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ERIC Number: EJ977607
Record Type: Journal
Publication Date: 2012-Apr
Pages: 19
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1531-7714
Interpreting Multiple Linear Regression: A Guidebook of Variable Importance
Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim
Practical Assessment, Research & Evaluation, v17 n9 Apr 2012
Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what and how independent variables contribute to a regression equation. Thus, this paper presents a guidebook of variable importance measures that inform MR results, linking measures to a theoretical framework that demonstrates the complementary roles they play when interpreting regression findings. We also provide a data-driven example of how to publish MR results that demonstrates how to present a more complete picture of the contributions variables make to a regression equation. We end with several recommendations for practice regarding how to integrate multiple variable importance measures into MR analyses. (Contains 6 tables.)
Dr. Lawrence M. Rudner. e-mail: editor@pareonline.net; Web site: http://pareonline.net
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A