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Bonferroni adjustments for multiple testing negated all associations.
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In the present study, Bonferroni adjustments for multiple testing negate all associations.
Even when applied properly, multiple testing corrections do not negate biases inadvertently incorporated into experimental design and data analysis that may also lead to spurious results.
Using Bonferroni correction would be overly conservative; the existance of marginal effects negates the multiple testing cost.
No correction for multiple testing was included.
No multiple testing corrections were applied.
Adjustment for multiple testing was not done.
No corrections for multiple testing were performed.
We do not correct for multiple testing.
P-values were corrected for multiple testing.
No adjustments for multiple testing were performed.
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