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El. knyga: Structural Equation Modeling With EQS: Basic Concepts, Applications, and Programming, Second Edition 2nd edition [Taylor & Francis e-book]

(University of Ottawa, Canada)
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Structural Equation Modeling With EQS: Basic Concepts, Applications, and Programming, Second Edition 2nd editionDidesnis paveikslėlis
Kitos knygos pagal šią temą:
Taylor & Francis e-booksMore info about Taylor & Francis e-books
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Researchers and students who want a less mathematical alternative to the EQS manual will find exactly what they're looking for in this practical text. Written specifically for those with little to no knowledge of structural equation modeling (SEM) or EQS, the author's goal is to provide a non-mathematical introduction to the basic concepts of SEM by applying these principles to EQS, Version 6.1. The book clearly demonstrates a wide variety of SEM/EQS applications that include confirmatory factor analytic and full latent variable models. Analyses are based on a wide variety of data representing single and multiple-group models; these include data that are normal/non-normal, complete/incomplete, and continuous/categorical.


Written in a "user-friendly" style, the author "walks" the reader through the varied steps involved in the process of testing SEM models. These include model specification and estimation, assessment of model fit, description of EQS output, and interpretation of findings. Each of the book's applications is accompanied by: a statement of the hypothesis being tested, a schematic representation of the model, explanations and interpretations of the related EQS input and output files, tips on how to use the associated pull-down menus and icons, and the data file upon which the application is based. Beginning with an overview of the basic concepts of SEM and the EQS program, the book carefully works through applications starting with relatively simple single group analyses, through to more advanced applications, such as a multi-group, latent growth curve, and multilevel modeling.


The new edition features:

*Many new applications that include a latent growth curve model, a multilevel model, a second-order model based on categorical data, a missing data multigroup model based on the EM algorithm, and the testing for latent mean differences related to a higher-order model.

*A CD enclosed with the book that includes all application data.

*Vignettes illustrating procedural and/or data management tasks using a Windows interface.

*Description of how to build models both interactively using the BUILDULEQ interface and graphically using the EQS Diagrammer.


This practical volume is intended for researchers and students who want a less technical alternative to the EQS manual.
Preface and Acknowledgments ix
I: INTRODUCTION
Structural Equation Models: The Basics
3(15)
Basic Concepts
4(5)
The General Structural Equation Model
9(5)
The General EQS Structural Equation Model
14(4)
Using the EQS Program
18(59)
Components of the EQS Input File
19(18)
The Concept of Model Identification
30(7)
Creating the EQS Input File
37(34)
Building an Input File Manually
36(2)
Building an Input File Interactively Using BUILD_EQS
38(10)
Building an Input File Graphically Using the Diagrammer
48(23)
The EQS Output File in General
71(2)
EQS Error Messages
73(1)
Overview of Remaining
Chapters
74(3)
II: SINGLE-GROUP ANALYSES
Application 1: Testing for the Factorial Validity of a Theoretical Construct (First-Order CFA Model)
77(41)
The Hypothesized Model
78(4)
The EQS Input File
82(4)
The EQS Output File
86(26)
Model Specification and Analysis Summary
87(2)
Model Assessment
89(19)
Model Misspecification
108(4)
Post Hoc Analyses
112(6)
Application 2: Testing for the Factorial Validity of Scores From a Measuring Instrument (First-Order CFA Model)
118(40)
The Hypothesized Model
119(8)
The EQS Input File
127(2)
The EQS Output File
129(8)
Post Hoc Analyses
137(21)
Application 3: Testing for the Factorial Validity of Scores From a Measuring Instrument (Second-Order CFA Model)
158(28)
The Hypothesized Model
159(4)
Analysis of Categorical Data
163(4)
Categorical Variables Analyzed as Continuous Variables
163(1)
Categorical Variables Analyzed as Categorical Variables
164(3)
Analyses Based on Data Regarded as Categorical
167(1)
The EQS Input File
167(3)
The EQS Output File
170(6)
Post Hoc Analyses
176(3)
Analyses Based on Data Regarded as Continuous
179(7)
The EQS Output File
179(7)
Application 4: Testing for the Validity of a Causal Structure
186(39)
The Hypothesized Model
186(5)
Formulation of Indicator Variables
188(1)
Confirmatory Factor Analyses
189(2)
The EQS Input File
191(8)
The EQS Output File
199(6)
Post Hoc Analyses
205(20)
III: MULTIPLE-GROUP ANALYSES
Application 5: Testing for the Factorial Invariance a Measuring Instrument
225(25)
Testing for Multigroup Invariance
226(2)
Testing for Invariance Across Independent Samples
228(1)
The Hypothesized Model
228(6)
The EQS Input File
234(3)
The EQS Output File
237(8)
Other Considerations in Testing for Multiple Group Invariance
245(5)
Application 6: Testing for the Invariance of a Causal Structure
250(11)
Cross-Validation in SEM
250(2)
Testing for Invariance Across Calibration/Validation Samples
252(1)
The Hypothesized Model
253(1)
The EQS Input File
253(6)
The EQS Output File
259(2)
Application 7: Testing for Latent Mean Differences (First-Order CFA Model)
261(32)
Basic Concepts Underlying Tests of Latent Mean Structures
262(1)
Modeling Mean Structures in EQS
263(4)
Testing for Latent Mean Differences of a First-Order CFA Model
267(1)
The Strategy
267(1)
The Hypothesized Model
267(7)
The EQS Input File
274(3)
The EQS Output File
277(16)
Application 8: Testing for Latent Mean Differences (Second-Order CFA Model)
293(32)
Testing for Latent Mean Differences of a Second-Order Model
294(1)
The Strategy
294(1)
The Hypothesized Model
294(31)
IV: OTHER IMPORTANT TOPICS
Application 9: Testing for Construct Validity: The Multitrait-Multimethod Model
325(27)
The General CFA Approach to MTMM Analyses
330(1)
The Hypothesized Model
330(2)
The EQS Input File
332(1)
The EQS Output File
332(12)
The Correlated Uniqueness Approach to MTMM Analyses
344(2)
The Hypothesized Model
346(2)
The EQS Input File
348(1)
The EQS Output File
348(4)
Application 10: Testing for Change Over Time: The Latent Growth Curve Model
352(24)
Measuring Change in Individual Growth Over Time: The General Notion
354(1)
The Hypothesized Model
354(8)
Modeling Intraindividual Change
354(4)
Modeling Inter-individual Differences in Change
358(1)
Testing for Inter-individual Differences in Change
359(3)
The EQS Input File
362(1)
The EQS Output File
362(8)
Gender as a Time-Invariant Predictor of Change
370(3)
The EQS Input File
373(1)
The EQS Output File
373(3)
Application 11: Testing for Within- and Between-Level Variance: The Multilevel Model
376(35)
Overview of Multilevel Modeling
377(2)
Single-Level Analyses of Hierarchically Structured Data: Related Problems
377(1)
Multiple Level Analyses of Hierarchically Structured Data: Multilevel Modeling
378(1)
The Hypothesized Model
379(12)
The EQS Input File
391(5)
The EQS Output File
396(15)
References 411(14)
Author Index 425(4)
Subject Index 429


Barbara M. Byrne is Professor Emeritus in the School of Psychology, University of Ottawa, Canada. An internationally recognized expert in the area of SEM, Dr. Byrnes research focuses on construct validity issues as they relate to theoretical constructs and measuring instruments. She is the author of7 popular introductory books on SEMand has conducted over 100 SEM workshops at conferences, universities, and test publishers around the globe. In addition to the publication of over 95 book chapters and scholarly journal articles, most of which have addressed SEM application issues, she is the author of an important reference book, Measuring Self-concept Across the Lifespan: Issues and Instrumentation. Dr. Byrne is the recipient of three Distinguished Teaching Awards presented by the Canadian Psychological Association, the American Psychological Association (APA), and the APA, Division 5 (Jacob Cohen Award). She is a Fellow in two APA Divisions, is a Foundation member on the International Board of the SELF Research Centre, University of Western Sydney, Australia, and is an elected member of the Society of Multivariate Experimental Psychology.
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