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

Fingerprint

scanning electron microscopy
matrix
indicator
analysis

Cite this

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
Schuberth, Florian ; Cantaluppi, Gabriele. / Ordinal Consistent Partial Least Squares. Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. editor / Hengky Latan ; Richard Noonan. Springer, 2017. pp. 109-150
@inbook{93f24afaee884c78b90dccab25579447,
title = "Ordinal Consistent Partial Least Squares",
abstract = "In this chapter, we present a new variance-based estimator called ordinalconsistent 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.",
author = "Florian Schuberth and Gabriele Cantaluppi",
year = "2017",
doi = "10.1007/978-3-319-64069-3_6",
language = "English",
isbn = "978-3-319-64068-6",
pages = "109--150",
editor = "Hengky Latan and Richard Noonan",
booktitle = "Partial Least Squares Path Modeling",
publisher = "Springer",

}

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. Springer, pp. 109-150. https://doi.org/10.1007/978-3-319-64069-3_6

Ordinal Consistent Partial Least Squares. / Schuberth, Florian ; Cantaluppi, Gabriele.

Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. ed. / Hengky Latan; Richard Noonan. Springer, 2017. p. 109-150.

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

TY - CHAP

T1 - Ordinal Consistent Partial Least Squares

AU - Schuberth, Florian

AU - Cantaluppi, Gabriele

PY - 2017

Y1 - 2017

N2 - In this chapter, we present a new variance-based estimator called ordinalconsistent 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.

AB - In this chapter, we present a new variance-based estimator called ordinalconsistent 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.

U2 - 10.1007/978-3-319-64069-3_6

DO - 10.1007/978-3-319-64069-3_6

M3 - Chapter

SN - 978-3-319-64068-6

SP - 109

EP - 150

BT - Partial Least Squares Path Modeling

A2 - Latan, Hengky

A2 - Noonan, Richard

PB - Springer

ER -

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