A First Course in Structural Equation Modeling Review

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(More customer reviews)If you haven't been exposed to SEM , this book is right for you. Basic, straightforward, well planned and nonmathematical. However, this book cannot be the "only" book in your library if you are planning to go deep in SEM. This book is a good step for moving to intermediate or advanced levels.
The book is well desinged. It starts with fundamentals of SEM and EQS and LISREL programs. This book is NOT an EQS or LISREL reference, however, in each chapter, Raykov and Marcoulides cover an example showing the syntax and output of each program. The syntax and the output are deeply explained.
After introducing SEM and EQS and LISREL, the authors start to cover different approaches in SEM. Path analysis, Confirmatory Factor Analysis, Structural Regression Models and finally there is chapter about Latent Change Analysis.
In overall, the book is useful for only beginners as the authors' claim.

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This book is designed to introduce students to the basics of structural equation modeling through a conceptual, nonmathematical approach. The few mathematical formulas included are used in a conceptual or illustrative nature, rather than a computational one. The book features examples from LISREL and EQS. For that reason, the book can also be used as a beginning guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. Intended as an introduction for graduate students or researchers in psychology, education, business, and other applied social and health sciences. The only prerequisite is a basic statistics course.

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A First Course in Structural Equation Modeling Review

Average Reviews:

(More customer reviews)This book does a good job of explaining the basic concepts involved in SEM, path analysis, and CFA in easy to understand terms. Also, it lays out syntax and output for running popular SEM programs, such as LISREL, EQS, and Mplus. This book is perfect for the person who is trying to learn SEM on their own. I think it gives you enough to be able to know how to run a SEM, but it isn't enough to really make you a pro at it.

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In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one. Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner's guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software. Highlights of the second edition include:• review of latent change (growth) analysis models at an introductory level; •coverage of the popular Mplus program; •updated examples of LISREL and EQS; and •a CD that contains all of the text's LISREL, EQS, and Mplus examples.A First Course in Structural Equation Modeling is intended as an introductory book for students and researchers in psychology, education, business, medicine, and other applied social, behavioral, and health sciences with limited or no previous exposure to SEM. A prerequisite of basic statistics through regression analysis is recommended. The book frequently draws parallels between SEM and regression, making this prior knowledge helpful.

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Principles and Practice of Structural Equation Modeling Review

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(More customer reviews)Rex Kline easy writing style will take you through step-by-step in one of the most comprehesive yet accessible introductions to multivariate analysis and structural equation modeling. After outlining the building blocks of SEM (multiple regression, path analysis, and factor analysis), Kline gets the reader ready to tackle popular SEM software with examples for AMOS, LISREL and EQS. There is also a great chapter on what NOT to do with this often misused technique. For a preview, see Kline's article in the Journal of Clinical Psychology (1991), Latent variable path analysis: A beginner's tour guide. This book is an excellent read, and a must have for researchers and statisticians.

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Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in 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.

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