Basics of structural equation modeling /

With the availability of software programs such as LISREL, EQS, and AMOS modeling techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. The pop...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Maruyama, Geoffrey
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Thousand Oaks, Calif. ; London : Sage, ©1998.
Temas:
Multivariate analysis.
Social sciences > Statistical methods.
Analyse multivariée.
Sciences sociales > Méthodes statistiques.
MATHEMATICS > Probability & Statistics > Multivariate Analysis.
Multivariate analysis
Social sciences > Statistical methods
Strukturgleichungsmodell
Multivariate Analyse
Sozialwissenschaften
Structurele vergelijkingen.
Multivariate analyse.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. What Does It Mean to Model Hypothesized Causal Processes With Nonexperimental Data?
  • 2. History and Logic of Structural Equation Modeling
  • 3. Basics: Path Analysis and Partitioning of Variance
  • 4. Effects of Collinearity on Regression and Path Analysis
  • 5. Effects of Random and Nonrandom Error on Path Models
  • 6. Recursive and Longitudinal Models: Where Causality Goes in More Than One Direction and Where Data Are Collected Over Time
  • 7. Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling
  • 8. Putting It All Together: Latent Variable Structural Equation Modeling
  • 9. Using Latent Variable Structural Equation Modeling to Examine Plausibility of Models
  • 10. Logic of Alternative Models and Significance Tests
  • 11. Variations on the Basic Latent Variable Structural Equation Model
  • 12. Wrapping Up
  • App. A Brief Introduction to Matrix Algebra and Structural Equation Modeling.

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