BookMathias Harrer [and three others].
Summary: "This book serves as an accessible introduction into how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced, but highly relevant topics such as network meta-analysis, multi-/three-level meta-analyses, Bayesian meta-analysis approaches, SEM meta-analysis are also covered. A companion R package, dmetar, is introduced in the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide"-- Provided by publisher.
Contents: <br/
>1. Introduction.
2. Discovering R.
3. Effect Sizes.
4. Pooling Effect Sizes.
5. Between-Study Heterogeneity.
6. Forest Plots.
7. Subgroup Analyses.
8. Meta-Regression.
9. Publication Bias.
10. "Multilevel" Meta-Analysis.
11. Structural Equation Modeling Meta-Analysis.
12. Network Meta-Analysis.
13. Bayesian Meta-Analysis.
14. Power Analysis.
15. Risk of Bias Plots.
16. Reporting & Reproducibility.
17. Effect Size Calculation & Conversion.