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A Beginner's Guide to Partial Least Squares Analysis

Haenlein, Michael, Kaplan, Andreas M.·2004·Understanding Statistics
DOI 10.1207/s15328031us0304_4
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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.

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Metadata

Authors
Haenlein, M., & Kaplan, A. M.
Venue
Understanding Statistics
Publisher
Informa UK Limited
Published
2004-11
Volume
3
Issue
4
Pages
283-297
ISSN
  • 1532-8031 (ISSN-L)
  • 1534-844X
DOI
10.1207/s15328031us0304_4
OpenAlex
W2017806383
Cited by
1,694
References
5
FWCI
12.05
Type
journal article
Language
en
Open access
closed

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Haenlein, M., & Kaplan, A. M. (2004). A Beginner's Guide to Partial Least Squares Analysis. Understanding Statistics. https://doi.org/10.1207/s15328031us0304_4

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