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Purpose – The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons...
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An Introduction to Structural Equation Modeling -- Introduction to R and RStudio -- Introduction to SEMinR -- Evaluation of Reflective Measurement Models -- Evaluation of Formative Measurement Models -- Evaluation of the Structural Model -- Mediation Analysis -- Moderation Analysis.
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Structural equation modeling (SEM) is a statistical analytic framework that allows researchers to specify and test models with observed and latent (or unobservable) variables and their generally linear relationships. In the past decades, SEM has become a standard statistical analysis technique...
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Applications of the partial least squares (PLS) path modeling approach — which have gained increasing dissemination in business research — usually build on the assumption that the data stem from a single population. However, in empirical applications, this assumption of homogeneity is...
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"Advanced Issues in Partial Least Squares Structural Equation Modeling provides a practical and applied description of advanced issues in PLS-SEM relevant for students, professors and applied researchers. The book combines simple explanations of complex statistical concepts with examples and...
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Purpose: Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This...
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With the increasing prominence of partial least squares structural equation modeling (PLS-SEM) in business research, the use of latent class analyses for identifying and treating unobserved heterogeneity has also gained momentum. Researchers have introduced various latent class approaches in a...
Persistent link: https://www.econbiz.de/10013313426