Doing meta-analysis with R: a hands-on guide
Material type:
TextPublication details: Boca Raton CRC Press 2022 Description: xxvi, 474 pISBN: 9780367610074Subject(s): Meta-analysis | R (Computer program language)DDC classification: 610.727 Summary: Book Description
Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and 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 and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide.
The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible.
Features
• Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises
• Describes statistical concepts clearly and concisely before applying them in R
• Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Book
|
Indian Institute of Management LRC General Stacks | IT & Decisions Sciences | 610.727 HAR (Browse shelf(Opens below)) | 1 | Available | 003866 |
Table of Contents
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.
Book Description
Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and 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 and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide.
The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible.
Features
• Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises
• Describes statistical concepts clearly and concisely before applying them in R
• Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book
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