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Comparisons between variables using the Student t test and Pearson Chi2.
We applied Dutilleul's modified t test [29] to assess correlations between variables using the program PASSaGE 2.0 [106].
We have also checked for interaction between variables using the logistic regression after creating the interaction terms.
We assessed associations between variables using the Pearson χ-test or the Fisher's exact test for categorical variables.
We determined a priori that certain attitudes may be correlated, and we examined statistical association between variables using the Pearson correlation coefficient.
The significant difference between samples was computed using the Student's t test and correlation between variables using the Pearson correlation coefficient.
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We analyzed correlations between categorical variables using the χ2 or Fisher's exact test.
We studied the association between the variables using the chi-square test because the data was categorical.
We used version 21 of IBM SPSS to report associations between categorical variables using the Pearson x test at the P < 0.05 level of significance.
Open image in new window Fig. 7 Analysis of the dependence structure between the random variables using the scatter plot.
The simple correlation coefficient was calculated to determine the relationships between the studied morphological variables using the Pearson correlation coefficient.
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