Regression Commonality Analysis: A Technique for Quantitative Theory Building

Author:

Nimon Kim1,Reio Thomas G.2

Affiliation:

1. University of North Texas, Denton, TX, USA,

2. Florida International University, Miami, FL, USA

Abstract

When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality analysis to more completely interpret their regression effects and thereby inform theory. Using an empirical example from published literature, readers will see how regression commonality analysis can uncover important theoretical relationships that might be left undetected by only examining beta weights.

Publisher

SAGE Publications

Subject

Earth-Surface Processes

Reference26 articles.

1. Use of Structure Coefficients in Published Multiple Regression Articles: β is not Enough

2. Regression Diagnostics

3. Frederick, B.N. ( 1999). Partitioning variance in the multivariate case: A step-by-step guide to canonical commonality analysis. In B. Thompson (Ed.), Advances in social science methodology (Vol. 5, pp. 305-318). StaMford, CT : JAI.

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