

Unfortunately, the model does not calculate a tau^2 value (at least it
is 0 in both models), so my thought was that I could maybe use the QE
value for a calculation like:

(1 - ((all_mods $QE/all_mods $QEdf)/(no_mods $QE/no_mods $QEdf)))*100

basically calculating the change of the QE value in percent with
respect to their dfs.

In summary, my questions are:
1) Can I use the QE value to quantify the amount of residual
heterogeneity accounted for by all moderators?
2) If the answer is no or if there is a simpler solution, what options
are there?

Thank you and best regards,
Max