Hair, Joseph F. <br/><br/>
Partial least squares structural equation modeling (PLS-SEM) using R: a workbook 

 - Switzerland  Springer  2021 
 - xiv, 197 p. 
<br/><br/> About this book Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method's flexibility in terms of data requirements and measurement specification.  This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software's SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the "how-tos" of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM. 
<br/><br/><label>ISBN: </label>9783030805180 
<br/><br/><label>Subjects--Topical Terms: </label><br/>R (Computer program language)<br/>Structural equation modeling<br/>Finance--Mathematical models<br/>Least squares
<br/><br/><label>Dewey Class. No.: </label>511.42  / HAI