sempls: structural equation modeling using partial least squares

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ID: 154427
2012
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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. Various plot functions help to evaluate the model. The well known mobile phone dataset from marketing research is used to demonstrate the features of the package.
Reference Key
monecke2012journalsempls: Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Armin Monecke;Friedrich Leish
Journal open geospatial data, software and standards
Year 2012
DOI
DOI not found
URL
http://www.jstatsoft.org/v48/i03/paper
Keywords
partial least squares structural equation model

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