That way we Bayesian meta-analysts can help each other with this fascinating subject, wherever we are in the world. We are keen to include news of new developments, publications, events, etc, so please let us know if you have any news you think we should feature.

Part III: "Specific Problems" explores methods including network meta-analysis, individual participant data integration, publication bias modeling, and emerging techniques such as multivariate approaches and population-adjusted indirect comparisons.

Part II: "Getting Inputs and Crafting Outputs" addresses the practical challenges of extracting statistics from published literature, eliciting expert priors, and effectively communicating meta-analytic findings.

Part I: "The Fundamentals" establishes core statistical inference principles and Bayesian methodology, progressing through common effect and random effects meta-analysis frameworks.