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Ultimately, the overall quality of the extracted covariance (i.e., the adequacy of the least-squares approximation, equivalent to the usual Determination Coefficient in a classic bivariate linear correlation analysis) is calculated as the achieved percentage of total possible squared covariance between the two sets of synthetic axes.
Bivariate linear correlation analysis was also performed to analyze the relationship of Piwi-like mRNA expression with clinical factors.
We performed a bivariate linear correlation analysis (Spearman-Rho-test) to examine whether the mRNA expression levels of individual Piwi-like genes were correlated with the mRNA expression levels of the other Piwi-like genes in the tumor tissues.
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After having assessed the effects of stimuli, side, and gender, we then analyzed in depth the relationship between the left and right feet in response to visual stimuli using a bivariate Pearson linear correlation analysis.
The associations between serum calcium and metabolic parameters were examined using bivariate linear correlation (Pearson correlation).
The bivariate linear correlation (Pearson) test was performed to identify statistical correlations among spine and arthritis parameters.
Linear correlation analysis was performed to reveal possible correlations.
Correlations were established using Pearson's correlation coefficient (r) in bivariate linear correlations (p < 0.01).
Correlations were established by using Pearson's correlation coefficient (r) in bivariate linear correlations (p < 0.01).
Correlations were obtained by Pearson's correlation coefficient (r) in bivariate linear correlations.
Correlations were established using Pearson's correlation coefficient (r) in bivariate linear correlations (P < 0.01).
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