Abstract
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 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.
Original language | English |
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Pages (from-to) | 57-69 |
Number of pages | 13 |
Journal | Quality & quantity |
Volume | 52 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2018 |
Keywords
- UT-Hybrid-D
- Testing parameter difference
- Bootstrap
- Confidence interval
- Practitioner’s guide
- Statistical misconception
- Consistent partial least squares