As for the model to use:
In general, you want to use: ~1|studyID/effectsizeID
Using list(~1|effectsizeID, ~1|studyID) may be correct if effectsizeID is unique for every row.
This is essentially a question of 'explicit' versus 'implict' nesting. See also:
https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2018-July/000896.html
Best,
Wolfgang
-----Original Message-----
From: Rafael Rios [mailto:biorafaelrm at gmail.com]
Sent: Sunday, 04 November, 2018 0:32
To: Viechtbauer, Wolfgang (SP)
Cc: Michael Dewey; r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Questions about Omnibus tests
Dear Wolfgang,
Could you please help me again with new questions?
Should I build model1 rather than model2 to control for the dependency among studyID and effectsizeID??
model1=rma.mv(zf, vzf, mods=~mate_choice, random=list(~1|studyID/effectsizeID, ~1|species1), data = h_mc)
model2=rma.mv(zf, vzf, mods=~mate_choice, random=list(~1|effectsizeID, ~1|studyID, ~1|species1), data = h_mc)
I used your script to calculate I? and found a high heterogeneity in my model (86.63%).?
#I?: http://www.metafor-project.org/doku.php/tips:i2_multilevel_multivariate
W <- diag(1/h_mc$vzf)
X <- model.matrix(model1)
P <- W - W %*% X %*% solve(t(X) %*% W %*% X) %*% t(X) %*% W
100 * sum(meta$sigma2) / (sum(meta$sigma2) + (meta$k-meta$p)/sum(diag(P)))
Do you have suggestions on how to handle with high heterogeneity among effect sizes? How may I conduct sensitivity tests in a multilevel meta-analysis using metafor? I identified (using a funnel plot) and removed outliers to reduce the heterogeneity and redo the model. Is this approach suitable to evaluate potential bias in results? Or are there better alternatives?
Best wishes,
Rafael.
__________________________________________________________
Dr. Rafael Rios Moura
scientia amabilis
Behavioral Ecologist,?PhD
Postdoctoral Researcher
Universidade Estadual de Campinas (UNICAMP)
Campinas, S?o Paulo, Brazil
Curr?culo Lattes:?http://lattes.cnpq.br/4264357546465157
ORCID:?http://orcid.org/0000-0002-7911-4734
Research Gate:?https://www.researchgate.net/profile/Rafael_Rios_Moura2