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Beginner's Guide to Structural Equation Monitoring

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ISBN-10: 1841698911

ISBN-13: 9781841698915

Edition: 3rd 2010 (Revised)

Authors: Randall E. Schumacker, Richard G. Lomax

List price: $43.99
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This textbook presents a basic introduction to structural equation modeling (SEM) and focuses on the conceptual steps to be taken in analysing conceptual models.
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Book details

List price: $43.99
Edition: 3rd
Copyright year: 2010
Publisher: Taylor & Francis Group
Publication date: 5/21/2010
Binding: Paperback
Pages: 536
Size: 5.75" wide x 8.75" long x 1.25" tall
Weight: 1.584
Language: English

About the Authors
Preface
Introduction
What Is Structural Equation Modeling?
History of Structural Equation Modeling
Why Conduct Structural Equation Modeling?
Structural Equation Modeling Software Programs
Summary
References
Data Entry and Data Editing Issues
Data Entry
Data Editing Issues
Measurement Scale
Restriction of Range
Missing Data
LISREL-PRELIS Missing Data Example
Outliers
Linearity
Nonnormality
Summary
References
Correlation
Types of Correlation Coefficients
Factors Affecting Correlation Coefficients
Level of Measurement and Range of Values
Nonlinearity
Missing Data
Outliers
Correction for Attenuation
Nonpositive Definite Matrices
Sample Size
Bivariate, Part, and Partial Correlations
Correlation versus Covariance
Variable Metrics (Standardized versus Unstandardized)
Causation Assumptions and Limitations
Summary
References
SEM Basics
Model Specification
Mode] Identification
Model Estimation
Model Testing
Model Modification
Summary
References
Model Fit
Types of Model-Fit Criteria
LISREL-SIMPLIS Example
Data
Program
Output
Model Fit
Chi-Square (X<sup>2</sup>)
Goodness-of-Fit Index (GFI) and Adjusted Goodness-of-Fit Index (AGFI)
Root-Mean-Square Residual Index (RMR)
Model Comparison
Tucker-Lewis Index (TLI)
Normed Fit Index (NFI) and Comparative Fit Index (CFI)
Model Parsimony
Parsimony Normed Fit Index (PNFI)
Akaike Information Criterion (AIC)
Summary
Parameter Fit
Power and Sample Size
Model Fit
Power
Sample Size
Model Comparison
Parameter Significance
Summary
Two-Step Versus Four-Step Approach to Modeling
Summary
Chapter Footnote
Standard Errors
Chi-Squares
References
Regression Models
Overview
An Example
Model Specification
Model Identification
Model Estimation
Model Testing
Model Modification
Summary
Measurement Error
Additive Equation
Chapter Footnote
Regression Model with Intercept Term
LISREL-SIMPLIS Program (Intercept Term)
References
Path Models
An Example
Model Specification
Model Identification
Model Estimation
Model Testing
Model Modification
Summary
Appendix: LISREL-SIMPLIS Path Model Program
Chapter Footnote
Another Traditional Non-SEM Path Model-Fit Index
LISREL-SIMPLIS program
References
Confirmatory Factor Models
An Example
Model Specification
Model Identification
Model Estimation
Model Testing
Model Modification
Summary
Appendix: LISREL-SIMPLIS Confirmatory Factor Model Program
References
Developing Structural Equation Models: Part I
Observed Variables and Latent Variables
Measurement Model
Structural Model
Variances and Covariance Terms
Two-Step/Four-Step Approach
Summary
References
Developing Structural Equation Models: Part II
An Example
Model Specification
Model Identification
Model Estimation
Model Testing
Model Modification
Summary
Appendix: LISREL-SIMPLIS Structural Equation Model Program
References
Reporting SEM Research: Guidelines and Recommendations
Data Preparation
Model Specification
Model Identification
Model Estimation
Model Testing
Model Modification
Summary
References
Model Validation
Key Concepts
Multiple Samples
Model A Computer Output
Model B Computer Output
Model C Computer Output
Model D Computer Output
Summary
Cross Validation
ECVI
CVI
Bootstrap
PRELIS Graphical User Interface
LISREL and PRELIS Program Syntax
Summary
References
Multiple Sample, Multiple Group, and Structured Means Models
Multiple Sample Models
Multiple Group Models
Separate Group Models
Similar Group Model
Chi-Square Difference Test
Structured Means Models
Model Specification and Identification
Model Fit
Model Estimation and Testing
Summary
Suggested Readings
Multiple Samples
Multiple Group Models
Structured Means Models
Chapter Footnote
SPSS
References
Second-Order, Dynamic, and Multitrait Multimethod Models
Second-Order Factor Model
Model Specification and Identification
Model Estimation and Testing
Dynamic Factor Model
Multitrait Multimethod Model (MTMM)
Model Specification and Identification
Model Estimation and Testing
Correlated Uniqueness Model
Summary
Suggested Readings
Second-Order Factor Models
Dynamic Factor Models
Multitrait Multimethod Models
Correlated Uniqueness Model
References
Multiple Indicator-Multiple Indicator Cause, Mixture, and Multilevel Models
Multiple Indicator-Multiple Cause (MIMIC) Models
Model Specification and Identification
Model Estimation and Model Testing
Model Modification
Goodness-of-Fit Statistics
Measurement Equations
Structural Equations
Mixture Models
Model Specification and Identification
Model Estimation and Testing
Model Modification
Robust Statistic
Multilevel Models
Constant Effects
Time Effects
Gender Effects
Multilevel Model Interpretation
Intraclass Correlation
Deviance Statistic
Summary
Suggested Readings
Multiple Indicator-Multiple Cause Models
Mixture Models
Multilevel Models
References
Interaction, Latent Growth, and Monte Carlo Methods
Interaction Models
Categorical Variable Approach
Latent Variable Interaction Model
Computing Latent Variable Scores
Computing Latent Interaction Variable
Interaction Model Output
Model Modification
Structural Equations-No Latent Interaction Variable
Two-Stage Least Squares (TSLS) Approach
Latent Growth Curve Models
Latent Growth Curve Program
Model Modification
Monte Carlo Methods
PRELIS Simulation of Population Data
Population Data from Specified Covariance Matrix
SPSS Approach
SAS Approach
LISREL Approach
Covariance Matrix from Specified Model
Summary
Suggested Readings
Interaction Models
Latent Growth-Curve Models
Monte Carlo Methods
References
Matrix Approach to Structural Equation Modeling
General Overview of Matrix Notation
Free, Fixed, and Constrained Parameters
LISREL Model Example in Matrix Notation
LISREL8 Matrix Program Output (Edited and Condensed)
Other Models in Matrix Notation
Path Model
Multiple-Sample Model
Structured Means Model
Interaction Models
PRELIS Computer Output
LISREL Interaction Computer Output
Summary
References
Introduction to Matrix Operations
Statistical Tables
Answers to Selected Exercises
Author Index
Subject Index
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