This Article Full Text (OnlineFirst PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Scopus Google Scholar Articles by Tonidandel, S. Articles by LeBreton, J. M. Social Bookmarking                         What's this?

Determining the Relative Importance of Predictors in Logistic Regression: An Extension of Relative Weights Analysis

^* To whom correspondence should be addressed. E-mail: sctonidandel{at}davidson.edu.

	Abstract

Techniques such as dominance analysis and relative weight analysis have been proposed recently to evaluate more accurately predictor importance in ordinary least squares (OLS) regression. Similar questions of predictor importance also arise in instances where logistic regression is the primary mode of analysis. This article presents an extension of relative weight analysis that can be applied in logistic regression and thus aids in the determination of predictor importance. We briefly review relative importance techniques and then discuss a new procedure for calculating relative importance estimates in logistic regression. Finally, we present a substantive example applying this new approach to an example data set.

First published on August 4, 2009
Organizational Research Methods 2009, doi:10.1177/1094428109341993


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?