PLS' Janus Face – Response to Professor Rigdon's ‘Rethinking Partial Least Squares Modeling: In Praise of Simple Methods’

By Theo K. Dijkstra. 2014

127 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/6ad7bc089dc668999ce9c2eb8fd474a3d6e6a62c

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Citations in the corpus

An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research (2017, methodology): “Alternatively, researchers may use consistent PLS (Dijkstra, 2014; Dijkstra and Henseler, 2015b), which “corrects” PLS-SEM-based parameter estimates, Electronic copy available at: https://ssrn.com/abstract=3128204 Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M., & Ryu, K. (2018).”
A new criterion for assessing discriminant validity in variance-based structural equation modeling (2015, unknown): “Figure 7 shows the reduced ACSI model and the PLS results.”
On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations (2017, background): “And Herman Wold, Jöreskog’s “Doktorvater”, the originator of PLS-SEM (Wold, 1966, 1974), in turn, was inspired to find least squares approaches for doing the same thing (Dijkstra, 2014), in a technology environment where computing time was in short supply.”
ESTIMATING MODERATING EFFECTS IN PLS-SEM AND PLSc-SEM: INTERACTION TERM GENERATION*DATA TREATMENT (2018, methodology): “These results support PLSc-SEM’s adequacy to estimate models using common factor model data (Dijkstra & Henseler, 2015a, 2015b; Sarstedt et al., 2016) and is consistent with the results by Dijkstra and Schermelleh-Engel (2014). The standard PLS-SEM algorithm, however, underestimates all structural m”
Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods (2017, background): “2 Our comparison does not consider consistent PLS (PLSc; Dijkstra 2014; Dijkstra and Henseler 2015) that corrects the PLS estimates for attenuation to mimic common factor models.”
Partial least squares path modeling: Time for some serious second thoughts (2016, methodology): “However, as originally presented by Herman Wold, PLS was not intended to impose constraints on the data, making the technique incompatible with the idea of model testing (Dijkstra, 2014; see R€onkk€o et al., 2015).”
PLS-SEM: Looking Back and Moving Forward (2014, methodology): “Even critiques of PLS-SEM (e.g., McIntosh et al., 2014) call the consistent PLS algorithms such as the PLSe2 (Bentler et al., 2014) and PLSc (Dijkstra, 2014) “impressive”.”