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

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This bestselling text provides a balance between the technical and practical aspects of structural equation modeling (SEM). Using clear and accessible language, Rex B. Kline covers core techniques, potential pitfalls, and applications across the behavioral and social sciences. Some more advanced topics are also covered, including estimation of interactive effects of latent variables and multilevel SEM.

The book contains black-and-white illustrations.

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Editorial Reviews

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.
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

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Product Details

  • ISBN-13: 9781606238769
  • 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
  • Sales rank: 531,740
  • Product dimensions: 6.90 (w) x 9.80 (h) x 0.80 (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

Part I Concepts and Tools

1 Introduction 3

The Book's Website 3

Pedagogical Approach 4

Getting Ready to Learn about SEM 5

Characteristics of SEM 7

Widespread Enthusiasm, but with a Cautionary Tale 13

Family History and a Reminder about Context 15

Extended Latent Variable Families 16

Plan of the Book 17

Summary 18

2 Fundamental Concepts 19

Multiple Regression 19

Partial Correlation and Part Correlation 28

Other Bivariate Correlations 31

Logistic Regression 32

Statistical Tests 33

Bootstrapping 42

Summary 43

Recommended Readings 44

Exercises 45

3 Data Preparation 46

Forms of Input Data 46

Positive Definiteness 49

Data Screening 51

Selecting Good Measures and Reporting about Them 68

Summary 72

Recommended Readings 72

Exercises 73

4 Computer Tools 75

Ease of Use, Not Suspension of Judgment 75

Human-Computer Interaction 77

Core SEM Programs and Book Website Resources 77

Other Computer Tools 86

Summary 87

Recommended Readings 87

Part II Core Techniques

5 Specification 91

Steps of SEM 91

Model Diagram Symbols 95

Specification Concepts 96

Path Analysis Models 103

CFA Models 112

Structural Regression Models 118

Exploratory SEM 121

Summary 121

Recommended Readings 122

Exercises 122

6 Identification 124

General Requirements 124

Unique Estimates 130

Rule for Recursive Structural Models 132

Rules for Standard CFA Models 137

Rules for Nonstandard CFA Models 138

Rules for SR Models 144

A Healthy Perspective on Identification 146

Empirical Underidentification 146

Managing Identification Problems 147

Summary 148

Recommended Readings 149

Exercises 149

Appendix 6.A. Evaluation of the Rank Condition 151

7 Estimation 154

Maximum Likelihood Estimation 154

Detailed Example 160

Brief Example with a Start Value Problem 172

Fitting Models to Correlation Matrices 175

Alternative Estimators 176

A Healthy Perspective on Estimation 182

Summary 182

Recommended Readings 183

Exercises 183

Appendix 7.A Start Value Suggestions for Structural Models 185

Appendix 7.B Effect Decomposition in Nonrecursive Models and the Equilibrium Assumption 186

Appendix 7.C Corrected Proportions of Explained Variance for Nonrecursive Models 187

8 Hypothesis Testing 189

Eyes on the Prize 189

State of Practice, State of Mind 190

A Healthy Perspective on Fit Statistics 191

Types of Fit Statistics and "Golden Rules" 193

Model Chi-Square 199

Approximate Fit Indexes 204

Visual Summaries of Fit 209

Recommended Approach to Model Fit Evaluation 209

Detailed Example 210

Testing Hierarchical Models 214

Comparing Nonhierarchical Models 219

Power Analysis 222

Equivalent and Near-Equivalent Models 225

Summary 228

Recommended Readings 228

Exercises 229

9 Measurement Models and Confirmatory Factor Analysis 230

Naming and Reification Fallacies 230

Estimation of CFA Models 231

Detailed Example 233

Respecification of Measurement Models 240

Special Topics and Tests 241

Items as Indicators and Other Methods for Analyzing Items 244

Estimated Factor Scores 245

Equivalent CFA Models 245

Hierarchical CFA Models 248

Models for Multitrait-Multimethod Data 250

Measurement Invariance and Multiple-Sample CFA 251

Summary 261

Recommended Readings 262

Exercises 262

Appendix 9.A Start Value Suggestions for Measurement Models 263

Appendix 9.B Constraint Interaction in Measurement Models 264

10 Structural Regression Models 265

Analyzing SR Models 265

Estimation of SR Models 269

Detailed Example 270

Equivalent SR Models 276

Single Indicators in Partially Latent SR Models 276

Cause Indicators and Formative Measurement 280

Invariance Testing of SR Models 288

Reporting Results of SEM Analyses 289

Summary 293

Recommended Readings 293

Exercises 294

Appendix 10.A Constraint Interaction in SR Models 295

Part III Advanced Techniques, Avoiding Mistakes

11 Mean Structures and Latent Growth Models 299

Logic of Mean Structures 299

Identification of Mean Structures 303

Estimation of Mean Structures 304

Latent Growth Models 304

Structured Means in Measurement Models 316

MIMIC Models as an Alternative to Multiple-Sample Analysis 322

Summary 325

Recommended Readings 326

12 Interaction Effects and Multilevel SEM 327

Interaction Effects of Observed Variables 327

Interaction Effects in Path Models 331

Mediation and Moderation Together 333

Interactive Effects of Latent Variables 336

Estimation with the Kenny-Judd Method 337

Alternative Estimation Methods 340

Rationale of Multilevel Analysis 343

Basic Multilevel Techniques 345

Convergence of SEM and MLM 348

Multilevel SEM 350

Summary 354

Recommended Readings 354

13 How to Fool Yourself with SEM 356

Tripping at the Starting Line: Specification 356

Improper Care and Feeding: Data 359

Checking Critical Judgment at the Door: Analysis and Respecification 361

The Garden Path: Interpretation 363

Summary 366

Recommended Readings 366

Suggested Answers to Exercises 367

References 387

Author Index 405

Subject Index 411

About the Author 427

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