[R-meta] Advice on running a multilevel meta-analysis

[Matheus Gallas Lopes]

Hi everyone,

We're conducting a systematic review and meta-analysis on the effects of 
NMDA receptor antagonists on social behavior in animals (PROSPERO: 
CRD42023402129). Our goal is to assess how these antagonists affect 
social behavior and whether antipsychotics can counteract these effects.

Since this is our first time running a multilevel meta-analysis, we want 
to ensure we properly account for dependencies within experiments and 
within studies. We have a few methodological questions:

Shared control groups within experiments: Some studies report multiple 
treatment groups (e.g., different doses of an NMDA antagonist) that 
share the same control group. In past reviews, we have split the control 
sample size across comparisons, but we know this approach has 
limitations. What is the best way to properly account for shared 
controls in a multilevel model?

Multiple correlated outcomes per experiment: As per our protocol, our 
goal was to extract all relevant outcomes measured in the same animals 
related to social behavior and combine them, rather than selecting just 
one. Many studies report multiple measures (e.g., time spent interacting 
and number of interactions), and we want to properly aggregate them in 
our multilevel meta-analysis to avoid redundancy while preserving 
information. What would be the best approach for this?

If anyone has experience handling these dependencies or can suggest 
useful references, we'd really appreciate your insights!

Thanks in advance!

Best,
Matheus

-- 
Matheus Gallas-Lopes
PhD student in Pharmacology and Therapeutics
Laboratório de Neurobiologia e Psicofarmacologia Experimental 
(PsychoLab)
Universidade Federal do Rio Grande do Sul (UFRGS)
Currículo Lattes: https://goo.gl/iwHPAM
ORCID: https://goo.gl/Tp2S6w
ResearchGate: https://goo.gl/lja63C

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