AMOSによる構造方程式モデリング(第3版)<br>Structural Equation Modeling with Amos : Basic Concepts, Applications, and Programming (Multivariate Applications) (3TH)

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AMOSによる構造方程式モデリング(第3版)
Structural Equation Modeling with Amos : Basic Concepts, Applications, and Programming (Multivariate Applications) (3TH)

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  • 製本 Hardcover:ハードカバー版/ページ数 437 p.
  • 言語 ENG
  • 商品コード 9781138797024
  • DDC分類 519.535

Full Description


This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter "walks" readers through the steps involved (specification, estimation, evaluation, and post hoc modification) in testing a variety of SEM models. Accompanying each application is: an explanation of the issues addressed and a schematic presentation of hypothesized model structure; Amos input and output with interpretations; use of the Amos toolbar icons and pull-down menus; and data upon which the model application was based, together with updated references pertinent to the SEM model tested.Thoroughly updated throughout, the new edition features:All new screen shots featuring Amos Version 23. Descriptions and illustrations of Amos' new Tables View format which enables the specification of a structural model in spreadsheet form. Key concepts and/or techniques that introduce each chapter. Alternative approaches to model analyses when enabled by Amos thereby allowing users to determine the method best suited to their data. Provides analysis of the same model based on continuous and categorical data (Ch. 5) thereby enabling readers to observe two ways of specifying and testing the same model as well as compare results. All applications based on the Amos graphical mode interface accompanied by more "how to" coverage of graphical techniques unique to Amos.More explanation of key procedures and analyses that address questions posed by readers All application data files are available at www.routledge.com/9781138797031.The two introductory chapters in Section 1 review the fundamental concepts of SEM methodology and a general overview of the Amos program. Section 2 provides single-group analyses applications including two first-order confirmatory factor analytic (CFA) models, one second-order CFA model, and one full latent variable model. Section 3 presents multiple-group analyses applications with two rooted in the analysis of covariance structures and one in the analysis of mean and covariance structures. Two models that are increasingly popular with SEM practitioners, construct validity and testing change over time using the latent growth curve, are presented in Section 4. The book concludes with a review of the use of bootstrapping to address non-normal data and a review of missing (or incomplete) data in Section 5. An ideal supplement for graduate level courses in psychology, education, business, and social and health sciences that cover the fundamentals of SEM with a focus on Amos, this practical text continues to be a favorite of both researchers and practitioners. A prerequisite of basic statistics through regression analysis is recommended but no exposure to either SEM or Amos is required.

Table of Contents

Preface                                            xvi
Acknowledgments xxi
About the Author xxii
Section I Introduction
Chapter 1 Structural Equation Modeling: The 3 (13)
Basics
Key Concepts 3 (1)
What Is Structural Equation Modeling? 3 (1)
Basic Concepts 4 (5)
Latent versus Observed Variables 4 (1)
Exogenous versus Endogenous Latent 5 (1)
Variables
The Factor Analytic Model 5 (2)
The Full Latent Variable Model 7 (1)
General Purpose and Process of 7 (2)
Statistical Modeling
The General Structural Equation Model 9 (6)
Symbol Notation 9 (1)
The Path Diagram 10 (1)
Structural Equations 11 (1)
Nonvisible Components of a Model 12 (1)
Basic Composition 13 (1)
The Formulation of Covariance and Mean 14 (1)
Structures
Notes 15 (1)
Chapter 2 Using the Amos Program 16 (53)
Key Concepts 16 (2)
Model Specification Using Amos Graphics 18 (15)
(Example 1)
Amos Modeling Tools 19 (4)
The Hypothesized Model 23 (1)
Drawing the Path Diagram 23 (10)
Model Specification Using Amos Tables 33 (10)
View (Example 1)
Understanding the Basic Components of 40 (1)
Model 1
The Concept of Model Identification 40 (3)
Model Specification Using Amos Graphics 43 (8)
(Example 2)
The Hypothesized Model 43 (3)
Drawing the Path Diagram 46 (5)
Model Specification Using Amos Tables 51 (2)
View (Example 2)
Model Specification Using Amos Graphics 53 (5)
(Example 3)
The Hypothesized Model 54 (1)
Drawing the Path Diagram 55 (3)
Changing the Amos Default Color for 58 (3)
Constructed Models
Model Specification Using Amos Tables 61 (2)
View (Example 3)
Notes 63 (6)
Section II Single-Group Analyses
Confirmatory Factor Analytic Models
Chapter 3 Application 1: Testing the 69 (46)
Factorial Validity of a Theoretical
Construct (First-Order CFA Model)
Key Concepts 69 (1)
The Hypothesized Model 70 (1)
Hypothesis 1 Self-concept is a 4-Factor 70 (5)
Structure
Modeling with Amos Graphics 75 (32)
Model Specification 75 (1)
Data Specification 75 (3)
Calculation of Estimates 78 (3)
Amos Text Output: Hypothesized 4-Factor 81 (1)
Model
Model Summary 81 (1)
Model Variables and Parameters 82 (1)
Model Evaluation 82 (2)
Parameter Estimates 84 (2)
Model as a Whole 86 (16)
Model Misspecification 102 (5)
Post Hoc Analyses 107 (1)
Hypothesis 2 Self-concept is a 2-Factor 108 (2)
Structure
Selected Amos Text Output: Hypothesized 110 (1)
2-Factor Model
Hypothesis 3 Self-concept is a 1-Factor 110 (1)
Structure
Modeling with Amos Tables View 111 (2)
Notes 113 (2)
Chapter 4 Application 2: Testing the 115 (34)
Factorial Validity of Scores from a
Measurement Scale (First-Order CFA Model)
Key Concepts 115 (1)
Modeling with Amos Graphics 115 (2)
The Measuring Instrument under Study 116 (1)
The Hypothesized Model 117 (14)
Selected Amos Output: The Hypothesized 119 (7)
Model
Model Evaluation 126 (5)
Post Hoc Analyses 131 (1)
Model 2 132 (4)
Selected Amos Output: Model 2 132 (4)
Model 3 136 (3)
Selected Amos Output: Model 3 136 (3)
Model 4 139 (7)
Selected Amos Output: Model 4 139 (6)
Comparison with Robust Analyses Based 145 (1)
on the Satorra--Bentler Scaled Statistic
Modeling with Amos Tables View 146 (2)
Notes 148 (1)
Chapter 5 Application 3: Testing the 149 (36)
Factorial Validity of Scores from a
Measurement Scale (Second-Order CFA Model)
Key Concepts 149 (1)
The Hypothesized Model 150 (2)
Modeling with Amos Graphics 152 (11)
Selected Amos Output File: Preliminary 155 (6)
Model
Selected Amos Output: The Hypothesized 161 (1)
Model
Model Evaluation 161 (2)
Estimation Based on Continous Versus 163 (7)
Categorical Data
Categorical Variables Analyzed as 167 (1)
Continuous Variables
Categorical Variables Analyzed as 168 (2)
Categorical Variables
The Amos Approach to Analysis of 170 (10)
Categorical Variables
What is Bayesian Estimation? 171 (1)
Application of Bayesian Estimation 171 (9)
Modeling with Amos Tables View 180 (2)
Note 182 (3)
Full Latent Variable Model
Chapter 6 Application 4: Testing the 185 (42)
Validity of a Causal Structure
Key Concepts 185 (1)
The Hypothesized Model 186 (1)
Modeling with Amos Graphics 187 (16)
Formulation of Indicator Variables 187 (2)
Confirmatory Factor Analyses 189 (8)
Selected Amos Output: Hypothesized Model 197 (2)
Model Assessment 199 (4)
Post Hoc Analyses 203 (16)
Selected Amos Output: Model 2 203 (1)
Model Assessment 203 (1)
Selected Amos Output: Model 3 204 (1)
Model Assessment 204 (1)
Selected Amos Output: Model 4 205 (1)
Model Assessment 205 (1)
Selected Amos Output: Model 5 206 (1)
Model Assessment 206 (2)
Selected Amos Output: Model 6 208 (1)
Model Assessment 208 (1)
The Issue of Model Parsimony 208 (2)
Selected Amos Output: Model 7 (Final 210 (1)
Model)
Model Assessment 210 (2)
Parameter Estimates 212 (7)
Modeling with Amos Tables View 219 (2)
Notes 221 (6)
Section III Multiple-Group Analyses
Confirmatory Factor Analytic Models
Chapter 7 Application 5: Testing Factorial 227 (36)
Invariance of Scales from a Measurement
Scale (First-Order CFA Model)
Key Concepts 227 (2)
Testing For Multigroup Invariance 229 (1)
The General Notion 229 (1)
The Testing Strategy 230 (1)
The Hypothesized Model 230 (5)
Establishing Baseline Models: The 231 (1)
General Notion
Establishing the Baseline Models: 231 (4)
Elementary and Secondary Teachers
Modeling with Amos Graphics 235 (3)
Hierarchy of Steps in Testing Multigroup 238 (23)
Invariance
I Testing for Configural Invariance 238 (2)
Selected Amos Output: The Configural 240 (4)
Model (No Equality Constraints Imposed)
II Testing for Measurement and 244 (8)
Structural Invariance: The
Specification Process
III Testing for Measurement and 252 (1)
Structural Invariance: Model Assessment
Testing For Multigroup Invariance: The 253 (1)
Measurement Model
Model Assessment 253 (8)
Testing For Multigroup Invariance: The 261 (1)
Structural Model
Notes 261 (2)
Chapter 8 Application 6: Testing Invariance 263 (30)
of Latent Mean Structures (First-Order CFA
Model)
Key Concepts 263 (1)
Basic Concepts Underlying Tests of Latent 264 (3)
Mean Structures
Estimation of Latent Variable Means 266 (1)
The Hypothesized Model 267 (2)
The Baseline Models 269 (1)
Modeling with Amos Graphics 269 (2)
The Structured Means Model 269 (2)
Testing for Latent Mean Differences 271 (18)
The Hypothesized Multigroup Model 271 (1)
Steps in the Testing Process 271 (8)
Selected Amos Output: Model Summary 279 (2)
Selected Amos Output: Goodness-of-fit 281 (2)
Statistics
Selected Amos Output: Parameter 283 (6)
Estimates
Notes 289 (4)
Full Latent Variable Model
Chapter 9 Application 7: Testing Invariance 293 (18)
of a Causal Structure (Full Structural
Equation Model)
Key Concepts 293 (1)
Cross-Validation in Covariance Structure 293 (3)
Modeling
Testing for Invariance across 296 (1)
Calibration/Validation Samples
The Hypothesized Model 296 (7)
Establishing a Baseline Model 298 (5)
Modeling with Amos Graphics 303 (8)
Testing for the Invariance of Causal 303 (2)
Structure Using the Automated
Multigroup Approach
Selected Amos Output: Goodness-of-fit 305 (6)
Statistics for Comparative Tests of
Multigroup Invariance
Section IV Other Important Applications
Chapter 10 Application 8: Testing Evidence 311 (28)
of Construct Validity: The
Multitrait-Multimethod Model
Key Concepts 311 (2)
The Correlated Traits-Correlated Methods 313 (14)
Approach to MTMM Analyses
Model 1 Correlated Traits-Correlated 315 (5)
Methods
Model 2 No Traits-Correlated Methods 320 (2)
Model 3 Perfectly Correlated 322 (4)
Traits-Freely Correlated Methods
Model 4 Freely Correlated 326 (1)
Traits-Uncorrelated Methods
Testing for Evidence of Convergent and 327 (1)
Discriminant Validity: MTMM Matrix-level
Analyses
Comparison of Models 327 (1)
Evidence of Convergent Validity 327 (1)
Evidence of Discriminant Validity 327 (1)
Testing for Evidence of Convergent and 328 (3)
Discriminant Validity: MTMM
Parameter-level Analyses
Examination of Parameters 328 (1)
Evidence of Convergent Validity 329 (2)
Evidence of Discriminant Validity 331 (1)
The Correlated Uniquenesses Approach to 331 (7)
MTMM Analyses
Model 5 Correlated Uniqueness Model 335 (3)
Notes 338 (1)
Chapter 11 Application 9: Testing Change 339 (26)
Over Time: The Latent Growth Curve Model
Key Concepts 339 (2)
Measuring Change in Individual Growth 341 (1)
over Time: The General Notion
The Hypothesized Dual-domain LGC Model 341 (5)
Modeling Intraindividual Change 341 (4)
Modeling Interindividual Differences in 345 (1)
Change
Testing Latent Growth Curve Models: A 346 (8)
Dual-Domain Model
The Hypothesized Model 346 (4)
Selected Amos Output: Hypothesized Model 350 (4)
Testing Latent Growth Curve Models: 354 (7)
Gender as a Time-invariant Predictor of
Change
Notes 361 (4)
Section V Other Important Topics
Chapter 12 Application 10: Use of 365 (28)
Bootstrapping in Addressing Nonnormal Data
Key Concepts 365 (3)
Basic Principles Underlying the Bootstrap 368 (2)
Procedure
Benefits and Limitations of the 369 (1)
Bootstrap Procedure
Caveats Regarding the Use of 369 (1)
Bootstrapping in SEM
Modeling with Amos Graphics 370 (5)
The Hypothesized Model 371 (1)
Characteristics of the Sample 371 (2)
Applying the Bootstrap Procedure 373 (2)
Selected Amos Output 375 (17)
Parameter Summary 375 (1)
Assessment of Normality 376 (2)
Parameter Estimates and Standard Errors 378 (14)
Note 392 (1)
Chapter 13 Application 11: Addressing the 393 (14)
Issues of Missing Data
Key Concepts 393 (1)
Basic Patterns of Missing Data 394 (2)
Common Approaches to Handling Incomplete 396 (4)
Data
Ad Hoc Approaches to Handling Missing 396 (3)
Data (Not recommended)
Theory-based Approaches to Handling 399 (1)
Missing Data (Recommended)
The Amos Approach to Handling Missing Data 400 (1)
Modeling with Amos Graphics 401 (5)
The Hypothesized Model 401 (3)
Selected Amos Output: Parameter and 404 (1)
Model Summary Information
Selected Amos Output: Parameter 405 (1)
Estimates
Selected Amos Output: Goodness-of-fit 406 (1)
Statistics
Note 406 (1)
References407 (21)
Author Index 428 (5)
Subject Index 433