Buch, Englisch, 219 Seiten, Format (B × H): 173 mm x 246 mm, Gewicht: 586 g
A Manual for Researchers
Buch, Englisch, 219 Seiten, Format (B × H): 173 mm x 246 mm, Gewicht: 586 g
Reihe: Synthesis Lectures on Mathematics & Statistics
ISBN: 978-3-031-32672-1
Verlag: Springer International Publishing
This book presents a comprehensive overview of Structural Equation Modeling and how it can be applied to address research issues in different disciplines. The authors employ a ‘simple to complex’ approach. The book reviews topics such as variance, covariance, correlation, multiple regression, mediation, moderation, path analysis, and confirmatory factor analysis. The authors then discuss the initial steps for performing structural equation modeling, including model specification, model identification, model estimation, model testing, and model modification. The book includes an introduction to the IBM SPSS and IBM SPSS Amos software. The authors the explain how this software can be utilized for developing measurement, structural models, and SEM models. The book provides conceptual clarity in understanding the models and discusses practical approaches to solving them. The authors also highlight how these techniques can be applied to various disciplines, including psychology, education,sociology, business, medicine, political science, and biological sciences.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Mathematik Allgemein
- Mathematik | Informatik Mathematik Mathematische Analysis
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
Weitere Infos & Material
1. Overview Of Structural Equation Modelling.- 2. Introduction To Spss And Amos Software.- 3. Understanding Correlation And Regression.- 4. Understanding The Mediation Model.- 5. Understanding Path Analysis With Multiple Regression.- 6. Understanding Path Analysis With Structural Equation Modelling.- 7. Confirmatory Factor Analysis With Structural Equation Modelling.