University of Illinois Urbana-Champaign

Commonality Analysis: Demonstration of an SPSS Solution for Regression Analysis

Nimon, Kim; Gavrilova, Mariya

Content Files
iSchoolCommonalityPosterFinal.pdf

Permalink

https://hdl.handle.net/2142/15062

Description

Title
Commonality Analysis: Demonstration of an SPSS Solution for Regression Analysis
Author(s)
  • Nimon, Kim
  • Gavrilova, Mariya
Issue Date
2010-02-03
Keyword(s)
  • Commonality analysis
  • multicollinearity
  • suppression
Date of Ingest
2010-03-02T16:15:42Z
Abstract
Multiple regression is a widely used technique to study complex interrelationships among people, information, and technology. In the face of multicollinearity, researchers encounter challenges when interpreting multiple linear regression results. Although standardized function and structure coefficients provide insight into the latent variable ( ) produced, they fall short when researchers want to fully report regression effects. Regression commonality analysis provides a level of interpretation of regression effects that cannot be revealed by only examining function and structure coefficients. Importantly, commonality analysis provides a full accounting of regression effects which identifies the loci and effects of suppression and multicollinearity. Conducting regression commonality analysis without the aid of software is laborious and may be untenable, depending on the number of predictor variables. A software solution in SPSS is presented for the multiple regression case and demonstrated for use in evaluating predictor importance.
Type of Resource
text
Genre of Resource
Conference Poster
Permalink
http://hdl.handle.net/2142/15062

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