semPLS : Structural Equation Modeling Using Partial Least Squares
Indexed incrossrefdoaj
Abstract
Structural equation models (SEM) are very popular in many disciplines. The partial least squares (PLS) approach to SEM offers an alternative to covariance-based SEM, which is especially suited for situations when data is not normally distributed. PLS path modelling is referred to as soft-modeling-technique with minimum demands regarding mea- surement scales, sample sizes and residual distributions. The semPLS package provides the capability to estimate PLS path models within the R programming environment. Different setups for the estimation of factor scores can be used. Furthermore it contains modular methods for computation of bootstrap confidence intervals, model parameters and several quality indices.…
Citation impact
615
total citations
- FWCI
- 33.16
- Percentile
- 100%
- References
- 24
Citations per year
Authors
2Topics & keywords
Topics
Keywords
- Structural equation modeling
- Partial least squares regression
- Computer science
- Residual
- Covariance
- Path (computing)
- Sample (material)
- Least-squares function approximation
No related works found for this paper.