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One sample t test was used for quantitative variables.
Note that these two measures of intergenerational mobility can only be used for quantitative variables.
Frequency and percentages were used for quantitative variables, while mean and standard deviation were used for qualitative data.
For statistical analysis, SPSS v20.0 for comparison of qualitative variables the χ2 test and Student´s t test was used for quantitative variables.
The Chi-square test was used for qualitative variables, two-tailed Student's paired t-test was used for quantitative variables and Relative Risk (RR) was calculated for interpretation.
Median and interquartile ranges were used for quantitative variables, according to the data distribution.
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Parametric Student t-test or Non-parametric Mann-Whitney U test were used for quantitative variable comparisons, according to distribution characteristics.
When analysing predictors for cold sensitivity severity, the Spearman rank correlation (r S coefficient) were used for quantitative predictive variables, Mann–Whitney U-Test for dichotomous variables and Kruskal-Wallis Test for multiple categorical data.
When analysing predictors for cold sensitivity severity (CISS score) the Spearman rank correlation (r S ) coefficient were used for quantitative predictive variables, the Mann–Whitney U-Test for dichotomous variables and the Kruskal-Wallis Test for multiple categorical data.
For descriptive analysis, absolute frequencies were used for all categorical variables; central trend and dispersion measurement (mean, standard deviation) were used for quantitative continuous variables.
Frequencies and percentages have been adopted to summarize qualitative variables, while tools of descriptive statistics such as mean (± SD, standard deviation) and median was used for quantitative numerical variables.
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