Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods.
Author(s) -
Mikel Aickin,
Howard Gensler
Publication year - 1996
Publication title -
american journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.284
H-Index - 264
eISSN - 1541-0048
pISSN - 0090-0036
DOI - 10.2105/ajph.86.5.726
Subject(s) - bonferroni correction , statistical hypothesis testing , statistical significance , statistical power , test (biology) , statistics , multiple comparisons problem , public health , medicine , mathematics , econometrics , psychology , biology , pathology , paleontology
Public health researchers are sometimes required to make adjustments for multiple testing in reporting their results, which reduces the apparent significance of effects and thus reduces statistical power. The Bonferroni procedure is the most widely recommended way of doing this, but another procedure, that of Holm, is uniformly better. Researchers may have neglected Holm's procedure because it has been framed in terms of hypothesis test rejection rather than in terms of P values. An adjustment to P values based on Holm's method is presented in order to promote the method's use in public health research.
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