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Structural Equation Modelling with Partial Least Squares Using Stata and R (Paperback)
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Structural Equation Modelling with Partial Least Squares Using Stata and R (Paperback)
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Partial least squares structural equation modelling (PLS-SEM) is
becoming a popular statistical framework in many fields and
disciplines of the social sciences. The main reason for this
popularity is that PLS-SEM can be used to estimate models including
latent variables, observed variables, or a combination of these.
The popularity of PLS-SEM is predicted to increase even more as a
result of the development of new and more robust estimation
approaches, such as consistent PLS-SEM. The traditional and modern
estimation methods for PLS-SEM are now readily facilitated by both
open-source and commercial software packages. This book presents
PLS-SEM as a useful practical statistical toolbox that can be used
for estimating many different types of research models. In so
doing, the authors provide the necessary technical prerequisites
and theoretical treatment of various aspects of PLS-SEM prior to
practical applications. What makes the book unique is the fact that
it thoroughly explains and extensively uses comprehensive Stata
(plssem) and R (cSEM and plspm) packages for carrying out PLS-SEM
analysis. The book aims to help the reader understand the mechanics
behind PLS-SEM as well as performing it for publication purposes.
Features: Intuitive and technical explanations of PLS-SEM methods
Complete explanations of Stata and R packages Lots of example
applications of the methodology Detailed interpretation of software
output Reporting of a PLS-SEM study Github repository for
supplementary book material The book is primarily aimed at
researchers and graduate students from statistics, social science,
psychology, and other disciplines. Technical details have been
moved from the main body of the text into appendices, but it would
be useful if the reader has a solid background in linear regression
analysis.
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