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EDITOR
Recently, Perneger tried to establish that adjustments for
multiple testing are unnecessary.1 However, the main arguments against multiplicity adjustments are based on
misunderstanding of and a lack of knowledge about simultaneous
statistical inference.
Firstly, Perneger equated multiple test adjustments with Bonferroni corrections. The Bonferroni procedure ignores dependencies among the data and is therefore much too conservative if the number of tests is large.2 Hence, we agree with Perneger that the Bonferroni method should not be routinely used. This is, however, no argument against the use of multiplicity adjustments in general, as there are several alternative multiple test procedures which were totally ignored by Perneger.3
Secondly, Perneger argued that multiple test adjustments are concerned
only with the global null hypothesis that all individual null
hypotheses are true simultaneously. This is not true. The best multiple
test procedures control the multiple level (also called experimentwise
error rate in the strong