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• W2318147638 abstract "ABSTRACTCanonical correlations are maximized correlation coefficients indicating the relationships between pairs of canonical variates that are linear combinations of the two sets of original variables. The number of non-zero canonical correlations in a population is called its dimensionality. Parallel analysis (PA) is an empirical method for determining the number of principal components or factors that should be retained in factor analysis. An example is given to illustrate for adapting proposed procedures based on PA and bootstrap modified PA to the context of canonical correlation analysis (CCA). The performances of the proposed procedures are evaluated in a simulation study by their comparison with traditional sequential test procedures with respect to the under-, correct- and over-determination of dimensionality in CCA." @default.
• W2318147638 created "2016-06-24" @default.
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• W2318147638 date "2016-03-21" @default.
• W2318147638 modified "2023-09-24" @default.
• W2318147638 title "Parallel analysis approach for determining dimensionality in canonical correlation analysis" @default.
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• W2318147638 doi "https://doi.org/10.1080/00949655.2016.1161044" @default.
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