articleJournal of Statistical SoftwareJan 1, 2012DIAMOND OA

semPLS : Structural Equation Modeling Using Partial Least Squares

University of Wollongong

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.…

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615
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Topics & keywords

Keywords
  • Structural equation modeling
  • Partial least squares regression
  • Computer science
  • Residual
  • Covariance
  • Path (computing)
  • Sample (material)
  • Least-squares function approximation
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