Key result
Heart rate spectrum factor analysis explores statistical criteria validity and Spearman correlations for unnormalized variables.
This methodological study evaluates statistical approaches, such as the principle components method and Varimax Rotation, for conducting factor analysis on the heart rate spectrum.
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Cautions against unvalidated factor analysis in heart rate spectra; leaves open optimal criteria for Spearman use on unnormalized variables.
The methodical problems of the factor analysis of the heart rate spectrum have been considered: the multi-variate normal assumption, factorability of the intercorrelation matrix, criteria for determining the number of factors, and the validity of the factor analysis model. Unnormalized and normalized variables, the matrices of Pearson's and Spearman's correlation coefficients were used. In the process of the factor analysis (principle components method, Varimax Rotation), the restrictions and the possibility of different statistical criteria and procedures were explored. The meaning of the selected factors and the possibility of using the intercorrelation matrix of Spearman coefficients for unnormalized variables were considered.
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V. A. Mashin (2011) studied Heart rate spectrum analysis. Factor analysis was evaluated. Factor analysis of the heart rate spectrum explored the validity of statistical criteria and the use of Spearman correlation coefficients for unnormalized variables.
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