A Beginner's Guide to Partial Least Squares Analysis

TLDR: Partial least squares (PLS) analysis as mentioned in this paper is a generalization of covariance-based structural equation modeling (SEM), which is particularly suited for situations in which constructs are measured by a very large number of indicators and where maximum likelihood covariancebased SEM tools reach their limit.

Abstract: Since the introduction of covariance-based structural equation modeling (SEM) by Joreskog in 1973, this technique has been received with considerable interest among empirical researchers However, the predominance of LISREL, certainly the most well-known tool to perform this kind of analysis, has led to the fact that not all researchers are aware of alternative techniques for SEM, such as partial least squares (PLS) analysis Therefore, the objective of this article is to provide an easily comprehensible introduction to this technique, which is particularly suited to situations in which constructs are measured by a very large number of indicators and where maximum likelihood covariance-based SEM tools reach their limit Because this article is intended as a general introduction, it avoids mathematical details as far as possible and instead focuses on a presentation of PLS, which can be understood without an in-depth knowledge of SEM