Abstract #301520

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JSM 2002 Abstract #301520
Activity Number: 46
Type: Contributed
Date/Time: Sunday, August 11, 2002 : 4:00 PM to 5:50 PM
Sponsor: General Methodology
Abstract - #301520
Title: Univariate Variable Selection Criteria Available in SAS or SPSS
Author(s): Ali Al-Subaihi*+
Affiliation(s): Institute of Public Administration
Address: P. O. Box 205, Riyady, , 11141, Sadui Arabia
Keywords: Monte Carlo study ; Multiple linear regression ; Univariate variable selection
Abstract:

A Monte Carlo study was used to compare the ability of the univariate variable selection criteria that are available in either SAS or SPSS to select the "correct" multiple linear regression model. The performance of the univariate variable selection procedures was investigated for different sample sizes, intercorrelations, and interacorrelations. The results suggested that all procedures' ability to select the "correct" model improved by more than 50% when sample size increases from 25 to 50 or 100, and multicollinearity decreased the ability of all selection criteria to select the "correct" model, whereas the high correlation between the dependent variable (y) and independent variables (X) improved the ability of all procedures to select the correct model. The backward elimination criterion and Schwarz's Bayes information procedure are the best among the automatic search criteria and all-possible-regression procedures, respectively.

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