Structural Equation Modelling: Application for Research and Practice (With Amos and R)

Description

Structural Equation Modeling provides a conceptual and mathematical understanding of structural equation modelling, helping readers across disciplines understand how to test or validate theoretical models, and build relationships between observed variables. In addition to a providing a background understanding of the concepts, it provides step-by-step illustrative applications with AMOS, SPSS and R software programmes. This volume will serve as a useful reference for academic and industry researchers in the fields of engineering, management, psychology, sociology, human resources, and humanities. Preface Acknowledgements Contents About the Author 1 Introduction to Structural Equation Modelling 1.1 What Is Structural Equation Modelling (SEM)? 1.2 A Comparison of Traditional Statistical Techniques and SEM 1.3 Brief History of Causality Models 1.4 Types of Structural Equation Models 1.4.1 Latent Growth Curve (LGC) Model 1.4.2 Bayesian SEM (BSEM) 1.4.3 Partial Least Square SEM (PLS-SEM) 1.4.4 Hierarchical SEM 1.5 SEM Software Programmes 1.6 Reasons for Popularity of SEM 2 Technical Aspects of SEM 2.1 Basic Terminology of SEM 2.2 Basic Symbols and Relationships Used in Structural Equation Modelling 2.3 Path Analysis 2.4 Mathematical Explanation with Example 2.5 Confirmatory Factor Analysis (CFA) 2.6 Mathematical Specification of Structural Equation Modelling 2.7 Summarization of Key Concepts 2.8 Importance of SEM in Research 2.9 Assumptions in SEM 2.10 Sample Size Considerations in SEM 2.11 Key Issues in SEM 3 Procedural Steps in Structural Equation Modelling 4 Applications of Structural Equation Modelling with AMOS 21, IBM SPSS 4.1 History of AMOS, IBM SPSS Software 4.2 A Step-by-Step Procedure to Solve SEM Using AMOS, IBM SPSS 4.3 Illustrative Applications of SEM in AMOS, SPSS 4.3.1 Application 1: Healthcare System 4.3.2 Application 2: Marketing Model 4.3.3 Application 3: Productivity Model 4.3.4 Application 4: SEM for Job Satisfaction and HR Policies 4.3.5 Application 5: SEM for Student Performance and Teaching Pedagogy Model 5 Applications of Structural Equation Modelling with R 5.1 History of R Software 5.2 Step-by-Step Procedure for Conducting SEM in R 5.3 Illustrative Applications of SEM in R 5.3.1 Application 1: Student Performance and Teaching Pedagogy Model 5.3.2 Application 2: Productivity Model 6 Applications of SEM and FAQs 6.1 Applications of SEM 6.2 Frequently Asked Questions (FAQs) on Structural Equation Modelling (SEM) Summary of Key Points YouTube Links Glossary of Key SEM Terminologies Bibliography and Further Reading