Structural Equation Modeling: Foundations and Extensions: Advanced Quantitative Techniques in the Social Sciences, cartea 10
Autor David W. Kaplanen Limba Engleză Hardback – 3 sep 2008
- traditional SEM for continuous latent variables, including assumption issues as well as latent growth curve modeling for continuous growth factors
- 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. The book has been enhanced with certain features that will guide the student and researcher through the foundations and critical assumptions of SEM.
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Specificații
ISBN-13: 9781412916240
ISBN-10: 1412916240
Pagini: 272
Ilustrații: Illustrations
Dimensiuni: 152 x 229 x 18 mm
Greutate: 0.5 kg
Ediția:Second Edition
Editura: SAGE Publications
Colecția Sage Publications, Inc
Seria Advanced Quantitative Techniques in the Social Sciences
Locul publicării:Thousand Oaks, United States
ISBN-10: 1412916240
Pagini: 272
Ilustrații: Illustrations
Dimensiuni: 152 x 229 x 18 mm
Greutate: 0.5 kg
Ediția:Second Edition
Editura: SAGE Publications
Colecția Sage Publications, Inc
Seria Advanced Quantitative Techniques in the Social Sciences
Locul publicării:Thousand Oaks, United States
Cuprins
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
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
Notă biografică
David Kaplan received his Ph.D. in Education from UCLA in 1987. He is now a Professor of Education and (by courtesy) Psychology at the University of Delaware. His research interests are in the development and application of statistical models to problems in educational evaluation and policy analysis. His current program of research concerns the development of dynamic latent continuous and categorical variable models for studying the diffusion of educational innovations.
Descriere
Clearly and precisely shows how SEM can be used to answer or provide insight to substantive questions, specifically by weaving a small set of empirical examples and data throughout the chapters