Principles and Practice of Structural Equation Modeling, Third Edition / Edition 3

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Overview

Designed for researchers and students without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in psychology and the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the author offers clear instructions on the preparation and screening of data, common mistakes to avoid, and features of widely used software programs (Amos, EQS, and LISREL). Readers will acquire the skills necessary to begin to use SEM in their own research, and to interpret and critique the use of the method by others, making this a valuable text for students of psychology, communication sciences, education, sociology, and related fields.

The book contains black-and-white illustrations.

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Editorial Reviews

From the Publisher

"I would strongly recommend this book for use as a primary text in any SEM course. It offers a clear, applied presentation of complicated SEM techniques for a wide array of audiences with various abilities. The text would be beneficial for students with a limited background in theoretical statistics, as well as those with a strong understanding of the theoretical underpinnings of SEM. I often refer to this text in my everyday work, due to the clarity with which the material is presented."--Greg Welch, PhD, Nebraska Center for Research on Children, Youth, Families, and Schools, University of Nebraska-Lincoln

"The skill and knowledge sets for evaluating and using SEM have become important components of social science education. Kline provides a text that is accessible for graduate students, practitioners, and researchers who are not intimately familiar with SEM techniques. In addition, he effortlessly summarizes current information that researchers who already use SEM should have. The reorganization of the material, new topic boxes, new Web page, and updated technical information enhance an already great resource. A major strength of the book is the individual chapter examples with explanation of the values provided from a variety of statistical analysis packages. I will continue to use this third edition as the primary text in my SEM course, and highly recommend it as both a text and a technical resource."--James B. Schreiber, PhD, Center for Advancing the Study of Teaching and Learning, Duquesne University 

"In the third edition, Kline has improved the pedagogical value of his book relative to prior editions and to other SEM books. The many exercises help a reader understand how to apply important chapter concepts, making the book not only useful for an SEM course, but also an effective resource for self-study. The Web page featuring complete computer syntax and data for the examples is very helpful. Other new material further supports a reader’s understanding of SEM; for example, Chapter 2 provides more information on multiple regression/correlation, and the chapter on data preparation has been expanded to cover important topics such as positive-definite matrices, which are among the most common problems researchers experience when using SEM. This edition also provides more information on available SEM software, including an entire chapter on the use of computer software."--Craig Wells, PhD, School of Education, University of Massachusetts-Amherst
 

"Chapters 2 and 3 review important concepts in multiple regression and data screening, both of which are critical to understand before learning SEM. From an instructor's perspective, I enjoyed reading these chapters very much. They are well written, logically organized, and easy to follow. Another strength of the book is the thorough and comprehensive reference list on various topics."--Duan Zhang, PhD, College of Education, University of Denver
 

"I am excited about this book. The coverage is excellent and the writing style is friendly and direct, with a subtle humor that I find refreshing. I especially like the new topic boxes in the third edition, most of which discuss issues that I have had to address separately in lectures."--Jacob Marszalek, PhD, Division of Counseling and Educational Psychology, University of Missouri-Kansas City
 
"If you didn't think a statistics text could be riveting, read this book! The first chapter covers basic statistical concepts in better detail and more clearly than other texts that are meant to be general introductions. Discussing extremely helpful articles that have examined SEM research, Kline identifies and provides empirical evidence of potential problems with using and reporting SEM. This helps readers understand what to do (and what not to do) from the very beginning. I love it that one of the goals is to help readers avoid common mistakes in SEM."--Debbie Hahs-Vaughn, PhD, Department of Educational Research, Technology, and Leadership, University of Central Florida
 

"This is now the #1 book I will recommend to students and substantive researchers (who are not quantitative specialists) who want to learn SEM! Compared to most SEM books that I have seen, this one strikes a better balance between accessibility and breadth. In the third edition, Kline not only has updated the material, but has substantially improved it. He adds more depth to certain topics--such as estimation, in Chapter 7--and covers some intermediate-to-advanced topics not described in the previous edition, all at a level appropriate for beginners."--Noel A. Card, PhD, Division of Family Studies and Human Development, University of Arizona
 

"A terrific introduction to SEM. Kline offers some of the basics and does so in a way that is quite approachable for students. I have recommended this text to a number of people who were just beginning to use SEM, and will continue to do so."--R. Lance Holbert, PhD, School of Communications, Ohio State University

"Of all the introductory SEM texts, this one is the most interesting to read. Anyone who has taken a course in basic algebra or introductory statistics will be able to understand the ideas and work through the exercises, and those who work their way through the book will have a good foundation in SEM and will be able to use it effectively."--David F. Gillespie, PhD, George Warren Brown School of Social Work, Washington University in St. Louis

Booknews
Offers a guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in the social sciences, for students and researchers without extensive quantitative background. Covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data. Gives instructions on preparation and screening of data, and discusses widely used software programs. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

  • ISBN-13: 9781606238776
  • Publisher: Guilford Publications, Inc.
  • Publication date: 8/19/2010
  • Series: Methodology In The Social Sciences Series
  • Edition description: Third Edition
  • Edition number: 3
  • Pages: 427
  • Product dimensions: 7.10 (w) x 10.10 (h) x 1.00 (d)

Meet the Author

Rex B. Kline is Professor of Psychology at Concordia University in Montréal, Québec, Canada. Since earning a doctorate in clinical psychology, he has conducted research on the psychometric evaluation of cognitive abilities, child clinical assessment, structural equation modeling, training of behavioral science researchers, and usability engineering in computer science. Dr. Kline has published five books, six chapters, and more than 40 articles in research journals.

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Table of Contents

I. Concepts and Tools
1. Introduction
The Book's Website
Pedagogical Approach
Getting Ready to Learn about SEM
Characteristics of SEM
Widespread Enthusiasm, but with a Cautionary Tale
Family History and a Reminder about Context
Extended Latent Variable Families
Plan of the Book
Summary
2. Fundamental Concepts
Multiple Regression
Partial Correlation and Part Correlation
Other Bivariate Correlations
Logistic Regression
Statistical Tests
TOPIC BOX 2.1. The "Big Five" Misinterpretations of Statistical Significance
Bootstrapping
Summary
Recommended Readings
Exercises
3. Data Preparation
Forms of Input Data
Positive Definiteness
TOPIC BOX 3.1. Causes of Nonpositive Definiteness and Solutions
Data Screening
Selecting Good Measures and Reporting about Them
Summary
Recommended Readings
Exercises
4. Computer Tools
Ease of Use, Not Suspension of Judgment
Human-Computer Interaction
TOPIC BOX 4.1. Graphical Isn't Always Better
Core SEM Programs and Book Website Resources
Other Computer Tools
Summary
Recommended Readings
II. Core Techniques
5. Specification
Steps of SEM
Model Diagram Symbols
Specification Concepts
Path Analysis Models
CFA Models
Structural Regression Models
Exploratory SEM
Summary
Recommended Readings
Exercises
6. Identification
General Requirements
Unique Estimates
Rule for Recursive Structural Models
Rules for Nonrecursive Structural Models
Rules for Standard CFA Models
Rules for Nonstandard CFA Models
Rules for SR Models
A Healthy Perspective on Identification
Empirical Underidentification
Managing Identification Problems
Summary
Recommended Readings
Exercises
APPENDIX 6.A. Evaluation of the Rank Condition
7. Estimation
Maximum Likelihood Estimation
TOPIC BOX 7.1. Two-Stage Least Squares Estimation
Detailed Example
Brief Example with a Start Value Problem
Fitting Models to Correlation Matrices
Alternative Estimators
A Healthy Perspective on Estimation
Summary
Recommended Readings
Exercises
APPENDIX 7.A. Start Value Suggestions for Structural Models
APPENDIX 7.B. Effect Decomposition in Nonrecursive Models and the Equilibrium Assumption
8. Hypothesis Testing
Eyes on the Prize
State of Practice, State of Mind
A Healthy Perspective on Fit Statistics
Types of Fit Statistics and "Golden Rules"
Model Chi-Square
Approximate Fit Indexes
Visual Summaries of Fit
Recommended Approach to Model Fit Evaluation
Detailed Example
Testing Hierarchical Models
Comparing Nonhierarchical Models
Power Analysis
Equivalent and Near-Equivalent Models
Summary
Recommended Readings
Exercises
9. Measurement Models and Confirmatory Factor Analysis
Naming and Reification Fallacies
Estimation of CFA Models
Detailed Example
Respecification of Measurement Models
Special Topics and Tests
TOPIC BOX 9.1. Reliability of Construct Measurement
Items as Indicators and Other Methods for Analyzing Items
Estimated Factor Scores
Equivalent CFA Models
Hierarchical CFA Models
Models for Multitrait–Multimethod Data
Measurement Invariance and Multiple-Sample CFA
Summary
Recommended Readings
Exercises
APPENDIX 9.A. Start Value Suggestions for Measurement Models
APPENDIX 9.B. Constraint Interaction in Measurement Models
10. Structural Regression Models
Analyzing SR Models
Estimation of SR Models
Detailed Example
Equivalent SR Models
Single Indicators in Partially Latent SR Models
Cause Indicators and Formative Measurement
TOPIC BOX 10.1. Partial Least Squares Path Modeling
Invariance Testing of SR Models
Reporting Results of SEM Analyses
Summary
Recommended Readings
Exercises
APPENDIX 10.A. Constraint Interaction in SR Models
III. Advanced Techniques, Avoiding Mistakes
11. Mean Structures and Latent Growth Models
Logic of Mean Structures
Identification of Mean Structures
Estimation of Mean Structures
Latent Growth Models
Structured Means in Measurement Models
MIMIC Models as an Alternative to Multiple-Sample Analysis
Summary
Recommended Readings
12. Interaction Effects and Multilevel SEM
Interaction Effects of Observed Variables
Interaction Effects in Path Models
Mediation and Moderation Together
Interactive Effects of Latent Variables
Estimation with the Kenny-Judd Method
Alternative Estimation Methods
Rationale of Multilevel Analysis
Basic Multilevel Techniques
Convergence of SEM and MLM
Multilevel SEM
Summary
Recommended Readings
13. How to Fool Yourself with SEM
Tripping at the Starting Line: Specification
Improper Care and Feeding: Data
Checking Critical Judgment at the Door: Analysis and Respecification
The Garden Path: Interpretation
Summary
Recommended Readings
*Suggested Answers to Exercises

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