Introduction to Structural Equation Modeling Using IBM SPSS Statistics and Amos
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Go to College Publishing WebsiteDescription
This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS' graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this Second Edition is the ideal guide for those new to the field.
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
- Real life examples from a variety of disciplines to show hoe SEM is applied in real research contexts
- Exercises for each chapter on an accompanying companion website
- A new glossary at the end of book
Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline.
Contents
PART ONE: PREPARING YOURSELF AND YOUR DATA
- Introduction
- Measuring Your Variables: Reliability and Validity
- Factor Analysis
PART TWO: THE THREE BASIC MODELS
- Structural Equation Modeling with AMOS
- Models with Only Manifest Variables
- The Measurement Model in SEM: Confirmatory Factor Analysis
- The General Model
PART THREE: ADVANCED MODELS AND TECHNIQUES
- Mean Structures and Multi-Group Analysis
- Incomplete and Non-Normal Data
- Latent Curve Models
Additional materials
Description
This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS' graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this Second Edition is the ideal guide for those new to the field.
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
- Real life examples from a variety of disciplines to show hoe SEM is applied in real research contexts
- Exercises for each chapter on an accompanying companion website
- A new glossary at the end of book
Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline.
Contents
PART ONE: PREPARING YOURSELF AND YOUR DATA
- Introduction
- Measuring Your Variables: Reliability and Validity
- Factor Analysis
PART TWO: THE THREE BASIC MODELS
- Structural Equation Modeling with AMOS
- Models with Only Manifest Variables
- The Measurement Model in SEM: Confirmatory Factor Analysis
- The General Model
PART THREE: ADVANCED MODELS AND TECHNIQUES
- Mean Structures and Multi-Group Analysis
- Incomplete and Non-Normal Data
- Latent Curve Models
Additional materials
Reviews
Introduction to Structural Equation Modeling Using IBM SPSS Statistics and Amos
April 2013 | 312 pages | Sage UK
| Format | Published Date | ISBN | Price |
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This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS' graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this Second Edition is the ideal guide for those new to the field.
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
- Real life examples from a variety of disciplines to show hoe SEM is applied in real research contexts
- Exercises for each chapter on an accompanying companion website
- A new glossary at the end of book
Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline.
Table Of Contents:
- PART ONE: PREPARING YOURSELF AND YOUR DATA
- Introduction
- Measuring Your Variables: Reliability and Validity
- Factor Analysis
- PART TWO: THE THREE BASIC MODELS
- Structural Equation Modeling with AMOS
- Models with Only Manifest Variables
- The Measurement Model in SEM: Confirmatory Factor Analysis
- The General Model
- PART THREE: ADVANCED MODELS AND TECHNIQUES
- Mean Structures and Multi-Group Analysis
- Incomplete and Non-Normal Data
- Latent Curve Models