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Sensitivity and specificity were compared between these subgroups using the z-test [ 36].
Mean FT4 and mean TSH were compared between these subgroups using one way ANOVA.
Post hoc analyses were performed to investigate differences in patient characteristics and treatment between these subgroups, using chi-square tests.
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Clinicopathological parameters were compared between different subgroups using student's t test for continuous variables and chi-square test for categorical variables.
18 21 Allele frequencies were compared between cases and controls and between phenotypic subgroups using χ tests of 2 × 2 tables.
We also used gene ontology analysis to identify altered pathways within and between glioma subgroups using the ToppGene system [ 5].
We report differences in Hb between different subgroups using independent samples T-tests, reporting the mean difference and probability (p).
Analysis of variance and Student t tests were used to determine the statistical significance (p<0.05) of the differences between population subgroups using the SPSS V.20.0 statistics program.
The relative gene expression levels were compared between various subgroups using Kruskal Wallis test (>2 groups) and Mann–Whitney U-test (two groups).
Furthermore, we evaluated the changes in pulmonary function during work shift in each subgroup of tea workers using paired t test and between two subgroups using two-sample t test.
One-year mortality was compared between subgroups using univariate Kaplan Meier curves.
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