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For each category, a significance value is computed by a dynamic programming approach (Keller et al, 2007) and all significance values of a certain category have been adjusted for multiple testing using Benjamini Hochberg adjustment (Benjamini & Hochberg, 1995).
Results have not been adjusted for multiple comparisons.
Therefore the results reported have not been adjusted for multiple testing.
Despite the large sample size, neither association is highly significant (P = 0.047 and 0.02 respectively) and the P-values have not been adjusted for multiple hypothesis testing.
All reported p values are two-sided and have not been adjusted for multiple testing.
All P-values are two tailed and have not been adjusted for multiple comparisons.
Similar(42)
The p-values for the correlations are adjusted for multiple testing using the Sidak adjustment.
The resulting p-values were adjusted for multiple testing by Benjamini-Hochberg adjustment.
The P values were adjusted for multiple comparisons (the Tukey-Kramer adjustment).
The resulting p-values were adjusted for multiple testing using Šidák step-up adjustment [33].
The resulting p-values were adjusted for multiple testing by Benjamini-Hochberg [ 17, 18] adjustment.
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CEO of Professional Science Editing for Scientists @ prosciediting.com