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The Bonferroni method was applied to allow for multiple significance tests with adjusted p-values <0.01 regarded as statistically significant.
We adjusted for multiple significance tests by applying a sequential Bonferroni adjustment within each of the clusters [20].
No adjustments were made for multiple significance testing [ 15].
No corrections were made for multiple significance testing.
Corrections for multiple significance tests were performed using a sequential Bonferroni-type correction [ 57].
We required the 99% CI in order to allow for multiple significance testing.
Similar(48)
The experience of the EU is of multiple significances for the future development and cooperation of East Asia.
Scores can be calculated and tested for multiple different significance thresholds levels of statistical significance.
The significance of their differences was tested with the paired t test with Bonferroni correction for multiple comparisons (significance level α = 0.05/m, with m = number of multiple hypothesis tested).
The significance of the likelihood ratio tests were tested using a Bonferroni correction to correct for multiple testing (significance level = 0.05/83 where 83 is the number of markers = 6 × 10-4).
The analysis generated a raw (unadjusted for multiple comparisons) significance map showing raw p-values exceeding 0.05 across the surface.
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