, Volume 46, Issue 2, pp 139–142 | Cite as

Relationships between redundancy analysis, canonical correlation, and multivariate regression

  • Keith E. Muller


This paper attempts to clarify the nature of redundancy analysis and its relationships to canonical correlation and multivariate multiple linear regression. Stewart and Love introduced redundancy analysis to provide non-symmetric measures of the dependence of one set of variables on the other, as channeled through the canonical variates. Van den Wollenberg derived sets of variates which directly maximize the between set redundancy. Multivariate multiple linear regression on component scores (such as principal components) is considered. The problem is extended to include an orthogonal rotation of the components. The solution is shown to be identical to van den Wollenberg's maximum redundancy solution.


Linear Regression Public Policy Multiple Linear Regression Statistical Theory Multivariate Regression 
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Copyright information

© The Psychometric Society 1981

Authors and Affiliations

  • Keith E. Muller
    • 1
  1. 1.Department of BiostatisticsUniversity of North CarolinaChapel Hill

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