Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
A Workbook
| dc.contributor.author | Hair Jr., Joseph F. | |
| dc.contributor.author | Hult, G. Tomas M. | |
| dc.contributor.author | Ringle, Christian M. | |
| dc.contributor.author | Sarstedt, Marko | |
| dc.contributor.author | Danks, Nicholas P. | |
| dc.contributor.author | Ray, Soumya | |
| dc.date.accessioned | 2021-11-16T06:32:08Z | |
| dc.date.available | 2021-11-16T06:32:08Z | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-11-15T15:27:39Z | |
| dc.identifier | ONIX_20211115_9783030805197_9 | |
| dc.identifier | https://library.oapen.org/handle/20.500.12657/51463 | |
| dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/72839 | |
| dc.description.abstract | 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. | |
| dc.language | English | |
| dc.relation.ispartofseries | Classroom Companion: Business | |
| dc.rights | open access | |
| dc.subject.other | Open Access | |
| dc.subject.other | PLS-SEM) Using R | |
| dc.subject.other | Workbook | |
| dc.subject.other | Partial Least Squares Structural Equation Modeling | |
| dc.subject.other | R Software Environment | |
| dc.subject.other | thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJS Sales and marketing | |
| dc.subject.other | thema EDItEUR::U Computing and Information Technology::UF Business applications::UFM Mathematical and statistical software | |
| dc.subject.other | thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCH Econometrics and economic statistics | |
| dc.title | Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R | |
| dc.title.alternative | A Workbook | |
| dc.type | book | |
| oapen.identifier.doi | 10.1007/978-3-030-80519-7 | |
| oapen.relation.isPublishedBy | 9fa3421d-f917-4153-b9ab-fc337c396b5a | |
| oapen.relation.isFundedBy | Otto von Guericke University Magdeburg | |
| oapen.relation.isFundedBy | 0ba1b5cf-bbfb-48f0-8246-0acef2894f7e | |
| oapen.relation.isbn | 9783030805197 | |
| oapen.imprint | Springer International Publishing | |
| oapen.pages | 197 | |
| oapen.grant.number | [grantnumber unknown] | |
| dc.relationisFundedBy | 0ba1b5cf-bbfb-48f0-8246-0acef2894f7e |
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