Discounting Correlations.. Alternative Descriptives?
I am comparing a similar calculation for the same sample via two different methods. My goal is to show that the second measure offers more rich / complete data than the first so I can justify that it is potentially a better measure. My problem stems from the very high correlation of the two measures potentially suggesting the traditional measure may be nearly the same as the new measure.
Can someone give me arguments justifying why correlations are somewhat inapropriate for comparing these two measures and suggest what other descriptive statistics will help me demostrate that the second measure offers significantly more data than the first?
I don’t understand how the two measures in the two ordinary histograms (and last 3D histogram which combines the other two histograms) can be correlated so highly (see attachments for pictures). The correlation between the two measures is .92 and thus the first could be said to explain 84% of the variance in the second. It seems that the second offers a much richer set of values in its distribution (In my sample the first measure calculates 135,000 zeros which the new method calculates some continuous set of values from 0 to about .6).
Obviously the utility of the measures are actually in their correlation with other variables of interest but it seems that such a high correlation between these two measures would translate into similar correlations of each with other variables (thus defeating my argument).
Thank you very much in advance for any help someone can give.
-Rob
I am comparing a similar calculation for the same sample via two different methods. My goal is to show that the second measure offers more rich / complete data than the first so I can justify that it is potentially a better measure. My problem stems from the very high correlation of the two measures potentially suggesting the traditional measure may be nearly the same as the new measure.
Can someone give me arguments justifying why correlations are somewhat inapropriate for comparing these two measures and suggest what other descriptive statistics will help me demostrate that the second measure offers significantly more data than the first?
I don’t understand how the two measures in the two ordinary histograms (and last 3D histogram which combines the other two histograms) can be correlated so highly (see attachments for pictures). The correlation between the two measures is .92 and thus the first could be said to explain 84% of the variance in the second. It seems that the second offers a much richer set of values in its distribution (In my sample the first measure calculates 135,000 zeros which the new method calculates some continuous set of values from 0 to about .6).
Obviously the utility of the measures are actually in their correlation with other variables of interest but it seems that such a high correlation between these two measures would translate into similar correlations of each with other variables (thus defeating my argument).
Thank you very much in advance for any help someone can give.
-Rob
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