Interpreting Canonical Correlation Results: Using Yhat Software to Analyze Canonical Variates

• In Event: Multiple Linear Regression: The General Linear Model SIG Special Topics Paper Session

Abstract

This paper presents a comprehensive statistical software solution to aid researchers in interpreting the results of canonical correlation analysis (CCA). Using a heuristic example previously published, we demonstrate how traditional CCA output can be complemented with product measures, relative weights, dominance analysis, and commonalty analysis to aid in the interpretation of canonical effects in the presence of multcollinearity. The solution allows results to be bootstrapped, which offers researchers the opportunity to report confidence intervals and reproducibility measures.

Authors

• Kim Nimon, The University of Texas - Tyler

• Linda Reichwein Zientek, Sam Houston State University