Determining Predictor Importance In Multiple Regression Under Varied Correlational And Distributional Conditions

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Published Nov 1, 2002
DOI : https://doi.org/10.22237/jmasm/1036110360

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Tiffany A. Whittaker
The University of Texas at Austin
Rachel T. Fouladi
University of Texas M.D. Anderson Cancer Center at Houston
Natasha J. Williams
University of Texas at Austin

Abstract

This study examines the performance of eight methods of predictor importance under varied correlational and distributional conditions. The proportion of times a method correctly identified the dominant predictor was recorded. Results indicated that the new methods of importance proposed by Budescu (1993) and Johnson (2000) outperformed commonly used importance methods.

Article Details

Issue
Vol. 1 (2002): Issue 2
Section
Articles