ERIC Number: ED282904
Record Type: RIE
Publication Date: 1987-Apr-16
Reference Count: 0
Fundamentals of Canonical Correlation Analysis: Basics and Three Common Fallacies in Interpretation.
Canonical correlation analysis is illustrated and three common fallacious interpretation practices are described. Simply, canonical correlation is an example of the bivariate case. Like all parametric methods, it involves the creation of synthetic scores for each person. It presumes at least two predictor variables and at least two criterion variables. Weights, usually labelled standardized function coefficients, are applied to each individual's data to yield the synthetic variables which are the basis for canonical analysis. However, in canonical correlation, several sets of weights and synthetic variables can be created. Structure coefficients and index coefficients may also be computed. The interpretation of canonical results is challenging because of the myriad of coefficients produced. The three common fallacies to be avoided are: (1) interpreting structure coefficients while ignoring function coefficients; (2) interpreting redundancy coefficients; and (3) failing to employ commonality analysis. When researchers are aware of these pitfalls, canonical correlation analysis can be a powerful analytic method that may be the best technique in a complex situation. (GDC)
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Authoring Institution: N/A
Note: Paper presented at the Annual Meeting of the Society for Multivariate Experimental Psychology, Southwestern Division (New Orleans, LA, April 16, 1987).