preface

Chapter 1: Background of Meta-Analysis
1.
Definition of meta-analysis
2.
Background of the meta-analysis
3.
Integrated analysis of research results
4.
Evidence-Based Practice and Meta-Analysis
summation

Chapter 2: Steps of Meta-Analysis
1.
Research topic selection and research questions
2.
Literature search
3.
Study selection, quality assurance, and coding of individual studies
4.
data analysis
5.
Results Report
summation

Chapter 3: Basic Understanding of Meta-Analysis: Forest Plot
1.
effect size
2.
Statistical significance
3.
weight
4.
Average effect size
summation

Chapter 4 Effect Size
1.
Effect size meaning
2.
Effect size type
3.
Effect size interpretation
4.
Calculating effect size
summation

Chapter 5: Effect Size Analysis Using R
1.
Installing R and RStudio
2.
continuous data
3.
dichotomous data
4.
Correlation data
5.
Generalized effect size data
summation
Command Summary

Chapter 6: Analysis of Effect Sizes of Various Types and Multiple Outcomes
1.
Various types of effect size analysis
2.
Multiple outcome effect size analysis
summation
Command Summary

Chapter 7 Fixed-Effects Models and Random-Effects Models
1.
The meaning of fixed-effects models and random-effects models
2.
Differences between fixed-effects and random-effects models
3.
Application examples of fixed-effects and random-effects models
4.
Calculating the average effect size of fixed-effects and random-effects models using Excel
summation

Chapter 8 Heterogeneity of Effect Sizes
1.
The meaning of heterogeneity
2.
Heterogeneity statistics
summation

Chapter 9 Moderating Effect Analysis
1.
Meaning of moderating effect analysis
2.
meta-ANOVA
3.
meta-regression analysis
summation
Command Summary

Chapter 10: Analysis of Publication Errors
1.
Meaning of publication error
2.
Analysis process of publication errors
summation
Command Summary

Chapter 11: Cumulative Meta-Analysis and Sensitivity Analysis
1.
Cumulative meta-analysis
2.
Sensitivity analysis
summation
Command Summary

Chapter 12: Quality Assurance of Individual Studies
1.
Quality assurance of traditional individual studies
2.
Quality assurance of individual studies using 'robvis'
3.
Quality assurance of individual studies using 'dmetar'
summation
Command Summary

Chapter 13: Reporting the Results of Meta-Analysis
1.
title
2.
Structured Summary
3.
introduction
4.
Research methods
5.
Analysis results
6.
Discussion and Conclusion
7.
References
8.
supplement
summation

supplement
References
Search

Compared to the first edition, this book adds three chapters—Chapters 2, 6, and 12—and strives to supplement the existing chapters with as much content as possible.
At the end of each chapter, the contents are briefly summarized and the R code used for the analysis is organized.
Specifically, Chapter 1 describes the background and characteristics of meta-analysis so that readers can understand them, and Chapter 2 describes the main contents of each stage of meta-analysis.
Chapter 3 provides a basic understanding of meta-analysis through forest plots. Chapter 4 provides a detailed explanation of the meaning and calculation method of effect size, and Chapter 5 describes effect size analysis using R.
Chapter 6 then presents methods for analyzing various types of effect sizes and multiple outcome effect sizes, and Chapter 7 explains the fixed-effects model and random-effects model for calculating the average effect size.
Chapters 8 and 9 explain the concept of effect size heterogeneity and cover meta-ANOVA and meta-regression analysis as moderating effect analyses that can explain heterogeneity.
Chapters 10 and 11 cover publication error analysis, cumulative meta-analysis, and sensitivity analysis to verify errors in the overall results that cannot be overlooked in meta-analysis.
Chapter 12 covers how to use a recently developed R package, rather than RevMan, to verify the quality of individual studies required in meta-analysis studies.
Finally, Chapter 13 presents specific details for reporting the results of meta-analysis, along with examples.
And in the appendix, we introduce various methods for creating forest plots, formulas for calculating effect size and heterogeneity statistics, professional societies related to meta-analysis, and meta-analysis software programs.