Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods

By Edward E. Rigdon. 2012

868 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Food Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/68dac040f297d778bdf35279e93c369d338112b5

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In Analytical Chemistry

In Food Science

In Statistics and Probability

Citations in the corpus

A review of the methodological misconceptions and guidelines related to the application of structural equation modeling: A Malaysian scenario (2017, methodology): “Specifically, when the primary focus of the research is to predict and explain the key target constructs and/or identify the key driver constructs (Hair et al., 2017b; Rigdon, 2012).”
Confirmatory composite analysis using partial least squares: setting the record straight (2020, methodology): “Against the recent history of PLS-SEM, and especially since Rigdon (2012), it is suggested that in PLS-SEM reflective and formative measurement refer to a model 1 3 where the emergent variable is built by correlation weights (Mode A) and regression weights (Mode B), respectively.”
On the adoption of partial least squares in psychological research: Caveat emptor (2015, background): “As Rigdon (2012) aptly notes, the parallels drawn in the PLS literature between Mode A and reflective measurement “may be described as an article of faith among regular PLS path modeling users and among those who write about the method” (p. 344).”
How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research (2020, methodology): “(composites) as proxies for the theoretical concepts ([31] [32],).”
Promoting innovative experiential learning practices to improve academic performance: Empirical evidence from a Spanish Business School (2019, background): “Both theoretical contributions (Henseler et al., 2014; Rigdon, 2012) and empirical simulation studies (Becker, Rai, & Rigdon, 2013; Sarstedt, Hair, Ringle, Thiele, & Gudergan, 2016) endorse the usage of PLS for composite models.”
PLS' Janus Face – Response to Professor Rigdon's ‘Rethinking Partial Least Squares Modeling: In Praise of Simple Methods’ (2014, background): “It was observed in the fifties that systems like (22, 23) could be rewritten as:”