[R-meta] Model selection using glmulti & MuMln with multilevel (rma.mv) models
Viechtbauer, Wolfgang (SP)
wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Sat Mar 7 12:53:08 CET 2020
Since you mentioned multilevel, I take it you want to use rma.mv() then?
The example here would be easy to adapt:
Basically, it would just require something like:
rma.glmulti <- function(formula, data, ...)
rma.mv(formula, vi, random = ~ 1 | study / effect, data=data, method="ML", ...)
If you are also interested in interactions, you should read the "Models with Interactions" section. The number of models quickly explodes once one also wants to consider interactions.
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Mia Daucourt
Sent: Friday, 06 March, 2020 16:37
To: r-sig-meta-analysis using r-project.org
Subject: [R-meta] Model selection using glmulti & MuMln with multilevel (rma.mv) models
I am interested in using the glmulti or MuMln package to choose the best combination of moderators for a multi-level model with random effects for study and effect size included. I am also interested in examining interactions between moderators. I need your help, please! Do you have any advice on how to code this or any resources you can point me to?
Please let me know!
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