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Association between variables was calculated by Spearman Rank Order Correlations.
Effect modification between variables was calculated by means of dummy variables as proposed by Rothman (27).
Relationship between variables was calculated using the Spearman correlation coefficient (indicated as R in the text).
The relationship between variables was calculated using Pearson's or Spearman's correlation coefficient, whichever appropriate.
The strength of association between variables was calculated using Pearson's method for parametric variables and Spearman's ρ-correlation test for nonparametric contrasts.
The variance inflation factor (a measure of the increase in model variance due to correlation between variables) was calculated for each exposure of interest to assess the effect of correlation between variables.
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Correlations between variables were calculated with Spearman test.
The minimal redundancy between variables is calculated by finding the mutual information scores between variables.
Multiple and simple logistic regressions between variables were calculated.
Correlations between variables were calculated using Pearson's correlation coefficient.
Correlations between variables were calculated using Kendall's coefficient.
More suggestions(17)
between variables was estimated
between variables was computed
between values was calculated
between variables was investigated
between variables was checked
between variables was excluded
between variables was measured
between uniques was calculated
between bipartitions was calculated
between samples was calculated
between variables was analysed
between clades was calculated
between sites was calculated
between columns was calculated
between studies was calculated
between species was calculated
between reactions was calculated
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