A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

Hair, Joe

ISBN 10: 1452217440 / ISBN 13: 9781452217444

Editore: SAGE Publications, Inc, 2013

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Titolo: A Primer on Partial Least Squares Structural...

Casa editrice: SAGE Publications, Inc

Data di pubblicazione: 2013

Legatura: Brossura

Condizione: Good

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Riassunto:

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), by Hair, Hult, Ringle, and Sarstedt, provides a concise yet very practical guide to understanding and using PLS structural equation modeling (PLS-SEM). PLS-SEM is evolving as a statistical modeling technique and its use has increased exponentially in recent years within a variety of disciplines, due to the recognition that PLS-SEM's distinctive methodological features make it a viable alternative to the more popular covariance-based SEM approach. This text—the only comprehensive book available to explain the fundamental aspects of the method—includes extensive examples on SmartPLS software, and is accompanied by multiple data sets that are available for download from the accompanying website (www.pls-sem.com).

Recensione:

The text is well written and relatively easy to understand. It provides abundant information without being overwhelming. It is very current. (Eleanor Witta 2012-11-21)

The author provided a great deal of practical advice on a variety of tangentially related topics that I think is great for students. (Richard S. Mohn 2012-11-21)

The book is of good quality as its content is easy-to-read, comprehensive, and up-to-date. Tourism researchers are highly recommended to read this book if they want to catch up with the latest trend of application of SEM techniques. (Lawrence Hoc Nang Fong and Rob Law European Journal of Tourism Management)

This book is a valuable reference to acquire basic grasps on PLS-SEM, especially for readers who do not have background in advanced statistics... The volume will undoubtedly become a basic reference for students, teachers, researchers, and practitioners interested in learning and teaching the fundamental concepts of PLS-SEM. (Adrian Leguina, University of Manchester)