Assessing statistical differences between parameters estimates in Partial Least Squares path modeling
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- Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whetherStructural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess differences between parameters that are estimated for different subpopulations, the study at hand introduces a technique that allows to also assess whether two parameter estimates that are derived from the same sample are statistically different. To illustrate this advancement to PLS-SEM, we particularly refer to a reduced version of the well-established technology acceptance model.…
Autor(en): | Macario Rodríguez-Entrena, Florian Schuberth, Carsten Gelhard |
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URN: | urn:nbn:de:bvb:20-opus-226403 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Wirtschaftswissenschaftliche Fakultät / Betriebswirtschaftliches Institut |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Quality & Quantity |
Erscheinungsjahr: | 2018 |
Band / Jahrgang: | 52 |
Heft / Ausgabe: | 1 |
Seitenangabe: | 57-69 |
Originalveröffentlichung / Quelle: | Qual Quant (2018) 52:57–69 |
DOI: | https://doi.org/10.1007/s11135-016-0400-8 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Freie Schlagwort(e): | Bootstrap; Confidence interval; Consistent partial least squares; Practitioner's guide; Statistical misconception; Testing parameter difference |
Datum der Freischaltung: | 07.02.2023 |
Lizenz (Deutsch): | ![]() |