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Assumptions for CCA

# Assumptions for CCA - AssumptionsofCCA o , ..Gifi(1990

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Assumptions of CCA o Interval level data are assumed. o Linearity of relationships is assumed, though there is a nonlinear canonical correlation procedure available ‐‐ OVERALS . This is found in the SPSS Categories module. Gifi (1990) discusses non linear canonical correlation analysis in his Chapter 6. In the usual form of canonical correlation, however, analysis is performed on the correlation or variance covariance matrices, which reflect linear relationships. Of course, one can insert exponentiated or otherwise nonlinearly transformed variables into either measured variable set in canonical correlation. o Low multicollinearity : To the extent that the variables within the independent sets of variables are highly intercorrelated, the canonical coefficients will be unstable. The coefficients for some variables may be misleadingly low or even negative because variance has already been explained by other variables.

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