A primer on partial least squares structural equations modeling (PLS-SEM) / Joseph F. Hair, Jr., G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt.

Includes bibliographical references (page 282-289) and indexes.

Structural Equation Modeling -- Specifying the Path Model and Collecting Data -- Path Model Estimation -- Assessing PLS-SEM Results Part I: Evaluation of Reflective Measurement Models -- Assessing PLS-SEM Results Part II: Evaluation of the Formative Measurement Models -- Assessing PLS-SEM Results Part III: Evaluation of the Structural Model -- Advanced Topics in PLS Path Modeling -- Modeling Heterogeneous Data.

'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 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).'--Publisher's website.