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ERIC Number: ED408308
Record Type: Non-Journal
Publication Date: 1997-Jan
Pages: 35
Abstractor: N/A
Reference Count: N/A
Canonical Correlation Analysis as the General Linear Model.
Vidal, Sherry
The concept of the general linear model (GLM) is illustrated and how canonical correlation analysis is the GLM is explained, using a heuristic data set to demonstrate how canonical correlation analysis subsumes various multivariate and univariate methods. The paper shows how each of these analyses produces a synthetic variable, like the Yhat variable in regression. Ultimately these synthetic variables are actually analyzed in all statistics, a fact that is important to researchers who want to understand the substance of their statistical analysis. The illustrative (fictitious) example involves the relationship between a set of marital happiness characteristics, including a marital satisfaction score and a frequency of sex score, and a set of personal characteristics, which includes IQ scores and overall religiosity. The latent constructs, marital happiness and personal characteristics, are the sets of variables that are examined. A brief summary of the canonical correlation analysis is presented, and how canonical correlation subsumes regression, factorial analysis of variance, and T-tests is discussed. The discussion makes it clear that the "F" statistic is not the sole statistic of interest to researchers. The use of canonical correlation as GLM can help students and researchers comprehend the similarities between models as well as the different statistics that are important in all analyses, such as synthetic variables. (Contains 6 figures, 7 tables, and 18 references.) (SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A