Commonality Analysis: Partitioning Variance for Multivariate Prediction

Commonality analysis partitions the proportion of explained variance in the dependent variable or variables that is accounted for by the independent variables. Both variances unique to independent variables and variances common to sets of independent variables are obtained. An algorithm is described...

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Bibliographic Details
Published in:Educational and psychological measurement 1980-10, Vol.40 (3), p.739-743
Main Author: Jernstedt, G. Christian
Format: Article
Language:English
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Summary:Commonality analysis partitions the proportion of explained variance in the dependent variable or variables that is accounted for by the independent variables. Both variances unique to independent variables and variances common to sets of independent variables are obtained. An algorithm is described for computing these variance components for both the single and multiple dependent variable case. An associated program selects the proper procedure, multiple regression or canonical correlation, and provides a table of all variance components.
ISSN:0013-1644
1552-3888
DOI:10.1177/001316448004000317