CHAPTER 1 Overview of SEM
1. Significance of SEM
2. Characteristics of SEM
3. Why SEM is Preferred

CHAPTER 2 Understanding Amos
1.
About Amos
2.
Drawing a route with Amos
3.
SEM analysis procedure by Amos

CHAPTER 3 SEM Fundamentals
1. Variables of SEM
2.
Confirmatory factor analysis
3.
Complete model
4.
Path analysis

CHAPTER 4: Building a Model and Creating a Path Map
1.
Model conceptualization and path mapping
2.
The main research model of this book
3.
Building a multidimensional concept model
4.
Non-recursive model

CHAPTER 5 Data Collection and Data Review
1.
Data Collection: Determining Sample Size
2.
Data review

CHAPTER 6 Model Setup, Model Identification, and Model Estimation
1.
Model settings
2.
Model identification
3.
Model estimation

CHAPTER 7 EVALUATION AND INTERPRETATION OF ANALYSIS RESULTS
1.
Review of the year
2.
Model fit evaluation
3.
Interpretation of results

CHAPTER 8 MODEL MODIFICATION
1.
Significance and strategy of model modification
2.
Considerations when modifying models
3.
Evaluation of the goodness of fit of the modified model
4.
Example of model modification
5.
Setting Exploration by Amos

CHAPTER 9 PRESENTATION AND DESCRIPTION OF ANALYSIS RESULTS
1.
Description of conceptual and statistical models
2.
Technology of Results
[Appendix] Checklist for Presenting SEM Results

CHAPTER 10 Reflection and formative indicators, item grouping, and concept validity assessment
1.
Reflection indicators and formative indicators
2.
Grouping items
3.
Conceptual validity assessment

CHAPTER 11 Moderating Effect Analysis (Ⅰ): Nonmetric Variables
1.
Significance of moderating effect
2.
Analysis of the moderating effect of nonmetric variables

CHAPTER 12 Moderating Effect Analysis (Ⅱ): Metric Variables
1.
Analysis of the moderating effect of latent variables
2.
Ping's approach
3.
Marsh et al.'s approach
4.
Lin et al.'s approach
5.
Considerations for Matched Pairs Strategies
6.
Little et al.'s approach

CHAPTER 13 Analysis of Mediation Effects (I): Single Mediation Model
1.
Significance of mediation effect analysis
2.
Single Mediating Effect Model: Example 1
3.
Single Mediating Effect Model: Example 2
4.
Single Mediating Effect Model: Example 3

CHAPTER 14 Analysis of Mediation Effects (II): Multiple Mediation Model
1.
Parallel multiparameter model
2.
Continuous multi-parameter model
3.
Multimediation Model: Example 1
4.
Multimediation Model: Example 2
5.
Multimediation Model: Example 3
6.
multi-group mediation analysis

CHAPTER 15: Comparison of Path Coefficients Between Groups, Analysis of the Relative Effectiveness of Path Coefficients, and Introduction of Control Variables
1.
Cross-Group Comparison of Path Coefficients: Path Models
2.
Cross-Group Comparison of Path Coefficients: A Structural Model
3.
Relative effectiveness analysis of path coefficients
4.
Introduction of control variables

CHAPTER 16 Equivalent Model, Single Indicator Setting
1.
Equivalent model
2.
Single indicator setting

CHAPTER 17 Common Method Variance
1.
The significance and origin of common method variance
2.
Control method for common method dispersion
3.
Diagnosis and bias estimation of common method variance

【Data and input files can be downloaded from http://www.esem.co.kr】


Author's Note

In the book 『Amos 24 Structural Equation Modeling』 (2017), the author strongly emphasized that the error variance reported in Amos should not be used when calculating CR and AVE, which are used to evaluate conceptual validity.
However, if you look at Amos books published in Korea, papers using Amos, or YouTube videos related to Amos, you can see that such errors still exist.
Even in papers published in domestic journals with excellent rankings, such errors are still being found.
Seeing these errors, I cannot help but feel truly sorry, as the author's cries seem to be nothing more than echoes.
I would like to once again urge researchers not to make such mistakes.
I sincerely hope that the author's regret will disappear after this book.

This book is a compilation of the following additions and supplements to the book Amos 24:
① In Chapter 3, effect decomposition is described.
② In Chapter 10, it is also described that the discriminant validity evaluation is based on the HTMT.
It has been shown to be more stringent than the AVE standard, which has been widely used in the past for evaluating discriminant validity, and its use has been increasing recently.
③ In addition to analyzing multi-parameter models using phantom variables in Chapter 14, analysis using user-defined estimates is also described.
We also described another way to create phantom variables.
④ Chapter 14 describes how to analyze the multiple group mediation model.
A multi-group mediation model tests whether there is a difference in the mediating effect between two or more groups.
⑤ Chapter 16 describes another method using a single indicator.
⑥ In Chapter 17, we added information on diagnosing common method variance (CMV). Diagnosing CMV is a recent research trend.
In that respect, the 'top journal' emphasizes that not diagnosing CMV will result in a 'desk reject'.
⑦ References are organized by chapter in accordance with APA style (7th edition) to provide practical help to readers.