Preface; Contents; 1 Introduction to Meta-Analysis and Structural Equation Modeling; Abstract ; 1.1 What Is Meta-Analysis?; 1.1.1 Issues in Meta-Analysis; 1.1.2 Statistical Analysis; 1.2 What Is SEM?; 1.2.1 Path Analysis; 1.2.2 Model Fit; 1.2.3 Factor Analysis; 1.3 Why Should You Combine SEM and MA?; References; 2 Methods for Meta-Analytic Structural Equation Modeling; Abstract ; 2.1 Introduction; 2.2 Univariate Methods; 2.3 Multivariate Methods; 2.3.1 The GLS Method; 2.3.2 Two Stage Structural Equation Modeling (TSSEM); References; 3 Heterogeneity; Abstract ; 3.1 Introduction

3.2 Testing the Significance of Heterogeneity3.3 The Size of the Heterogeneity; 3.4 Random Effects Analysis or Explaining Heterogeneity; 3.4.1 Random Effects MASEM; 3.4.2 Subgroup Analysis; References; 4 Issues in Meta-Analytic Structural Equation Modeling; Abstract ; 4.1 Software to Conduct MASEM; 4.2 Fit-Indices in TSSEM; 4.3 Missing Correlations in TSSEM; 4.4 The ML-Approach to MASEM; References; 5 Fitting a Path Model with the Two-Stage Approach; Abstract ; 5.1 Introduction; 5.2 Preparing the Data; 5.3 Fixed Effects Analysis; 5.4 Random Effects Analysis

5.5 Random Effects Subgroup AnalysisReferences; 6 Fitting a Factor Model with the Two-Stage Approach; Abstract ; 6.1 Introduction; 6.2 Preparing the Data; 6.3 Fixed Effects Analysis; 6.4 Random Effects Analysis; References; Appendix A Model Implied Covariance Matrix of the Example Path Model; Appendix B Fitting a Path Model to a Covariance Matrix with OpenMx; Appendix C Model Implied Covariance Matrix of the Example Factor Model; Appendix D Fitting a Factor Model to a Covariance Matrix with OpenMx