Principles and Practice of Structural Equation Modeling

Methodology in the Social Sciences

by Rex B. Kline

Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by exercises with answers, rules to remember, and topic boxes. The companion website supplies data, syntax, and output for the book's examples--now including files for Amos, EQS, LISREL, Mplus, Stata, and R (lavaan). New to This Edition *Extensively revised to cover important new topics: Pearl's graphing theory and the SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. *Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping. *Expanded coverage of psychometrics. *Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan). *Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models. Pedagogical Features *Exercises with answers, plus end-of-chapter annotated lists of further reading. *Real examples of troublesome data, demonstrating how to handle typical problems in analyses. *Topic boxes on specialized issues, such as causes of nonpositive definite correlations. *Boxed rules to remember. *Website promoting a learn-by-doing approach, including syntax and data files for six widely used SEM computer tools.

Genres: Nonfiction, Textbooks, Research Methods, Psychology, Reference, Research, Logic

534 pages, Kindle Edition

First published May 27, 1998

Reviews

[Terran M · Rating 5 out of 5]

This is the correct first book to read on causal inference. It covers structural equation modeling (SEM), confirmatory factor analysis (CFA), and Pearl's structured causal modeling (SCM). Adequate preparation for understanding this book would be a basic treatment of multivariate regression, such as Gelman and Hill. Introduction to Statistical Learning would also be sufficient. If you want to really understand confirmatory factor analysis, you should probably already know something about factor analysis as well; I liked Gorsuch.

Although this book claims to cover various software packages, the treatment is cursory and the code examples (online) are mostly uncommented; don't expect to really learn how to use the software from this book. Read this book for the principles and then also read the software manual for whatever tool you're going to use.

Ironically, this book, whose title claims to be about SEM only, actually covers most of modern causal inference, whereas Pearl's book, with the grand title "Causality", covers only his own narrow work. This is definitely the one you want.

[Fahed Al Kerdi · Rating 5 out of 5]

Great book to cite some information about the validity and the reliability of the research instrument.

[Sam · Rating 4 out of 5]

Excellent SEM book for students/academics. Provides detailed explanations of the consensus (and controversy) of state of the art structural equation modeling techniques. Kline's book uses plain language to communicate complex issues in applying SEM to research questions. Very helpful in answering reviewers/referees questions in the publication process. Minus 1 star for lack of MPLUS syntax addressing model comparisons.

[Jared · Rating 5 out of 5]

Yeah that's right.
I'm actually really excited to re-read this book. This guy is a great writer when it comes to this stuff. I think this is a wonderfully powerful tool for gaining insight into how the world works.
This is where stats is going. If you're getting a degree in this stuff, read this.

[Erin · Rating 4 out of 5]

Fantastix explanation of theory, assumptions, and technique.

[Robyn · Rating 5 out of 5]

Very clear and easy to follow. A great textbook for introductory SEM coursework.

[Desiree Leboeuf-davis · Rating 5 out of 5]

Very informative and understandable for non-mathematician folks.