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To address multiple comparisons, all statistical maps were assigned thresholds at p < 0.005 (voxel level), and the false discovery rate (FDR) was corrected to p < 0.05 at the cluster level.
After adjusting for multiple comparisons all p-values were > 0.05.
Because of multiple comparisons, all P values were two sided (P<0.01).
P-values were not adjusted for multiple comparisons, All two-sided P-values < 0.05 were determined to be statistically significant.
Repeated measures Friedman's test with Dunn's correction for multiple comparisons (all time points to the pre-operative baseline) was used for within-group analysis.
In an effort to minimize the risk of falsely identifying significant results with multiple comparisons, all variables were specified and judged a priori to be clinically sound.
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To compare CPT values between controls, headache groups and subcategory of headache patients' features, we used independent unpaired samples (with unequal variances) t test and Bonferroni correction for multiple comparison; all p values were two-sided.
We did not adjust for all multiple comparisons for all SNPs in all types of lymphoma.
Analysis of variance (ANOVA) and multiple comparisons of all quality parameters were performed among all NILs within each Glu-3 group (Table 2, Additional file 2: Tables S2, S3 and S4).
The results were not adjusted for multiple comparisons, because all outcomes of interest were nominated a priori and such adjustment would likely have rendered all findings of interest, despite their clinical importance, nonsignificant [ 44].
Results will not be adjusted for multiple comparisons as all outcomes of interest have been nominated a priori and such adjustment would likely render all findings of interest non-significant, despite their clinical importance [ 26].
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