000			01897nam a22002537a 4500
999			_c2786 _d2786
005			20220813112343.0
008			220718b ||||| |||| 00| 0 eng d
020			_a9783030805180
082			_a511.42 _bHAI
100			_aHair, Joseph F. _9876
245			_aPartial least squares structural equation modeling (PLS-SEM) using R: a workbook
260			_bSpringer _aSwitzerland _c2021
300			_axiv, 197 p.
365			_aEURO _b49.99
520			_aAbout 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.
650			_aR (Computer program language) _91512
650			_aStructural equation modeling _98383
650			_aFinance--Mathematical models _9180
650			_aLeast squares _94223
700			_aHult, G. Tomas M. _94224
700			_aRingle, Christian M. _94225
700			_aMarko Sarstedt _97722
942			_2ddc _cBK