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.
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 language | English |
|---|---|
| Title of host publication | Partial Least Squares Path Modeling |
| Subtitle of host publication | Basic Concepts, Methodological Issues and Applications |
| Editors | Hengky Latan, Richard Noonan |
| Publisher | Springer |
| Pages | 109-150 |
| Number of pages | 42 |
| ISBN (Electronic) | 978-3-319-64069-3 |
| ISBN (Print) | 978-3-319-64068-6 |
| DOIs | |
| Publication status | Published - 2017 |
Keywords
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