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E-raamat: Structural Equation Modelling: Application for Research and Practice (with AMOS and R)

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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.

Arvustused

The book can be very recommended all readers, who are interested in this field. (Ludwig Paditz, zbMATH 1461.62003, 2021)

1 Introduction to Structural Equation Modelling
1(12)
1.1 What Is Structural Equation Modelling (SEM)?
1(3)
1.2 A Comparison of Traditional Statistical Techniques and SEM
4(1)
1.3 Brief History of Causality Models
4(2)
1.4 Types of Structural Equation Models
6(3)
1.4.1 Latent Growth Curve (LGC) Model
7(1)
1.4.2 Bayesian SEM (BSEM)
8(1)
1.4.3 Partial Least Square SEM (PLS-SEM)
8(1)
1.4.4 Hierarchical SEM
8(1)
1.5 SEM Software Programmes
9(1)
1.6 Reasons for Popularity of SEM
9(4)
2 Technical Aspects of SEM
13(16)
2.1 Basic Terminology of SEM
13(2)
2.2 Basic Symbols and Relationships Used in Structural Equation Modelling
15(2)
2.3 Path Analysis
17(1)
2.4 Mathematical Explanation with Example
17(1)
2.5 Confirmatory Factor Analysis (CFA)
18(2)
2.6 Mathematical Specification of Structural Equation Modelling
20(3)
2.7 Summarization of Key Concepts
23(2)
2.8 Importance of SEM in Research
25(1)
2.9 Assumptions in SEM
25(1)
2.10 Sample Size Considerations in SEM
26(1)
2.11 Key Issues in SEM
27(2)
3 Procedural Steps in Structural Equation Modelling
29(6)
4 Applications of Structural Equation Modelling with AMOS 21, IBM SPSS
35(56)
4.1 History of AMOS, IBM SPSS Software
35(1)
4.2 A Step-by-Step Procedure to Solve SEM Using AMOS, IBM SPSS
36(14)
4.3 Illustrative Applications of SEM in AMOS, SPSS
50(41)
4.3.1 Application 1: Healthcare System
50(8)
4.3.2 Application 2: Marketing Model
58(6)
4.3.3 Application 3: Productivity Model
64(10)
4.3.4 Application 4: SEM for Job Satisfaction and HR Policies
74(7)
4.3.5 Application 5: SEM for Student Performance and Teaching Pedagogy Model
81(10)
5 Applications of Structural Equation Modelling with R
91(10)
5.1 History of R Software
91(2)
5.2 Step-by-Step Procedure for Conducting SEM in R
93(1)
5.3 Illustrative Applications of SEM in R
93(8)
5.3.1 Application I: Student Performance and Teaching Pedagogy Model
93(3)
5.3.2 Application 2: Productivity Model
96(5)
6 Applications of SEM and FAQs
101(12)
6.1 Applications of SEM
101(1)
6.2 Frequently Asked Questions (FAQs) on Structural Equation Modelling (SEM)
101(12)
Summary of Key Points 113(4)
YouTube Links 117(2)
Glossary of Key SEM Terminologies 119(4)
Bibliography and Further Reading 123
Dr. Jitesh J Thakkar is an Associate Professor in the Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur, India. He received his Ph.D. in Supply Chain Management from IIT Delhi. He has over 20 years of teaching, research and industry experience. He has published over 50 research papers in leading national and international journals in the areas of Lean & Sustainable manufacturing, Supply Chain Management, Quality Management, Small and Medium Enterprises, and Performance Measurement. He is the Associate Editor for OPSEARCH a journal published by Springer. His online course (MOOCs-NPTEL) on Six Sigma has benefited university students and industry professionals. He has conducted several training workshops for corporate managers in Six Sigma, Lean Manufacturing, Value Engineering, Project Management, Quality Management, Supply Chain Management and Statistical Decision Making.