I have a data that I have used discriminant function analysis with. In the results, one variable has a standardized canonical function coefficient that is greater than 1.0. I didn't think these could be greater than 1 and I am not sure what to make of it.
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1$\begingroup$ how, exactly, are these being standardized? $\endgroup$– Glen_bFeb 19, 2014 at 2:10
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$\begingroup$ I guess what I meant is it possible for standardized canonical correlation coefficients to be greater than 1 (i.e. is it indicative of something wrong)? $\endgroup$– user40530Feb 19, 2014 at 2:40
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$\begingroup$ I can't answer your question until I know in what what the canonical correlation coefficient was 'standardized'. Define 'standardized' in this context. $\endgroup$– Glen_bFeb 19, 2014 at 3:01
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$\begingroup$ IV's were items from factor analysis that were created from self ratings on measures of different problem behaviors (e.g. stealing $50+, using drugs, ect). DV was having/not having ADHD. Does this help? Otherwise, where can I look for how they were standardized in the results? $\endgroup$– user40530Feb 19, 2014 at 3:28
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$\begingroup$ sorry, typo above, should read *in what way the correlation coefficient was standardized'. No, telling me what the variables were doesn't help. I need you to define the quantity your question relates to. How do I know - for certain - what you're asking about? $\endgroup$– Glen_bFeb 19, 2014 at 3:34
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1 Answer
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This link may be helpful: http://www.ssicentral.com/lisrel/techdocs/HowLargeCanaStandardizedCoefficientbe.pdf
Also see this reference: Deegan, J.Jr. (1978). On the Occurrence of Standardized Regression Coefficients Greater Than One. Educational and Psychological Measurement, 38, No. 4, 873-888.
"If there is a single predictor or multiple predictors that are uncorrelated, then the beta values will be confined to the bounds of (-1,1). However, if there are 2 or more predictors that are correlated, positively or negatively, then the beta values may exceed those bounds."
In other words, you probably have multicollinearity issues.
