COMMONALITY ANALYSIS: A METHOD FOR DECOMPOSING EXPLAINED VARIANCE IN MULTIPLE REGRESSION ANALYSES

DAVID R. SEIBOLD, ROBERT D. McPHEE

Research output: Contribution to journalArticle

80 Scopus citations

Abstract

Commonality analysis is a procedure for decomposing R2 in multiple regression analyses into the percent of variance in the dependent variable associated with each independent variable uniquely, and the proportion of explained variance associated with the common effects of predictors. Commonality analysis thus sheds additional light on the magnitude of an obtained multivariate relationship by identifying the relative importance of all independent variables, findings which can be of theoretical and practical significance. In this paper we offer a brief explication of commonality analysis; a step‐by‐step discussion of how communication researchers may perform commonality analyses using output from computer‐assisted statistical analysis programs like SPSS; and we provide an extended example illustrating a commonality analysis.

Original languageEnglish (US)
Pages (from-to)355-365
Number of pages11
JournalHuman Communication Research
Volume5
Issue number4
DOIs
StatePublished - 1979
Externally publishedYes

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ASJC Scopus subject areas

  • Communication
  • Developmental and Educational Psychology
  • Anthropology
  • Linguistics and Language

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