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Structural equation modeling with Mplus : basic concepts, applications, and programming / Barbara M. Byrne

Main Author Byrne, Barbara M., 1935- Country Estados Unidos. Publication New York : Routledge, cop. 2012 Description XVI, 412 p. : il. ; 23 cm Series Multivariate applications series ISBN 978-1-84872-839-4 CDU 519.2 303.7 681.3.06
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Holdings
Item type Current location Call number Status Date due Barcode Item holds
Monografia Biblioteca Geral da Universidade do Minho
BGUM 519.2 - B Available 416047
Total holds: 0

Enhanced descriptions from Syndetics:

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 at http://www.psypress.com/sem-with-mplus/datasets .

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.

Table of contents provided by Syndetics

  • Preface (p. xi)
  • Acknowledgments (p. xvii)
  • Section I Introduction
  • Chapter 1 Structural Equation Models: The Basics (p. 3)
  • Basic Concepts (p. 4)
  • The General Structural Equation Model (p. 9)
  • The General Mplus Structural Equation Model (p. 15)
  • Notes (p. 17)
  • Chapter 2 Using the Mplus Program (p. 19)
  • Mplus Notation and Input File Components and Structure (p. 19)
  • The Mplus Language Generator (p. 26)
  • Model Specification From Two Perspectives (p. 27)
  • The Concept of Model Identification (p. 31)
  • Overview of Remaining Chapters (p. 39)
  • Notes (p. 40)
  • Section II Single-Group Analyses
  • Chapter 3 Testing the Factorial Validity of a Theoretical Construct: First-Order Confirmatory Factor Analysis Model (p. 43)
  • The Hypothesized Model (p. 43)
  • Mplus Input File Specification and Output File Results (p. 48)
  • Hypothesis 2: Self-Concept Is a Two-Factor Structure (p. 89)
  • Mplus Input File Specification and Output File Results (p. 89)
  • Hypothesis 3: Self-Concept Is a One-Factor Structure (p. 91)
  • Notes (p. 93)
  • Chapter 4 Testing the Factorial Validity of Scores From a Measuring Instrument: First-Order Confirmatory Factor Analysis Model (p. 95)
  • The Measuring Instrument Under Study (p. 96)
  • The Hypothesized Model (p. 96)
  • Mplus Input File Specification and Output File Results (p. 101)
  • Notes (p. 121)
  • Addendum (p. 122)
  • Chapter 5 Testing the Factorial Validity of Scores From a Measuring Instrument: Second-Order Confirmatory Factor Analysis Model (p. 125)
  • The Hypothesized Model (p. 126)
  • Analysis of Categorical Data (p. 126)
  • Mplus Input File Specification and Output File Results (p. 133)
  • Notes (p. 146)
  • Chapter 6 Testing the Validity of a Causal Structure: Full Structural Equation Model (p. 147)
  • The Hypothesized Model (p. 147)
  • Mplus Input File Specification and Output File Results (p. 153)
  • Post Hoc Analyses (p. 168)
  • Notes (p. 188)
  • Section III Multiple-Group Analyses
  • Chapter 7 Testing the Factorial Equivalence of a Measuring Instrument: Analysis of Covariance Structures (p. 193)
  • Testing Multigroup Invariance: The General Notion (p. 194)
  • Testing Multigroup Invariance Across Independent Samples (p. 197)
  • The Hypothesized Model (p. 197)
  • Mplus Input File Specification and Output File Results (p. 208)
  • Notes (p. 226)
  • Chapter 8 Testing the Equivalence of Latent Factor Means: Analysis of Mean and Covariance Structures (p. 227)
  • Testing Latent Mean Structures: The Basic Notion (p. 227)
  • The Hypothesized Model (p. 231)
  • Testing Multigroup Invariance (p. 231)
  • Mplus Input File Specification and Output File Results (p. 241)
  • Testing Multigroup Invariance: Other Considerations (p. 254)
  • Notes (p. 257)
  • Chapter 9 Testing the Equivalence of a Causal Structure: Full Structural Equation Model (p. 259)
  • Cross-Validation in Structural Equation Modeling (p. 259)
  • Testing Invariance Across Calibration and Validation Samples (p. 261)
  • The Hypothesized Model (p. 262)
  • Mplus Input File Specification and Output File Results (p. 264)
  • Notes (p. 282)
  • Section IV Other Important Topics
  • Chapter 10 Testing Evidence of Construct Validity: The Multitrait-Multimethod Model (p. 285)
  • The General CFA Approach to MTMM Analyses (p. 286)
  • The Hypothesized Model (p. 287)
  • Mplus Input File Specification and Output File Results (p. 288)
  • Examining Evidence of Construct Validity at the Matrix Level (p. 295)
  • Examining Evidence of Construct Validity at the Parameter Level (p. 301)
  • The Correlated Uniquenesses Approach to MTMM Analyses (p. 303)
  • Notes (p. 311)
  • Chapter 11 Testing Change Over Time: The Latent Growth Curve Model (p. 313)
  • Measuring Change in Individual Growth Over Time: The General Notion (p. 316)
  • The Hypothesized Dual-Domain LGC Model (p. 316)
  • Mplus Input File Specification and Output File Results (p. 321)
  • Hypothesized Covariate Model: Age and Surgery as Predictors of Change (p. 338)
  • Notes (p. 344)
  • Chapter 12 Testing Within- and Between-Level Variability: The Multilevel Model (p. 345)
  • Overview of Multilevel Modeling (p. 346)
  • The Hypothesized Model (p. 350)
  • Mplus Input File Specification and Output File Results (p. 354)
  • Notes (p. 371)
  • References (p. 373)
  • Author Index (p. 395)
  • Subject Index (p. 401)

Author notes provided by Syndetics

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.

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