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ERIC Number: ED111829
Record Type: Non-Journal
Publication Date: 1973-Mar-2
Pages: 53
Abstractor: N/A
Reference Count: N/A
Beaton, Albert E., Jr.
Commonality analysis is an attempt to understand the relative predictive power of the regressor variables, both individually and in combination. The squared multiple correlation is broken up into elements assigned to each individual regressor and to each possible combination of regressors. The elements have the property that the appropriate sums not only add to squared multiple correlations with all regressors, but also to the squared multiple correlation of any subset of variables, including the simple correlations. Commonality analysis may be used as a procedure to guide a stepwise regression. Commonality analysis does not tell us anything that cannot be deduced from a table of squared multiple correlations. However, commonality analysis does help us make comparisons in an organized manner. The purpose of this paper is to explore commonality procedures, to develop its properties, and to present a multivariate generalization for the explorations of commonality in a situation where there is more than one regressor. A new computer-oriented algorithm is also presented. (Author/BJG)
Publication Type: Reports - Research
Education Level: N/A
Audience: N/A
Language: N/A
Sponsor: N/A
Authoring Institution: N/A