Introduction to Structural Equation Modeling Using IBM SPSS Statistics and EQS

by Niels J. Blunch

Overview

This student orientated guide to structural equation modeling promotes theoretical understanding and inspires students with the confidence 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, 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 accompanying .
• A detailed glossary.

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

Product Details

ISBN-13:	9781473916227
Publisher:	SAGE Publications
Publication date:	11/12/2015
Pages:	360
Product dimensions:	6.69(w) x 9.53(h) x (d)

About the Author

Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark.

Table of Contents

Preface
PART 1: PREPARING YOURSELF AND YOUR DATA
Chapter 1: Introduction
Chapter 2: Measuring Your Variables: Reliability and Validity
Chapter 3: Factor Analysis
PART 2: THE THREE BASIC MODELS
Chapter 4: Structural Equation Modeling with EQS
Chapter 5: Data-entering and programming in EQS
Chapter 6: Models with Only Manifest Variables
Chapter 7: The Measurement Model in SEM: Confirmatory Factor Analysis
Chapter 8: The General Model
PART 3: ADVANCED MODELS AND TECHNIQUES
Chapter 9: Mean Structures and Multi-group Analysis
Chapter 10: Incomplete and Non-normal Data
Chapter 11: Latent Curve Models
Appendix A: Statistical Prerequisites
Appendix B: Glossary
Appendix C: EQS Statements

Editorial Reviews

This textbook combines accessible explanations of key concepts and methods used in SEM with detailed demonstrations of how to use EQS. It covers both basic as well as advanced topics, all illustrated with examples relevant to social science subjects. An excellent choice for anybody new to SEM and who would like to learn how to use EQS.

Keming Yang