Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming

✍ Scribed by Byrne, Barbara M

• Publisher: Taylor and Francis
• Year: 2013
• Tongue: English
• Leaves: 417
• Series: Multivariate applications book series
• Edition: 2nd edition
• Category: Library

✦ Synopsis

Cover; Half Title; Title Page; Copyright Page; Table of Contents; Preface; Acknowledgments; Section I:Introduction; Chapter 1. Structural equation models: The basics; Basic concepts; Latent versus observed variables; Exogenous versus endogenous latent variables; The factor analytic model; The full latent variable model; General purpose and process of statistical modeling; The general structural equation model; Symbol notation; The path diagram; Structural equations; Nonvisible components of a model; Basic composition; The formulation of covariance and mean structures; Endnotes.;This bestselling text provides a practical guide to the basic concepts of structural equation modeling (SEM) and the AMOS program (Versions 17 & 18). The author reviews SEM applications based on actual data taken from her research. Noted for its non-mathematical language, this book is written for the novice SEM user. With each chapter, the author ""walks"" the reader through all steps involved in testing the SEM model including: an explanation of the issues addressed an illustration of the hypothesized and posthoc models tested AMOS input and output with accompanying interpretation and explana.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgments
Section I:Introduction
Chapter 1. Structural equation models: The basics
Basic concepts
Latent versus observed variables
Exogenous versus endogenous latent variables
The factor analytic model
The full latent variable model
General purpose and process of statistical modeling
The general structural equation model
Symbol notation
The path diagram
Structural equations
Nonvisible components of a model
Basic composition
The formulation of covariance and mean structures
Endnotes. Chapter 2. Using the AMOS programWorking with AMOS Graphics: Example 1
Initiating AMOS Graphics
AMOS modeling tools
The hypothesized model
Drawing the path diagram
Understanding the basic components of model 1
The concept of model identification
Working with AMOS Graphics: Example 2
The hypothesized model
Drawing the path diagram
Working with AMOS Graphics: Example 3
The hypothesized model
Drawing the path diagram
Endnotes
Section II: Applications in single-group analyses
Chapter 3. Testing for the factorial validity of a theoretical construct
The hypothesized model. Hypothesis 1: Self-concept is a four-factor structureModeling with AMOS Graphics
Model specification
Data specification
Calculation of estimates
AMOS text output: Hypothesized four-factor model
Model summary
Model variables and parameters
Model evaluation
Parameter estimates
Feasibility of parameter estimates
Appropriateness of standard errors
Statistical significance of parameter estimates
Model as a whole
The model-fitting process
The issue of statistical significance
The estimation process
Goodness-of-fit statistics
Model misspecification
Residuals
Modification indices. Post hoc analysesHypothesis 2: Self-concept is a two-factor structure
Selected AMOS text output: Hypothesized two-factor model
Hypothesis 3: Self-concept is a one-factor structure
Endnotes
Chapter 4. Testing for the factorial validity of scores from a measuring instrument (First-order CFA model)
The measuring instrument under study
The hypothesized model
Modeling with AMOS Graphics
Selected AMOS output: The hypothesized model
Model summary
Assessment of normality
Assessment of multivariate outliers
Model evaluation
Goodness-of-fit summary
Modification indices
Post hoc analyses. Model 2Selected AMOS output: Model 2
Model 3
Selected AMOS output: Model 3
Model 4
Selected AMOS output: Model 4
Comparison with robust analyses based on the Satorra-Bentler scaled statistic
Endnotes
Chapter 5. Testing for the factorial validity of scores from a measuring instrument
The hypothesized model
Modeling with AMOS Graphics
Selected AMOS output: Preliminary model
Selected AMOS output: The hypothesized model
Model evaluation
Goodness-of-fit summary
Model maximum likelihood (ML) estimates
Estimation of continuous versus categorical variables.

✦ Subjects

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