Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS
eBook - ePub

Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS

  1. 360 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS

About this book

This student orientated guide to structural equation modeling promotes theoretical understanding and inspires studentsĀ with the confidenceĀ to successfully apply SEM. Assuming no previous experience, and a minimum of mathematical knowledge, this is an invaluable companion for students taking introductory SEM courses in any discipline.

Niels Blunch shines a light on each step of the structural equation modeling process,Ā providing a detailed introduction to SPSS and EQS with a focus on EQS? excellent graphical interface. He also sets out best practice for data entry and programming, and uses real life data to show how SEM is applied in research.

The book includes:

  • Learning objectives, key concepts and questions for further discussion in each chapter.
  • Helpful diagrams and screenshots to expand on concepts covered in the texts.
  • A wide variety of examples from multiple disciplines and real world contexts.
  • Exercises for each chapter on an accompanyingĀ .
  • A detailed glossary.

Clear, engaging and built around key software,Ā this is an ideal introduction for anyone new to SEM.Ā 

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Yes, you can access Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS by Niels J. Blunch in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Publisher Note
  4. Title Page
  5. Copyright Page
  6. Contents
  7. How to use the companion website
  8. About the author
  9. Preface
  10. Part 1 Preparing Yourself and Your Data
  11. 1 Introduction
  12. 2 Measuring Your Variables: Reliability and Validity
  13. 3 Factor Analysis
  14. Part 2 Structural Equation Modeling with EQS
  15. 4 The Three Basic Models
  16. 5 Data Entering and Programming in EQS
  17. 6 Models with Only Manifest Variables
  18. 7 The Measurement Model in SEM: Confirmatory Factor Analysis
  19. 8 The General Model
  20. Part 3 Advanced Models and Techniques
  21. 9 Mean Structures and Multi-group Analysis
  22. 10 Incomplete and Non-normal Data
  23. 11 Latent Curve Models
  24. Appendices A: Statistical Prerequisites
  25. References
  26. B: Glossary
  27. C: EQS Statements
  28. Author Index
  29. Index