Commonality Analysis: Understanding Variance Contributions to Overall Canonical Correlation Effects of Attitude Toward Mathematics on Geometry Achievement

Abstract

Canonical correlation analysis is the most general linear model subsuming all other univariate and multivariate cases (Kerlinger & Pedhazur, 1973; Thompson, 1985, 1991). Because “reality” is a complex place, a multivariate analysis such as canonical correlation analysis is demanded to match the research design. It is the purpose of this paper to increase the awareness and use of canonical correlation analysis and, specifically to demonstrate the value of the related procedure of commonality analysis. Commonality analysis provides the researcher with information regarding the variance explained by each of the measured variables and the common contribution from one or more of the other variables in a canonical analysis (Beaton, 1973; Frederick, 1999). This paper identifies confidence as contributing the most unique variance to the model, being more important than either intrinsic value or worry to
geometry content knowledge and spatial visualization.