紹介
Thoroughly revised to address the recent developments that continue to shape the use of structural equation modeling (SEM) in the social and behavioural sciences, the second edition of "Structural Equation Modeling" author has restructured this book into three defined sections: The foundations of SEM, including path analysis and factor analysis; traditional SEM for continuous latent variables, including assumption issues as well as latent growth curve modeling for continuous growth factors; and, SEM for categorical latent variables, including latent class analysis, Markov models (latent and mixed latent), and growth mixture modeling. Through the use of detailed, empirical examples, Kaplan demonstrates how SEM can provide a unique lens on the problems social and behavioural scientists face. This book has been enhanced with certain features that will guide the student and researcher through the foundations and critical assumptions of SEM.
目次
Preface to the Second Edition 1. Historical Foundations of Structural Equation Modeling for Continuous and Categorical Latent Variables 2. Path Analysis: Modeling Systems of Structural Equations Among Observed Variables 3. Factor Analysis 4. Structural Equation Models in Single and Multiple Groups 5. Statistical Assumptions Underlying Structural Equation Modeling 6. Evaluating and Modifying Structural Equation Models 7. Multilevel Structural Equation Modeling 8. Latent Growth Curve Modeling 9. Structural Models for Categorical and Continuous Latent Variables 10. Epilogue: Toward a New Approach to the Practice of Structural Equation Modeling
