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Holm correction is a statistical method for controlling the family-wise error rate in multiple comparisons, and it is less conservative and more statistically powerful than Bonferroni correction.
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11/6/2026
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UnverifiedHolm correction sorts p-values from smallest to largest and compares them in turn against the adjusted significance threshold α/(m-i+1), stopping subsequent tests as soon as one test is not significant; it is less conservative and has higher statistical power than Bonferroni correction, and does not require the tests to be independent.71% similarUnverifiedBonferroni 校正是最保守的多重比较校正方案，将显著性阈值除以比较次数；Benjamini-Hochberg FDR 校正更宽松，控制所有显著结果中假阳性的比例67% similarUnverified统计功效（Statistical Power）通常设为 80% 以上，多重比较问题可通过 Bonferroni 校正或 FDR 控制等方法调整66% similarUnverifiedThe fairness standard ProPublica used is "group balance in predictive error rates," while the company that developed COMPAS countered that the system is calibrated on "predictive accuracy" for both groups, i.e., the actual recidivism rate corresponding to a high risk score is roughly the same across races.66% similarVerifiedWhen samples are severely imbalanced, Accuracy becomes misleading—a model that predicts everyone as healthy can still achieve an accuracy of over 99%.65% similar
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