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The χ test (Fisher's exact method) was used to compare between variables.
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The categorical variables were presented as percentages and were compared between variables with the Chi-square.
AUCs can be considered the probability that the variable is at a higher level for case compared with control, and can be compared between variables using the test described by Hanley[ 13].
We used chi-square to compare distributions between categorical variables and t-test to compare between numerical variables.
The main outcome (median estimated tissue YM in kPa) was reported as a continuous variable and was compared between exposure variables using Wilcoxon Rank-Sum tests.
Weak MI is sufficient to compare associations between variables, whereas strong MI is necessary to compare latent means.
Paired and non-paired t-tests were used to compare data between variables.
Chi square test was used to compare proportions between variables where appropriate, at 95% confidence level.
The Chi-square test was used to compare proportions between variables.
The Wilcoxon signed rank test for paired samples was used to compare differences between variables in matched samples.
For the bivariate analysis of the data we used the Student's t test for independent groups to compare between means of a continuous variable and the Chi-square test to compare between categorical variables.
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