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1. Overview of structural equation models
1 What is a structural equation model?
2 Structural equation model program
3 Structural equation model variables
4 Examples of foreign car models

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2. Characteristics of structural equation models
1. Use of latent variables and estimation of measurement error
2 Simultaneous estimation
3 Direct effect, indirect effect, total effect
4 Various statistical techniques
5 Various expressive techniques

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3 Uses of Amos
1 Amos Start
2 Amos screen composition
3 Amos Practice
4 Amos Results Interpretation

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4 Confirmatory factor analysis
1 Factor analysis
2 Confirmatory factor analysis and validity
3 Validation

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5 Path Analysis
1 What is path analysis?
2 Verification of mediating effects
3 Decomposition of correlations

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6 Structural equation model
1. Origin of structural equation models
2 Covariance matrix and correlation matrix
3 Reflection indicators and formative indicators
4. Model using reflection indicators and formative indicators
5 Two-Step Approach

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7 Structural Equation Model Research Stage Ⅰ:
Hypothesis setting and questionnaire development
1 Hypothesis
2. Questionnaire Development

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8 Structural Equation Model Research Stage II:
Data collection and inspection
1 Sample and test statistics
2 Appropriate sample size
3 missing values
4 outliers
5 Regularity
6 Input data

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9 Structural Equation Model Research Stage Ⅲ:
concretization of the research model
1. Sum of items of the construct concept
2 Model Settings
3. Identification of models and parameters
Estimation of 4 models

ch.10 Structural Equation Model Research Stage IV:
Interpretation and fit verification of the model
Interpretation of Model 1
2 Model fit

ch.11 Structural Equation Model Research Stage V:
Modifying the model and determining the final model
1 Model Modification
2 Final model decision

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12 Moderating and Interaction Effects
1 Moderating effect
2 Interaction effects
3-mediated moderation model
4. Moderated mediation model
5 Mediated moderation model with moderator variables

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13 Multi-group analysis
1 Understanding Multi-Group Analysis
2 Multigroup confirmatory factor analysis
3 Multi-group path analysis
4 Multi-group structural equation model
5. Examples of multi-group analysis used in actual papers

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14 Individual path indirect effects
1. Individual path indirect effects using phantom variables
2 Individual path indirect effects in structural equation models
3 Multiple independent variable model Individual path indirect effects
4 Complex model individual path indirect effects

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15 Latent Mean Analysis
1 Morphological identity, matrix identity, and intercept identity
2 Latent Mean Analysis

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16 Potential Growth Curve Model
1 Potential growth curve model
2 Potential growth curve model that is difficult to predict growth
3 Covariate Latent Growth Curve Model
4 Multivariate latent growth curve model
5 Nonlinear Growth Curve Model
6. The potential growth curve model with a curved shape
7. Mediating Effect of the Potential Growth Curve Model
8. Multi-group analysis of the latent growth curve model
9 Higher-order potential growth curve model
10 Higher-Order Growth Mixed Models

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17 Other Analysis Techniques
1 Bayesian estimation
2 Model Setting Exploration
3. Comparison of coefficients between paths

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18 Error Messages and Solutions

▶ Build basic skills with clear concept explanations
By reducing complex formulas and difficult terms and focusing on clear explanations of structural equation modeling concepts, we aim to help beginners in statistics approach structural equation modeling with interest and build a solid foundation of basic skills.
At the end of each chapter, we have included a Q&A section with frequently asked questions and answers from Amos users.

▶ One model - solidifying analytical capabilities by applying various analysis methods.
The 'foreign car model' was used as a consistent example so that beginners could solidify their analytical skills by repeating a series of processes from 'data collection to analysis of the research model'.
This allows readers to understand the contents of the book with continuity.

▶ Revised edition with even richer content
The revised edition includes additional content on the use of mediated moderation models, moderated mediation models, and control variables, as well as the use of phantom variables and the analysis of various types of latent growth curve models.
This was intended to broaden readers' understanding of structural equation models and strengthen their analytical capabilities.