Dear community,
I (or, more precisely, my collaborator) am helping with one meta-analysis with dependent effect sizes. We used a multilevel model with effect size ID, study ID, and species ID as random effects. We also used the RVE to calculate the robust error. I have two questions.
1.
The test of model coefficient based on RVE indicates a significant effect (p < 0.05), while the test based on model-based error (we call it naive/original error) shows a non-significant effect (p < 0.05). I used `robust` in `metafor`, with `CR1` correction (`clubsandwich` is not working in my case; see below?) . Sorry, I do not have the raw data so there is no reproducible example.
2.
How to calculate the robust error for models with non-nested random-effects structure? This issue has troubled me for a long time. Precisely, in my case, because effect size ID is nested within the study ID, so it is easy to calculate robust error (either using ? ?`robust` or ?`clubsandwich` ?). However, I still have species ID as the random effect (it is a kind of crossed random effect). In such a case `clubsandwich` is not working. `robust` is still working, but we only can use `CR1` correction.
Regards,
Yefeng