
Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS
- 360 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
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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Information
Table of contents
- Cover
- Half Title
- Publisher Note
- Title Page
- Copyright Page
- Contents
- How to use the companion website
- About the author
- Preface
- Part 1 Preparing Yourself and Your Data
- 1 Introduction
- 2 Measuring Your Variables: Reliability and Validity
- 3 Factor Analysis
- Part 2 Structural Equation Modeling with EQS
- 4 The Three Basic Models
- 5 Data Entering and Programming in EQS
- 6 Models with Only Manifest Variables
- 7 The Measurement Model in SEM: Confirmatory Factor Analysis
- 8 The General Model
- Part 3 Advanced Models and Techniques
- 9 Mean Structures and Multi-group Analysis
- 10 Incomplete and Non-normal Data
- 11 Latent Curve Models
- Appendices A: Statistical Prerequisites
- References
- B: Glossary
- C: EQS Statements
- Author Index
- Index