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Structural Equation Modeling with EQS and EQS/WINDOWS: Basic Concepts, Applications, and Programming (Hardback)
  • Structural Equation Modeling with EQS and EQS/WINDOWS: Basic Concepts, Applications, and Programming (Hardback)
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Structural Equation Modeling with EQS and EQS/WINDOWS: Basic Concepts, Applications, and Programming (Hardback)

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£102.00
Hardback 304 Pages / Published: 19/04/1994
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Designed to help beginners estimate and test structural equation modelling (SEM) using the EQS approach, this book demonstrates a variety of SEM/EQS applications that include both partial factor analytic and full latent variable models. Beginning with an overview of the basic concepts of SEM and the EQS program, the author works through applications starting with a single sample approach through to more advanced applications, such as a multi-sample approach. The book concludes with a section on using EQS for modelling with Windows.

Publisher: SAGE Publications Inc
ISBN: 9780803950917
Number of pages: 304
Weight: 658 g
Dimensions: 228 x 152 x 25 mm


MEDIA REVIEWS

"Byrne's book is a delightfully written, systematic approach to the practical use of structural equation modeling in research. It begins with first principles and advances systematically through intermediate and advanced topics, introducing at each step the theory that is relevant as well as the practical models needed to implement these ideas on real models used in actual research contexts. The reader can then easily modify the examples for their own research since the types of models discussed will be relevant in many research contexts. The book is also timely, being the first text to show how statistics generally, and modeling in particular, can be fun in the Windows environment."

-- Peter M. Bentler

". . . . Newcomers to SEM who want to use EQS or EQS/Windows would benefit greatly from this book, either for self-teaching or as a supplemental guide in a course. . . . Byrne intends her books `to provide a practical guide to SEM using the EQS approach.' She succeeds admirably."

-- George R. Franke * Journal of Marketing Research *

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