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A multiple testing correction was performed using the Bonferroni error correction model [ 51].
The scores were adjusted using the standard Bonferroni error correction for multiple testing.
Kruskal Wallis tests were used to identify significantly discriminant taxa (with Bonferroni error correction) between sample groups.
A significance level of p < 0.01 was chosen for analysis of this categorical questionnaire data due to the risk of a type I, Bonferroni error with multiple comparisons.
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Significance levels are compared to a Bonferroni corrected error rate of α = 0.0167.
Bonferroni familywise error rate (FWER) correction was applied for multiple testing.
We conducted pairwise comparisons of the total and subscale PANSS scores between nonsmokers, those with mild dependence and those with severe dependence, using Bonferroni familywise error multiple testing corrections.
We applied Bonferroni familywise-error adjustment.
For example, binding signal on FunctCons or FunctActive elements was higher than that on SeqCons elements for 59%and50%0% of cell type-TF combinations for human and mouse respectively (with a Bonferroni-corrected error rate of 1%; Additional file 1: Figures S13, S14).
■ Log-rank (Mantel Cox) test: Bonferroni correction: alpha error = 0.025.
■ Chi-square test, pairwise differences between groups: Bonferroni correction: alpha error = 0.002778.
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