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Contents I. FUNDAMENTAL CONCEPTS 1. Introduction 1.1 Plan of the Book 1.2 Notation 1.3 Computer Programs for SEM 1.4 Statistical Journeys 1.5 Family Values 1.6 Extend Latent Variable Families 1.7 Family History 1.8 Internet Resources 1.9 Summary 2. Basic Statistical Concepts: I. Correlation and Regression 2.1 Standardized and Unstandardized Variables 2.2 Bivariate Correlation and Regression 2.3 Partial Correlation 2.4 Multiple Correlation and Regression 2.5 Statistical Tests 2.6 Bootstrapping 2.7 Summary 2.8 Recommended Readings 3. Basic Statistical Concepts: II. Data Preparation and Screening 3.1 Data Preparation 3.2 Data Screening 3.3 Score Reliability and Validity 3.4 Summary 3.5 Recommended Readings 4. Core SEM Techniques and Software 4.1 Steps of SEM 4.2 Path Analysis: A Structural Model of Illness Factors 4.3 Confirmatory Factor Analysis: A Measurement Model of Arousal 4.4 A Structural Regression Model of Family Risk and Child Adjustment 4.5 Extensions 4.6 SEM Computer Programs 4.7 Summary 4.8 Recommended Readings II. CORE TECHNIQUES 5. Introduction to Path Analysis 5.1 Correlation and Causation 5.2 Specification of Path Models 5.3 Types of Path Models 5.4 Principles of Identification 5.5 Sample Size 5.6 Overview of Estimation Options 5.7 Maximum Likelihood Estimation 5.8 Other Issues 5.9 Summary 5.10 Recommended Readings Appendix 5.A Recommendations for Start Values Appendix 5.B Effect Size Interpretation of Standardized Path Coefficients 6. Details of Path Analysis 6.1 Detailed Analysis of a Recursive Model of Illness Factors 6.2 Assessing Model Fit 6.3 Testing Hierarchical Models 6.4 Comparing Nonhierarchical Models 6.5 Equivalent Models 6.6 Power Analysis 6.7 Other Estimation Options 6.8 Summary 6.9 Recommended Readings Appendix 6.A Statistical Tests for Indirect Effects in Recursive Path Models Appendix 6.B Amos Basic Syntax Appendix 6.C Estimation of Recursive Path Models with Multiple Regression 7. Measurement Models and Confirmatory Factor Analysis 7.1 Specification of CFA Models 7.2 Identification of CFA Models 7.3 Naming and Reification Fallacies 7.4 Estimation of CFA Models 7.5 Testing CFA Models 7.6 Equivalent CFA Models 7.7 Analyzing Indicators with Nonnormal Distributions 7.8 Special Types of CFA Models 7.9 Other Issues 7.10 Summary 7.11 Recommended Readings Appendix 7.A Recommendations for Start Values Appendix 7.B CALIS Syntax 8. Models with Structural and Measurement Components 8.1 Characteristics of SR Models 8.2 Analysis of SR Models 8.3 Estimation of SR Models 8.4 Detailed Example 8.5 Other Issues 8.6 Summary 8.7 Recommended Readings Appendix 8.A SEPATH Syntax III. ADVANCED TECHNIQUES, AVOIDING MISTAKES 9. Nonrecursive Structural Models 9.1 Specification of Nonrecursive Models 9.2 Identification of Nonrecursive Models 9.3 Estimation of Nonrecursive Models 9.4 Examples 9.5 Summary 9.6 Recommended Readings Appendix 9.A EQS Syntax 10. Mean Structures and Latent Growth Models 10.1 Introduction to Mean Structures 10.2 Identification of Mean Structures 10.3 Estimation of Mean Structures 10.4 Structured Means in Measurement Models 10.5 Latent Growth Models 10.6 Extensions 10.7 Summary 10.8 Recommended Readings Appendix 10.A Mplus Syntax 11. Multiple-Sample SEM 11.1 Rationale of Multiple-Sample SEM 11.2 Multiple-Sample Path Analysis 11.3 Multiple-Sample CFA 11.4 Extensions 11.5 MIMIC Models as an Alternative to Multiple-Sample Analysis 11.6 Summary 11.7 Recommended Readings Appendix 11.A LISREL SIMPLIS Syntax 12. How to Fool Yourself with SEM 12.1 Tripping at the Starting Line: Specification 12.2 Improper Care and Feeding: Data 12.3 Checking Critical Judgment at the Door: Analysis and Respecification 12.4 The Garden Path: Interpretation 12.5 Summary 12.6 Recommended Readings 13. Other Horizons 13.1 Interaction and Curvilinear Effects 13.2 Multilevel Structural Equation Models 13.3 Summary 13.4 Recommended Readings References Index
Library of Congress Subject Headings for this publication:
Multivariate analysis.
Social sciences -- Statistical methods -- Data processing.
Statistics -- Mathematical models.