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A comparison of two PLS ‐based approaches to structural equation modeling
Author(s) -
Romano Rosaria,
Tomic Oliver,
Liland Kristian H.,
Smilde Age,
Næs Tormod
Publication year - 2019
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.3105
Subject(s) - structural equation modeling , path analysis (statistics) , computer science , path (computing) , representation (politics) , partial least squares regression , path coefficient , data mining , mathematics , machine learning , politics , political science , law , programming language
This paper presents a new approach to path modeling named SO‐PLS path modeling (SO‐PLS‐PM) and compares it with the more well‐known PLS path modeling (PLS‐PM). The new method is flexible and graphically oriented and allows for handling multidimensional blocks and diagnosing missing paths. In order to allow for a thorough comparison between the two methods, new definitions of total, direct, and indirect effects in terms of explained variances are proposed, along with new methods for graphical representation. The two PLS methods are tested on two well‐known data sets in the PLS‐PM literature from customer satisfaction analysis and descriptive sensory analysis. The findings from the empirical applications serve as a basis for recommendations and guidelines regarding the use of the SO‐PLS‐PM versus PLS‐PM.