Dear Stan community,
ELI5 (Explain like I’m 5) your general approach / how you would go about setting up for and performing a random-effects Bayesian meta-analysis and meta-regression (starting with brms)?
- Aggregate data,
- Standardized mean difference effect/variance estimate (e.g., Hedges’ g),
- Weakly informative heterogeneity prior (sensitivity analysis with empirical/uninformative priors),
- 2-3 small studies (n=10-40) and 3-5 medium studies (n=50-80).
- A forest plot with the pooled estimate (95% credible/prediction intervals),
- A meta-regression, 3 sets of models (i.e., patient characteristics, intervention characteristics, general study characteristics) with multiple (4-5) categorical and continuous potential effect modifiers in each model,
- Any (non-frequentist) test for publication bias or small-study effects.
I am a keen but complete novice with Bayesian modelling/computation, but hopefully after some surveying here I can get a better idea on how to narrow down my personal learning objectives. Thank you in advance for your advice.