Study of the Relationship between Dependent and Independent Variable Groups by Using Canonical Correlation Analysis with Application
Thanoon Y. Thanoon, Robiah Adnan, Seyed Ehsan Saffari
Abstract
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Thanoon Y. Thanoon, Robiah Adnan, Seyed Ehsan Saffari
Abstract
Open-access reader
Canonical correlation analysis is used to study the relationship between two groups of variables (dependent and independent). Since each group represents the linear combination to a number of variables, canonical correlation analysis measures the relationship between these variables that maximally correlate with linear combinations of another subset of variables. Statistical analysis involves canonical correlation between two groups of variables, canonical variates, standard canonical variates, canonical factor loadings, canonical cross factor loadings for both groups. Test of significance of canonical correlation using Wilk's Lambda showed that the first and second canonical correlation were significant and the third and fourth canonical correlation were insignificant. This method is illustrated by using a real data set. Results obtained by using SPSS program.
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Canonical correlation analysis is used to study the relationship between two groups of variables (dependent and independent). Since each group represents the linear combination to a number of variables, canonical correlation analysis measures the relationship between these variables that maximally correlate with linear combinations of another subset of variables. Statistical analysis involves canonical correlation between two groups of variables, canonical variates, standard canonical variates, canonical factor loadings, canonical cross factor loadings for both groups. Test of significance of canonical correlation using Wilk's Lambda showed that the first and second canonical correlation were significant and the third and fourth canonical correlation were insignificant. This method is illustrated by using a real data set. Results obtained by using SPSS program.
Key concepts: Canonical correlation, Canonical analysis, Canonical correspondence analysis, Mathematics, Correlation, Statistics, Variables, Biology