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The unpaired comparison of a variable between two independent samples was done in SPSS 22 (IBM, Armonk, NY, USA).
As the two groups do not have the same number of data items, the t test was used to analyse the means of the differences between two independent samples.
Comparisons between two independent samples were performed using two-tailed homoscedastic Student's t-tests.
Mann–Whitney U-tests were used to calculate asymptotic significance between two independent samples.
Differences between two independent samples were analyzed by Mann-Whitney test.
Levels of significance for comparisons between two independent samples were determined using the Student's t-test.
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Non-parametric data was analysed using the Mann–Whitney U-test to assess differences between two independent sample groups.
We aimed for a power of 80%% to detect a minimum difference in the main outcome measures between two independent sample means, at alpha.05 [ 22].
Comparisons of the plasma KLK6 levels between two independent sample cohorts were assessed by the Mann-Whitney U test, and those among more than two independent cohorts were assessed by the Kruskal-Wallis H test.
Seven SNPs showed consistent association between the two independent samples (Additional file 1 Table S2), and six of them were located within the PPARGC1B gene.
Only two SNPs, however, showed consistent association between the two independent samples (Additional file 1 Table S2), and none of the associations survived Bonferroni correction for multiple testing in the combined samples (smallest Pcorrected = 0.198).
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between two independent raters
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between two independent groups
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