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ERIC Number: ED395959
Record Type: Non-Journal
Publication Date: 1996-Jan-27
Pages: 13
Abstractor: N/A
Reference Count: N/A
Canonical Commonality Analysis.
Leister, K. Dawn
Commonality analysis is a method of partitioning variance that has advantages over more traditional "OVA" methods. Commonality analysis indicates the amount of explanatory power that is "unique" to a given predictor variable and the amount of explanatory power that is "common" to or shared with at least one predictor variable. This paper outlines and discusses the steps of commonality analysis specific to canonical correlation analysis using a heuristic example to make the discussion more concrete. The first step in canonical commonality analysis is to perform a canonical correlation analysis in order to derive the standardized canonical function coefficients and the canonical functions. Step two is to calculate the criterion composite scores, also called variate scores. The third step is to conduct multiple regression on the synthetic composite criterion variables using all possible combinations of the predictor variables. The final step is to calculate the unique and common variance partitions. The advantages and potential limitations of commonality analysis are discussed. An appendix presents a computer program for the analysis. (Contains four tables and seven references.) (Author/SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A