[R-meta] Assessing heterogeneity with random-effects models

[Célia Sofia Moreira]

Dear all,

I'm performing a meta-analysis with metafor package and I have some basic
questions regarding the assessment of residual heterogeneity.

For random-effects univariate models (using rma function), residual
heterogeneity can be assessed with
- QE and QEp,
- I2 (total heterogeneity / total variability),
- H2 (total variability / sampling variability),
- tau2 (estimated amount of total heterogeneity).

For random-effects multilevel models (using rma.mv function), heterogeneity
can be assessed with
- QE and QEp,
- tau2
- sigma2.
In this case:
1) Is tau2 still being the estimated amount of total heterogeneity?
2) May I define sigma2_1 as the variability/variance of the 3-level model
at level 1?
3) Why I2 and H2 is not defined?
4) In all cases I performed, I got tau2=0. Is this a coincidence or does
this fact always happen?
5) Is there any other useful way  to assess heterogeneity in the multilevel
case?

Kind regards,
celia

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