Longitudinal Structural Equation Modeling, Second Edition provides an in-depth, comprehensive overview of structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling options are available for which hypotheses.
Longitudinal Structural Equation Modeling, Second Edition provides an in-depth, comprehensive overview of structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling options are available for which hypotheses.
Jason T. Newsom is professor of psychology at Portland State University, Portland, Oregon, USA.
Inhaltsangabe
Contents List of Figures List of Tables Preface to the Second Editon Preface to the First Edition Acknowledgements Example Data Sets Chapter 1. Review of Some Key Latent Variable Principles Chapter 2. Longitudinal Measurement Invariance Chapter 3. Structural Models for Comparing Dependent Means and Proportions Chapter 4. Fundamental Concepts of Stability and Change Chapter 5. Cross-Lagged Panel Models Chapter 6. Latent State-Trait Models Chapter 7. Linear Latent Growth Curve Models Chapter 8. Nonlinear Latent Growth Curve Models Chapter 9. Nonlinear Latent Growth Curve Models Chapter 10. Latent Class and Latent Transition Chapter 11. Growth Mixture Models Chapter 12. Intensive Longitudinal Models: Time Series and Dynamic Structural Equation Models Chapter 13. Survival Analysis Models Chapter 14. Missing Data and Attrition Appendix A: Notation Appendix B: Why Does the Single Occasion Scaling Constraint Approach Work? Appendix C: A Primer on the Calculus of Change Glossary Index
Contents List of Figures List of Tables Preface to the Second Editon Preface to the First Edition Acknowledgements Example Data Sets Chapter 1. Review of Some Key Latent Variable Principles Chapter 2. Longitudinal Measurement Invariance Chapter 3. Structural Models for Comparing Dependent Means and Proportions Chapter 4. Fundamental Concepts of Stability and Change Chapter 5. Cross-Lagged Panel Models Chapter 6. Latent State-Trait Models Chapter 7. Linear Latent Growth Curve Models Chapter 8. Nonlinear Latent Growth Curve Models Chapter 9. Nonlinear Latent Growth Curve Models Chapter 10. Latent Class and Latent Transition Chapter 11. Growth Mixture Models Chapter 12. Intensive Longitudinal Models: Time Series and Dynamic Structural Equation Models Chapter 13. Survival Analysis Models Chapter 14. Missing Data and Attrition Appendix A: Notation Appendix B: Why Does the Single Occasion Scaling Constraint Approach Work? Appendix C: A Primer on the Calculus of Change Glossary Index
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