Statements (49)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
statistical analysis
|
| gptkbp:advantage |
suitable for exploratory research
robust to multicollinearity |
| gptkbp:alsoKnownAs |
gptkb:Partial_Least_Squares_Path_Modeling
|
| gptkbp:contrastsWith |
covariance-based SEM
|
| gptkbp:developedBy |
gptkb:Herman_Wold
|
| gptkbp:estimatedCost |
R-squared values
effect sizes latent variable scores outer loadings outer weights path coefficients predictive relevance (Q-squared) |
| gptkbp:handles |
small sample sizes
formative and reflective measurement models non-normal data |
| https://www.w3.org/2000/01/rdf-schema#label |
PLS path modeling
|
| gptkbp:introducedIn |
1970s
|
| gptkbp:limitation |
less suitable for theory testing
no global goodness-of-fit index |
| gptkbp:output |
average variance extracted (AVE)
composite reliability discriminant validity indicator reliability latent variable correlations model fit indices path diagram statistical significance of paths |
| gptkbp:relatedTo |
gptkb:principal_component_analysis
statistical analysis path analysis covariance-based SEM |
| gptkbp:requires |
measurement model specification
structural model specification |
| gptkbp:software |
gptkb:ADANCO
gptkb:PLS-Graph gptkb:SmartPLS gptkb:WarpPLS R package plspm |
| gptkbp:usedFor |
analyzing complex relationships between observed and latent variables
|
| gptkbp:usedIn |
social sciences
marketing research management research information systems research structural equation modeling |
| gptkbp:uses |
bootstrapping for significance testing
resampling techniques |
| gptkbp:bfsParent |
gptkb:Partial_Least_Squares_(statistical_method)
|
| gptkbp:bfsLayer |
7
|