Longitudinal structural equation modeling: a comprehensive introduction
β Scribed by Newsom, Jason T
- Publisher
- Taylor & Francis
- Year
- 2015
- Tongue
- English
- Leaves
- 437
- Series
- Multivariate applications series
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
- Review of Some Key Latent Variable Principles 2. Longitudinal Measurement Invariance 3. Structural Models for Comparing Dependent Means and Proportions 4. Fundamental Concepts of Stability and Change 5. Cross-Lagged Panel Models 6. Latent State-Trait Models 7. Linear Latent Growth Curve Models 8. Nonlinear Latent Growth Curve Models 9. Latent Difference Score Models 10. Latent Transition and Growth Mixture Models 11. Time Series Analysis 12. Survival Analysis Models 13. Missing Data and Attrition Appendix A: Notation Appendix B: A Primer on the Calculus of Change
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<P>This comprehensive resource reviews structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling options are available for which hypotheses. The author demonstrates how SEM is related to other longitudinal data techniques throughout. By exploring connecti
<P>This comprehensive resource reviews structural equation modeling (SEM) strategies for longitudinal data to help readers see which modeling options are available for which hypotheses. The author demonstrates how SEM is related to other longitudinal data techniques throughout. By exploring connecti
"Featuring actual datasets as illustrative examples, this book reveals numerous ways to apply structural equation modeling (SEM) to any repeated-measures study. Initial chapters lay the groundwork for modeling a longitudinal change process, from measurement, design, and specification issues to model