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Composite-Based Structural Equation Modeling : Analyzing Latent and Emergent Variables - Joerg Henseler
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Composite-Based Structural Equation Modeling

Analyzing Latent and Emergent Variables

By: Joerg Henseler

Hardcover | 1 April 2021

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This book presents powerful tools for integrating interrelated composites--such as capabilities, policies, treatments, indices, and systems--into structural equation modeling (SEM). Joerg Henseler introduces the types of research questions that can be addressed with composite-based SEM and explores the differences between composite- and factor-based SEM, variance- and covariance-based SEM, and emergent and latent variables. Using rich illustrations and walked-through data sets, the book covers how to specify, identify, estimate, and assess composite models using partial least squares path modeling, maximum likelihood, and other estimators, as well as how to interpret findings and report the results. Advanced topics include confirmatory composite analysis, mediation analysis, second-order constructs, interaction effects, and importance-performance analysis. Most chapters conclude with software tutorials for ADANCO and the R package cSEM. The companion website includes data files and syntax for the book's examples, along with presentation slides.

Industry Reviews

"This book offers a novel perspective on SEM in which constructs are viewed as composites rather than factors. Explaining the principles and rationales of composite-based SEM, the book provides examples and tutorials using the software ADANCO and the R package cSEM. It will make a great supplementary text for graduate-level courses on SEM, latent variable modeling, and multivariate analysis. It is written in such a way that both beginning doctoral students and experienced researchers can learn a lot from it. Students will get a fresh view of SEM and learn the SEM fundamentals; experienced researchers can use this book as an opportunity to elevate the discussion about SEM."--Ge Jiang, PhD, Department of Educational Psychology, University of Illinois at Urbana-Champaign

"Henseler gives an excellent introduction to composite-based SEM, the third member of the SEM family that also includes covariance-based SEM, widely known among researchers in psychology and related fields, and Judea Pearl's structural causal model, familiar to researchers in epidemiology and medicine. Methods in composite-based SEM offer researchers additional options for modeling, estimating, and testing hypotheses about latent variables, including emergent variables, or proxies for hypothetical constructs analyzed as linear combinations of observed variables. With clear descriptions, numerous examples, and coverage of advanced topics such as moderation, mediation, and importance-performance analysis, Henseler's book is a great starting point for both students and established researchers seeking to expand their modeling repertoires."--Rex B. Kline, PhD, Department of Psychology, Concordia University, Canada

"This extraordinary work on SEM to estimate composite models provides up-to-date explanations illustrated with a range of good examples. The book is 'ambidextrous' in the way it is both student-friendly and rigorous. It will surely make an impact on the SEM community. I plan to use this text in my master's- and doctoral-level SEM courses, as well as in my consulting activities with companies."--Jose Benitez, PhD, Rennes School of Business, France; and School of Business and Economics, University of Granada, Spain-

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