Longitudinal Structural Equation Modeling

Todd D. Little

• Publisher: The Guilford Press
• Year: 2023
• ISBN:
  9781462553150
• Edition: 2
• Topic: Social Sciences
• Subtopic: Social Science Research & Methodology
• Index: Social Sciences

This valuable book is now in a fully updated second edition that presents the latest developments in longitudinal structural equation modeling (SEM) and new chapters on missing data, the random intercepts cross-lagged panel model (RI-CLPM), longitudinal mixture modeling, and Bayesian SEM. Emphasizing a decision-making approach, leading methodologist Todd D. Little describes the steps of modeling a longitudinal change process. He explains the big picture and technical how-tos of using longitudinal confirmatory factor analysis, longitudinal panel models, and hybrid models for analyzing within-person change. User-friendly features include equation boxes that translate all the elements in every equation, tips on what does and doesn't work, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website provides data sets for the examples--including studies of bullying and victimization, adolescents' emotions, and healthy aging--along with syntax and output, chapter quizzes, and the book's figures. New to This Edition:
*Chapter on missing data, with a spotlight on planned missing data designs and the R-based package PcAux.
*Chapter on longitudinal mixture modeling, with Whitney Moore.
*Chapter on the random intercept cross-lagged panel model (RI-CLPM), with Danny Osborne.
*Chapter on Bayesian SEM, with Mauricio Garnier.
*Revised throughout with new developments and discussions, such as how to test models of experimental effects.

Table of contents

• Cover
• Front Endpaper: Greek Cheat Sheet
• Half Title Page
• Series Page
• Title Page
• Copyright
• Foreword
• Prologue: What’s New in the Second Edition?
• Contents
• 1. Overview and Foundations of Structural Equation Modeling
• 2. Design Issues in Longitudinal Studies
• 3. Modern Approaches to Missing Data in Longitudinal Studies
• 4. The Measurement Model
• 5. Model Fit, Sample Size, and Power
• 6. The Longitudinal CFA Model
• 7. Specifying and Interpreting a Longitudinal Panel Model
• 8. Multiple-Group Longitudinal Models
• 9. The Random Intercept Cross-Lagged Panel Model
• 10. Mediation and Moderation
• 11. Multilevel Growth Curves and Multilevel SEM
• 12. Longitudinal Mixture Modeling: Finding Unknown Groups
• 13. Bayesian Longitudinal Structural Equation Modeling
• 14. Jambalaya: Complex Construct Representations and Decompositions
• References
• Author Index
• Subject Index
• About the Author