A Beginner’s Guide to Structural Equation Modeling

Höfundur Tiffany A. Whittaker; Randall E. Schumacker

Útgefandi Taylor & Francis

Snið ePub

Print ISBN 9780367477967

Útgáfa 5

Útgáfuár 2022

11.390 kr.

Description

Efnisyfirlit

  • Cover
  • Half-Title Page
  • Title Page
  • Copyright Page
  • Dedication
  • Table of Contents
  • Preface
  • Chapter 1 Introduction
  • What is Structural Equation Modeling?
  • Notation and Terminology
  • History of Structural Equation Modeling
  • Why Conduct Structural Equation Modeling?
  • Brief Consideration of Causality in SEM
  • Structural Equation Modeling Software
  • AMOS (SPSS)
  • CALIS Procedure (in SAS)
  • EQS: Stand-alone Software
  • JMP: Stand-alone Software / SAS Interface
  • LISREL: Stand-alone Software
  • Mplus: Stand-alone Software
  • OpenMx: Stand-alone Software (Free); R Interface
  • R: Stand-alone Software (Free)
  • SEM (in STATA)
  • SEPATH (in Statistica)
  • Software Considerations
  • Book Website
  • Summary
  • Exercises
  • References
  • Chapter 2 Data Entry and Editing Issues
  • Data Set Formats
  • Data Editing Issues
  • Measurement Scale
  • Restriction of Range
  • Outliers
  • Normality
  • Linearity
  • Missing Data
  • Summary
  • Exercises
  • References
  • Chapter 3 Correlation and Regression Methods
  • Types of Correlation Coefficients
  • Factors Affecting Correlation Coefficients
  • Non-linearity
  • Missing Data
  • Level of Measurement and Restriction of Range
  • Non-normality
  • Outliers
  • Simple Linear Regression
  • Multiple Linear Regression
  • Bivariate, Part, and Partial Correlations in Multiple Regression
  • Multicollinearity and Suppressor Variables
  • Correlation Versus Covariance
  • Variable Metrics (Standardized Versus Unstandardized)
  • Correction for Attenuation
  • Multiple Regression Example
  • Summary
  • Chapter Footnote
  • Regression Model with Intercept Term
  • Exercises
  • References
  • Chapter 4 Path Models
  • Path Model Diagrams
  • Decomposition of the Correlation Matrix
  • Decomposition for Unstandardized Path Models
  • Path Model Example
  • Indirect Effects
  • Causation Assumptions and Limitations
  • Summary
  • Exercises
  • References
  • Chapter 5 SEM Basics
  • SEM Modeling Steps
  • Model Specification
  • Model Identification
  • Model Estimation
  • Model Testing
  • Model Modification/Re-specification
  • Model Estimation
  • Model Testing
  • Model Fit
  • Chi-square (χ2)
  • Model Fit Indices
  • Parameter Fit
  • Model Comparison
  • Model Modification and Re-specification
  • Modification Indices
  • Expected Parameter Change
  • MIs and EPCs in LISREL and Mplus
  • Summary
  • Exercises
  • Chapter Footnote
  • Chi-squares
  • References
  • Chapter 6 Factor Analysis
  • Exploratory Factor Analysis
  • Sample Size
  • Number of Factors
  • Rotation Methods
  • Factor Scores
  • EFA Versus PCA
  • EFA Example
  • Pattern and Structure Matrices
  • Confirmatory Factor Analysis
  • CFA Example
  • CFA with Missing Continuous Data
  • CFA Caveats
  • CFA with Missing Ordinal Indicators
  • CFA Model Comparisons
  • Summary
  • Exercises
  • References
  • Chapter 7 Full SEM
  • Full Structural Equation Models
  • Model Specification in Full SEM
  • Model Identification
  • Two-step Versus Four-step SEM Model Testing
  • Model Estimation
  • Model Testing and Model Modification
  • Indirect Effects in Full SEM Models
  • Summary
  • Exercises
  • References
  • Chapter 8 Extensions of CFA Models
  • Second-order Factor Model
  • Model Specification
  • Model Identification
  • Model Estimation
  • Model Testing and Model Modification
  • Model Interpretation
  • Bifactor Model
  • Model Specification
  • Model Identification
  • Model Estimation
  • Model Testing and Model Modification
  • Model Interpretation
  • Model Comparisons Between the Second-order and Bifactor Models
  • Summary
  • Exercises
  • References
  • Chapter 9 Multiple Group (Sample) Models
  • Brief Summary of Multiple Group Modeling
  • Multiple Group Path Analysis Model
  • Model Identification in Separate Groups
  • Model Estimation in Separate Groups
  • Model Testing in Separate Groups
  • Model Identification of the Baseline Multiple Group Model – With No Equality Constraints
  • Model Estimation of the Baseline Multiple Group Model – With No Equality Constraints
  • Model Testing of the Baseline Multiple Group Model – With No Equality Constraints
  • Model Identification of the Multiple Group Model – With Equality Constraints
  • Model Estimation of the Multiple Group Model – With Equality Constraints
  • Model Testing and Modification of the Multiple Group Model – With Equality Constraints
  • Final Model Interpretation
  • Multiple Group CFA/Measurement Model
  • Measurement Invariance
  • Multiple Group CFA Example
  • Model Identification in Separate Groups
  • Model Estimation in Separate Groups
  • Model Testing in Separate Groups
  • Model Identification of the Configural Multiple Group CFA Model – With No Equality Constraints
  • Model Estimation of the Configural Multiple Group CFA Model – With No Equality Constraints
  • Model Testing of the Configural Multiple Group CFA Model – With No Equality Constraints
  • Model Identification of the Metric Multiple Group CFA Model
  • Model Estimation of the Metric Multiple Group CFA Model
  • Model Testing and Modification of the Metric Multiple Group CFA Model
  • Model Identification of the Strong/Scalar Multiple Group CFA Model
  • Model Estimation of the Scalar Multiple Group CFA Model
  • Model Testing and Modification of the Scalar Multiple Group CFA Model
  • Final Model Interpretation
  • Strict Invariance Testing
  • Structural Model Group Differences
  • Multiple Group Models with Ordinal Indicators
  • Cautions about Invariance Testing
  • Summary
  • Exercises
  • References
  • Chapter 10 SEM Considerations
  • Best Practices in SEM
  • Checklist for SEM
  • Basic Issues
  • Analysis Issues
  • Model Specification
  • Model Identification
  • Data Preparation
  • Model Estimation
  • Model Testing
  • Model Modification/Re-specification
  • Non-recursive Models
  • Equivalent Models
  • Summary
  • References
  • Introduction to Matrix Operations
  • Statistical Tables
  • Name Index
  • Subject Index
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