# Relative Importance by Averaging over Orderings

Relative Importance by Averaging over Orderings Abstract Many ways have been suggested for explicating the ambiguous concept of relative importance for independent variables in a multiple regression setting. There are drawbacks to all the explications, but a relatively acceptable one is available when the independent variables have a relevant, known ordering: consider the proportion of variance of the dependent variable linearly accounted for by the first independent variable; then consider the proportion of remaining variance linearly accounted for by the second independent variable; and so on. When, however, the independent variables do not have a relevant ordering, that approach fails. The primary suggestion of this article is to rescue the idea by averaging relative importance over all orderings of the independent variables. Variations and extensions of the idea are described. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The American Statistician Taylor & Francis

# Relative Importance by Averaging over Orderings

, Volume 41 (1): 5 – Feb 1, 1987

## Relative Importance by Averaging over Orderings

, Volume 41 (1): 5 – Feb 1, 1987

### Abstract

Abstract Many ways have been suggested for explicating the ambiguous concept of relative importance for independent variables in a multiple regression setting. There are drawbacks to all the explications, but a relatively acceptable one is available when the independent variables have a relevant, known ordering: consider the proportion of variance of the dependent variable linearly accounted for by the first independent variable; then consider the proportion of remaining variance linearly accounted for by the second independent variable; and so on. When, however, the independent variables do not have a relevant ordering, that approach fails. The primary suggestion of this article is to rescue the idea by averaging relative importance over all orderings of the independent variables. Variations and extensions of the idea are described.

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# References (12)

Publisher
Taylor & Francis
Copyright Taylor & Francis Group, LLC
ISSN
1537-2731
eISSN
0003-1305
DOI
10.1080/00031305.1987.10475432
Publisher site
See Article on Publisher Site

### Abstract

Abstract Many ways have been suggested for explicating the ambiguous concept of relative importance for independent variables in a multiple regression setting. There are drawbacks to all the explications, but a relatively acceptable one is available when the independent variables have a relevant, known ordering: consider the proportion of variance of the dependent variable linearly accounted for by the first independent variable; then consider the proportion of remaining variance linearly accounted for by the second independent variable; and so on. When, however, the independent variables do not have a relevant ordering, that approach fails. The primary suggestion of this article is to rescue the idea by averaging relative importance over all orderings of the independent variables. Variations and extensions of the idea are described.

### Journal

The American StatisticianTaylor & Francis

Published: Feb 1, 1987

Keywords: Multiple regression; Causation; Correlation; Variance reduction