Bayesian Meta-Analysis : A Practical Introduction (Hardcover)

1. A statistical inference primer. 2. What is Bayesian statistics?. 3. Common effect meta-analysis. 4. Random effects meta-analysis and heterogeneity. 5. How to extract statistics from published papers. 6. Eliciting priors. 7. Writing up your meta-analysis. 8. Using arm- and time-based statistics. 9. Network meta-analysis. 10. Individual participant data. 11. Unreported statistics. 12. Living systematic reviews and Bayesian updating. 13. Publication bias. 14. Multiple statistics. 15. Multiple outcomes or study designs. 16. Informing policy and economic evaluation. 17. Emerging topics in Bayesian meta-analysis.