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Meta-Analysis: A Structural Equation Modeling Approach

Book Description

Presents a novel approach to conducting meta-analysis using structural equation modeling.

Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment.

Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included.

This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Preface
    1. Purpose of This Book
    2. Level and Prerequisites
  6. Acknowledgments
  7. List of abbreviations
  8. List of figures
  9. List of tables
  10. Chapter 1: Introduction
    1. 1.1 What is meta-analysis?
    2. 1.2 What is structural equation modeling?
    3. 1.3 Reasons for writing a book on meta-analysis and structural equation modeling
    4. 1.4 Outline of the following chapters
    5. 1.5 Concluding remarks and further readings
    6. References
  11. Chapter 2: Brief review of structural equation modeling
    1. 2.1 Introduction
    2. 2.2 Model specification
    3. 2.3 Common structural equation models
    4. 2.4 Estimation methods, test statistics, and goodness-of-fit indices
    5. 2.5 Extensions on structural equation modeling
    6. 2.6 Concluding remarks and further readings
    7. References
  12. Chapter 3: Computing effect sizes for meta-analysis
    1. 3.1 Introduction
    2. 3.2 Effect sizes for univariate meta-analysis
    3. 3.3 Effect sizes for multivariate meta-analysis
    4. 3.4 General approach to estimating the sampling variances and covariances
    5. 3.5 Illustrations Using <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family:sans-serif">R</span>
    6. 3.6 Concluding remarks and further readings
    7. References
  13. Chapter 4: Univariate meta-analysis
    1. 4.1 Introduction
    2. 4.2 Fixed-effects model
    3. 4.3 Random-effects model
    4. 4.4 Comparisons between the fixed- and the random-effects models
    5. 4.5 Mixed-effects model
    6. 4.6 Structural equation modeling approach
    7. 4.7 Illustrations using R
    8. 4.8 Concluding remarks and further readings
    9. References
  14. Chapter 5: Multivariate meta-analysis
    1. 5.1 Introduction
    2. 5.2 Fixed-effects model
    3. 5.3 Random-effects model
    4. 5.4 Mixed-effects model
    5. 5.5 Structural equation modeling approach
    6. 5.6 Extensions: mediation and moderation models on the effect sizes
    7. 5.7 Illustrations using <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family:sans-serif">R</span>
    8. 5.8 Concluding remarks and further readings
    9. References
  15. Chapter 6: Three-level meta-analysis
    1. 6.1 Introduction
    2. 6.2 Three-level model
    3. 6.3 Structural equation modeling approach
    4. 6.4 Relationship between the multivariate and the three-level meta-analyses
    5. 6.5 Illustrations using <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family:sans-serif">R</span>
    6. 6.6 Concluding remarks and further readings
    7. References
  16. Chapter 7: Meta-analytic structural equation modeling
    1. 7.1 Introduction
    2. 7.2 Conventional approaches
    3. 7.3 Two-stage structural equation modeling: fixed-effects models
    4. 7.4 Two-stage structural equation modeling: random-effects models
    5. 7.5 Related issues
    6. 7.6 Illustrations using <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family:sans-serif">R</span>
    7. 7.7 Concluding remarks and further readings
    8. References
  17. Chapter 8: Advanced topics in SEM-based meta-analysis
    1. 8.1 Restricted (or residual) maximum likelihood estimation
    2. 8.2 Missing values in the moderators
    3. 8.3 Illustrations using <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family:sans-serif">R</span>
    4. 8.4 Concluding remarks and further readings
    5. References
  18. Chapter 9: Conducting meta-analysis with Mplus
    1. 9.1 Introduction
    2. 9.2 Univariate meta-analysis
    3. 9.3 Multivariate meta-analysis
    4. 9.4 Three-level meta-analysis
    5. 9.5 Concluding remarks and further readings
    6. References
  19. Appendix A: A brief introduction to R, OpenMx, and metaSEM packages
    1. A.1 <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family:sans-serif">R</span>
    2. A.2 <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family: monospace;">OpenMx</span>
    3. A.3 <span xmlns="http://www.w3.org/1999/xhtml" xmlns:epub="http://www.idpf.org/2007/ops" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ibooks="http://vocabulary.itunes.apple.com/rdf/ibooks/vocabulary-extensions-1.0" style="font-family: monospace;">metaSEM</span>
    4. References
  20. Index
  21. End User License Agreement