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A Beginner's Guide to Structural Equation Modeling: Third Edition [Kindle Edition]

Randall E. Schumacker , Richard G. Lomax
4.6 out of 5 stars  See all reviews (5 customer reviews)

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Book Description

This best-seller introduces readers to structural equation modeling (SEM) so they can conduct their own analysis and critique related research. Noted for its accessible, applied approach, chapters cover basic concepts and practices and computer input/output from the free student version of Lisrel 8.8 in the examples. Each chapter features an outline, key concepts, a summary, numerous examples from a variety of disciplines, tables, and figures, including path diagrams, to assist with conceptual understanding.

The book first reviews the basics of SEM, data entry/editing, and correlation. Next the authors highlight the basic steps of SEM: model specification, identification, estimation, testing, and modification, followed by issues related to model fit and power and sample size. Chapters 6 through 10 follow the steps of modeling using regression, path, confirmatory factor, and structural equation models. Next readers find a chapter on reporting SEM research including a checklist to guide decision-making, followed by one on model validation. Chapters 13 through 16 provide examples of various SEM model applications. The book concludes with the matrix approach to SEM using examples from previous chapters.

Highlights of the new edition include:

  • A website with raw data sets for the book's examples and exercises so they can be used with any SEM program, all of the book's exercises, hotlinks to related websites, and answers to all of the exercises for Instructor’s only

  • New troubleshooting tips on how to address the most frequently encountered problems

  • Examples now reference the free student version of Lisrel 8.8

  • Expanded coverage of advanced models with more on multiple-group, multi-level, & mixture modeling (Chs. 13 & 15), second-order and dynamic factor models (Ch. 14), and Monte Carlo methods (Ch. 16)

  • Increased coverage of sample size and power (Ch. 5) and reporting research (Ch. 11)

  • New journal article references help readers better understand published research (Chs. 13 – 17) and 25 % new exercises with answers to half in the book for student review.

Designed for introductory graduate level courses in structural equation modeling or factor analysis taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. An understanding of correlation is assumed. To access the website visit the book page or the Textbook Resource page at for more details.

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"From the first edition this book has been the leading book on this topic, providing an authoritative and systematic treatment of SEM for both researchers and practitioners. [It is] well organised and clearly written [and] can be recommended as a textbook to teach a full course in SEM. [A] good mixture of theory and practical applications ... graduate and research students will definitely enjoy reading this book [and] practitioners may find the book useful. I would also recommend it for library purchase." - Kuldeep Kumar, Bond University, Gold Coast, in the Journal of the Royal Statistical Society

"The authors’ considerable experience as modelers and teachers really shines throughout this edition, as reflected in the accessibility and coverage of the writing, the extensive practical software examples, and the useful troubleshooting and reporting tips." - Gregory R. Hancock, University of Maryland, USA

"The authors guide us through SEM basics to more advanced techniques in an easily comprehensible style. As such, it is a great resource for both novice and veteran users of SEM." - Maria Regina Reyes, Yale University, USA

"Their step-by-step approach … makes the "how-to" extremely clear… The reader comes away not only knowing the logistics of how to run the models but also the conceptual of when to run them and how to interpret the findings. Their coverage of assumptions, data cleaning and screening, and common SEM errors is extremely refreshing for those who work with real, messy data. This is a much anticipated edition to the already classical text." - Debbie Hahs-Vaughn, University of Central Florida, USA

"There are a number of features that set this book apart ... it covers a variety of applications ... from simple regression models to highly complex analyses. ...[and] it takes a non-mathematical approach which makes [it] less intimidating.... students have found it to be quite readable and friendly ... I have continued to use it because it is the most comprehensive and helpful to students." - Philip Smith, Dept. of Ed Leadership, Counseling, & Special Education, Augusta State University, USA

About the Author

Randall E. Schumacker is Professor of Educational Research at The University of Alabama where he teaches courses in structural equation modeling. He received his Ph.D. in Educational Psychology from Southern Illinois University. A Past-President of the Southwest Educational Research Association and Emeritus Editor of Structural Equation Modeling, Dr. Schumacker has also served on the editorial boards of numerous journals. His research interests include modeling interaction in SEM, robust statistics, measurement model issues related to estimation, and reliability.

Richard G. Lomax is a Professor in the School of Educational Policy and Leadership at The Ohio State University where he teaches courses in structural equation modeling. He received his Ph.D. in Educational Research Methodology from the University of Pittsburgh. He has served on the editorial boards of numerous journals. His research focuses on models of literacy acquisition, multivariate statistics, and assessment.

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Customer Reviews

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4.6 out of 5 stars
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Most Helpful Customer Reviews
11 of 13 people found the following review helpful
By A Customer
With Structural Equation Modeling (SEM) becoming an important statistical tool, this book serves as an excellant guide to the topic. It covers the rudimentary topics that are important in SEM (e.g., sample size, interpretation of goodness of fit indices) as well as a short chapter on some advanced topics (e.g., Bootstrap methods, interactions). Lots of examples included at the end of each chapter as well as one chapter devoted to complete examples (i.e., from formulating models, command lines for the computer package and interpretation of outputs)! Though the many examples stated in the book involve using EQS5 and LISREL8 computer packages, even if the reader does not have these programs, the book is still very useful. If you ever wanted to ask what this or that mean in a SEM analysis that you are doing or have read - this book most probably has the answers! Personally, I have found this to be a helpful introduction to SEM without too much distracting mathematical details. My advice - GET IT!
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1 of 1 people found the following review helpful
5.0 out of 5 stars Just useful 10 Mar. 2013
If you are an intermediate statistician (i.e. you are well grounded in regression in all its forms and aspects) then this will help you on the journey to being advanced. SEQ is difficult but incredibly powerful and use hIt takes you through the process one step at a time and briefly reviews some of the background you need. But don't expect to get enough background just from the book.
I think it is now out of print - I got my copy second hand. But an update and re-release would be a good idea.
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4.0 out of 5 stars Structure from the Start 11 Dec. 2013
By John M. Ford TOP 500 REVIEWER
Randall Schumacker and Richard Lomax's book introduces structural equation modeling (SEM) to researchers with some previous background in applied statistics. It begins with the basics of correlation and then outlines the logic of multiple regression, path analysis, and factor analysis. It presents SEM as a combination of these three analytical techniques. The final chapters discuss more complex SEM procedures. There are also useful discussions of how to report SEM studies and check the validity of SEM results.

The SEM model development process of data preparation, specification, identification, estimation, testing, and modification is used to structure discussion across chapters. This organization works well and makes the book useful as a reference as well as a text. Most chapters contain example analyses which are explained in detail. There are also end-of-chapter exercises with answers to odd-numbered problems in an appendix.

A key strength is the book's integration with the LISREL 8.80 Student software, which is available for free download from the web. Early chapters explain the basics of LISREL and how to import data. Subsequent chapters use LISREL code and output in examples and exercises. This kind of hands-on work is essential to learning SEM.

I recommend the book as a text or for independent study for those learning about SEM for the first time.
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1 of 2 people found the following review helpful
4.0 out of 5 stars good depth of content 4 Jun. 2013
Format:Paperback|Verified Purchase
content i would rate 4/5.

not for dummies though.

not many books do a good SEM book for people/students just wanting to complete a dissertation.
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5.0 out of 5 stars Five Stars 31 Jan. 2015
By Yizhong
Format:Paperback|Verified Purchase
Useful for my PhD Study
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