Ordinal Consistent Partial Least Squares

Florian Schuberth, Gabriele Cantaluppi

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)

Abstract

In this chapter, we present a new variance-based estimator called ordinal
consistent partial least squares (OrdPLSc). It is a promising combination of consistent partial least squares (PLSc) and ordinal partial least squares (OrdPLS), respectively, which is capable to deal in structural equation models with common factors, composites, and ordinal categorical indicators. Besides providing the theoretical background of OrdPLSc, we present three approaches to obtain constructs scores from OrdPLS and OrdPLSc, which can be used, e.g., in importance-performance matrix analysis. Finally, we show its behavior on an empirical example and provide a practical guidance for the assessment of SEMs with ordinal categorical indicators in the context of OrdPLSc.
Original languageEnglish
Title of host publicationPartial Least Squares Path Modeling
Subtitle of host publicationBasic Concepts, Methodological Issues and Applications
EditorsHengky Latan, Richard Noonan
PublisherSpringer
Pages109-150
Number of pages42
ISBN (Electronic)978-3-319-64069-3
ISBN (Print)978-3-319-64068-6
DOIs
Publication statusPublished - 2017

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    Schuberth, F., & Cantaluppi, G. (2017). Ordinal Consistent Partial Least Squares. In H. Latan, & R. Noonan (Eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications (pp. 109-150). Springer. https://doi.org/10.1007/978-3-319-64069-3_6