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Longitudinal Structural Equation Modeling
Todd D. Little
- 616 pages
- English
- PDF
- Available on iOS & Android
Longitudinal Structural Equation Modeling
Todd D. Little
About This Book
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.
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Information
Table of contents
- Cover
- Front Endpaper: Greek Cheat Sheet
- Half Title Page
- Series Page
- Title Page
- Copyright
- Foreword
- Prologue: Whatâs 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