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Correlation between numerical variables was expressed using Spearman's correlation coefficient.
The interdependence between numerical variables was performed by the use of the Spearman rank correlation test.
Correlation between numerical variables was estimated with the Pearson's correlation coefficient.
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Correlations between numerical variables were calculated using the non-parametric Spearman's rank correlation coefficient (rho).
Correlation coefficients between numerical variables were calculated as Spearman's rank test.
Differences between numerical variables were analysed by Student's t test or using the Mann-Whitney test.
Correlation between different numerical variables was analyzed by Spearman's test.
The relationship between two numerical variables was tested using the Pearson's Correlation Coefficient whereas Chi square was used to test for association between differences in proportions.
The shape of the relationships between MRSA-persistent carriage and numerical variables was studied by means of non-parametric or semiparametric regression modelling (smoothing) using PROC GAM to relax the assumption of linearity.
Distribution of numerical variables was tested using Kolmogorov-Smirnov test.
Associations between categorical data were examined using the χ-test, χ-test for trend and Fisher's exact test when expected cell counts were less than 5. Associations between categorical and numerical variables were assessed using analysis of variance.
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