Structural Equation Modeling With EQS : Basic Concepts, Applications, and Programming, Second Edition

ISBN-13: 9780805841251 / Angielski / Twarda / 2006 / 440 str.

Barbara M. Byrne

Opis

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.

Spis treści

Contents: Part I: Introduction. Structural Equation Models: The Basics. Using the EQS Program. Part II: Single-Group Analyses. Application 1: Testing for the Factorial Validity of a Theoretical Construct (First-Order CFA Model). Application 2: Testing for the Factorial Validity of Scores From a Measuring Instrument (First-Order CFA Model). Application 3: Testing for the Factorial Validity of Scores from a Measuring Instrument (Second-Order CFA Model). Application 4: Testing for the Validity of a Causal Structure. Part III: Multiple-Group Analyses. Application 5: Testing for the Factorial Invariance of a Measuring Instrument. Application 6: Testing for the Invariance of a Causal Structure. Application 7: Testing for Latent Mean Differences (First-Order CFA Model). Application 8: Testing for Latent Mean Differences (Second-Order CFA Model). Part IV: Other Important Topics. Application 9: Testing for Construct Validity: The Multitrait-Multimethod Model. Application 10: Testing for Change Over Time: The Latent Growth Curve Model. Application 11: Testing for Within- and Between-Level Variance: The Multilevel Model.

O autorze

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. Byrne’s research focuses on construct validity issues as they relate to theoretical constructs and measuring instruments. She is the author of　　7 popular introductory books on SEM　and 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.