A Monte Carlo Study of the Stability of Canonical Correlations, Canonical Weights and Canonical Variate-Variable Correlations

Abstract

A Monte Carlo study was run to check the stability of canonical correlations, canonical weights, and canonical variate-variable correlations. Eight data matrices were selected from the literature for the canonical analyses, with the number of variables ranging from 7 to 41. The results showed that the canonical correlations are very stable upon replication. The results also indicated that there is no solid evidence for concluding that the components are superior to the coefficients, a t least not in terms of being more reliable. However, the number of subjects per variable necessary to achieve re1i:tbility in detecting the most important variables, using components or coefficients, was quite large, ranging from 42/1 to 68/1.