Joseph F. Hair Jr.,G. Tomas M. Hult,Christian M. Ringle,Marko Sarstedt,Nicholas P. Danks,Soumya Ray
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
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Excellent- More about Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
PLS-SEM is a popular method for analyzing complex inter-relationships between observed and latent variables, offering advantages such as estimating complex models and flexibility in data requirements and measurement specification. This practical 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. Each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study, with simple instructions to obtain solutions and document results.
Format: Hardback
Length: 197 pages
Publication date: 04 November 2021
Publisher: Springer Nature Switzerland AG
The analysis of complex interrelationships between observed and latent variables has become a prevalent approach in the field of research, and Partial Least Squares Structural Equation Modeling (PLS-SEM) has emerged as a widely adopted methodology. PLS-SEM offers numerous advantages, including the ability to estimate intricate models and its flexibility in accommodating diverse data requirements and measurement specifications. To assist researchers in effectively utilizing PLS-SEM, this practical open-access guide offers a comprehensive step-by-step treatment of the key considerations involved in analyzing PLS path models using the R software environment, a free and widely accessible statistical computing platform that operates on various computer platforms, including Windows, macOS, and UNIX.
Adopting the SEMinR package within the R software, this guide presents a user-friendly syntax for creating and estimating structural equation models. Each chapter provides a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Clear and concise instructions are provided to guide readers through the process of using SEMinR to obtain solutions and document their findings. Additionally, throughout the guide, practical rules of thumb are offered to provide guidance on best practices in applying and interpreting PLS-SEM.
By leveraging the power of PLS-SEM and the accessibility of R, researchers can gain a deeper understanding of the complex relationships between observed and latent variables, leading to more informed research conclusions and practical applications.
Weight: 462g
Dimension: 160 x 242 x 20 (mm)
ISBN-13: 9783030805180
Edition number: 1st ed. 2021
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