The problem | Estimates and standard errors | Computing effect sizes | The random effects model | Parameter estimation in the random effects model | The technical side | Prior & posterior | Prior information for the effect parameter $\mu$ | Prior information for the heterogeneity parameter $\tau$ | Inference | The practical side | A simple example | More detailed analysis | References

Introduction | Random-effects meta-analysis | Using the bayesmeta package | Summary | Unit information priors for binary outcomes | Conservatism of the uniform heterogeneity prior | Marginal likelihood derivation | Mixture implementation details | Calibration check