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Partial least squares structural equation modeling (PLS-SEM) using R : a workbook /
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...
|a Partial least squares structural equation modeling (PLS-SEM) using R :
|b a workbook /
|c Joseph Hair Jr...[et al].
|h [recurso electrónico - acceso abierto]
260
|a Cham :
|b Springer,
|c 2021
300
|a 1 recurso en línea (208 p.) :
|b texto/pdf 12.14Mb
490
0
|a Classroom Companion: Business
520
3
|a 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
4
|9 81
|a ESTIMACION POR MINIMOS CUADRADOS
650
4
|9 138
|a ANALISIS ESTADISTICO
650
4
|9 18914
|a MODELIZACION DE ECUACIONES ESTRUCTURALES
