Structural Equation Modeling with Mplus

"Barbara Byrne has published another winner--a practically oriented, thorough, and accessible resource for students and researchers who want to harness the power of Mplus for their SEM analyses. The writing is clear and engaging. I anticipate assigning the book in my graduate SEM course and recommending it to fellow researchers. This book will be a valuable resource for moving from knowing about SEM to using it." - Rick H. Hoyle, Duke University, USA "This book provides a good starting point to newcomers to Mplus. It focuses, as it should for an introductory text, on the basics of 'classical' SEM. If you are new to SEM, plan on using Mplus, and are looking for an introductory text with minimal statistical jargon, this is it." - Albert Maydeu-Olivares, University of Barcelona, Spain "A solid introduction to the use of Mplus for SEM. All of the common types of structural equation models are illustrated using real examples, building the Mplus syntax from start to finish. The book is an excellent and readable guide for researchers and students who want to learn more about SEM in the context of Mplus." - Roger E. Millsap, Arizona State University, USA "A hallmark of Byrne's booksis their accessibility to new users. Byrne has done a great service to the field by bringing thousands of students and researchers to structural equation modeling through her clear writing and accessible examples. This book will be another contribution along those same lines. .... I field many, many questions that could be answered by simply referring the asker to a book like Byrne's." - Kristopher J. Preacher, University of Kansas, USA "The book is targeted to non-mathematical readers, and hence it focuses on the applications of SEM. It does this very nicely, beginning from the part that covers the basic ideas of SEM and shows how to get started with the Mplus. Overall, this book is an excellent resource for a beginner interested in SEM with Mplus." -Kimmo Vehkalahti, Department of Social Research, Statistics, University of Helsinki, Finland "Through the use of illustrative examples, this much-needed and well-written book provides an accessible presentation of SEM with Mplus. Those new to SEM and/or Mplus will find Byrne's book extremely useful as a companion textbook and long-term reference guide." - Sara J. Finney, James Madison University, USA

Auteur

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.

Texte du rabat

First Published in 2012. Routledge is an imprint of Taylor & Francis, an informa company.

Résumé

Modeled after Barbara Byrne's other best-selling structural equation modeling (SEM) books, this practical guide reviews the basic concepts and applications of SEM using Mplus Versions 5 & 6. The author reviews SEM applications based on actual data taken from her own research. Using non-mathematical language, it is written for the novice SEM user. With each application chapter, the author "walks" the reader through all steps involved in testing the SEM model including:

• an explanation of the issues addressed
• illustrated and annotated testing of the hypothesized and post hoc models
• explanation and interpretation of all Mplus input and output files
• important caveats pertinent to the SEM application under study
• a description of the data and reference upon which the model was based
• the corresponding data and syntax files available under "Supplementary Material" below The first two chapters introduce the fundamental concepts of SEM and important basics of the Mplus program. The remaining chapters focus on SEM applications and include a variety of SEM models presented within the context of three sections: Single-group analyses, Multiple-group analyses, and other important topics, the latter of which includes the multitrait-multimethod, latent growth curve, and multilevel models.

Intended for researchers, practitioners, and students who use SEM and Mplus, this book is an ideal resource for graduate level courses on SEM taught in psychology, education, business, and other social and health sciences and/or as a supplement for courses on applied statistics, multivariate statistics, intermediate or advanced statistics, and/or research design. Appropriate for those with limited exposure to SEM or Mplus, a prerequisite of basic statistics through regression analysis is recommended.

Contenu

Part 1: Introduction. 1. Structural Equation Models: The Basics. 2. Using the Mplus Program. Part 2: Single-Group Analyses. Confirmatory Factor Analytic Models 3. Testing the Factorial Validity of a Theoretical Construct (1st-order CFA Model). 4. Testing the Factorial Validity of Scores from a Measuring Instrument (1st-order CFA Model). 5. Testing the Validity of Scores from a Measuring Instrument (2nd-order CFA Model). The Full Latent Variable Model 6. Testing the Validity of a Causal Structure. Part 3: Multiple-Group Analyses. Confirmatory Factor Analytic Models 7. Testing for the Factorial Equivalence of a Measuring Instrument (Analysis of Covariance Structures). 8. Testing for the Equivalence of Latent Factor Means (Analysis of Mean and Covariance Structures). The Full Latent Variable Model 9. Testing for the Equivalence of a Causal Structure (Analysis of Covariance Structures). Part 4: Other Important Topics. 10. Testing Evidence of Construct Validity: The Multitrait-multimethod Model. 11. Testing Change Over Time: The Latent Growth Curve Model. 12. Testing Within- and Between-level Variability: The Multilevel Model.