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An Introduction to Structural Equation Modeling (SEM) and the Partial Least Squares (PLS) Methodology

An Introduction to Structural Equation Modeling (SEM) and the Partial Least Squares (PLS) Methodology
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Author(s): Nicholas J. Ashill (American University of Sharjah, United Arab Emirates)
Copyright: 2011
Pages: 20
Source title: Student Satisfaction and Learning Outcomes in E-Learning: An Introduction to Empirical Research
Source Author(s)/Editor(s): Sean B. Eom (Southeast Missouri State University, USA) and J. B. Arbaugh (University of Wisconsin Oshkosh, USA)
DOI: 10.4018/978-1-60960-615-2.ch006

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Abstract

Over the past 15 years, the use of Partial Least Squares (PLS) in academic research has enjoyed increasing popularity in many social sciences including Information Systems, marketing, and organizational behavior. PLS can be considered an alternative to covariance-based SEM and has greater flexibility in handling various modeling problems in situations where it is difficult to meet the hard assumptions of more traditional multivariate statistics. This chapter focuses on PLS for beginners. Several topics are covered and include foundational concepts in SEM, the statistical assumptions of PLS, a LISREL-PLS comparison and reflective and formative measurement.

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