Abstract
In Chaps. 7 and 8, our focus has been on describing some of the technical aspects of reciprocal averaging (and canonical correlation analysis), so that one can obtain row and column scores that maximize the association between the variables of a two-way contingency table. The foundations under which, such discussions are laid, rests upon the assumption that the cell frequencies of the contingency table are assumed to be Poisson random variables. This is apparent by observing that for the \(\left( i,\,j\right) \)th cell it is defined \(Z_{ij}\).
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Nishisato, S., Beh, E.J., Lombardo, R., Clavel, J.G. (2021). On the Analysis of Over-Dispersed Categorical Data. In: Modern Quantification Theory. Behaviormetrics: Quantitative Approaches to Human Behavior, vol 8. Springer, Singapore. https://doi.org/10.1007/978-981-16-2470-4_11
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