Adjusting for multiple testing - when and how?

Multiplicity of data, hypotheses, and analyses is a common problem in biome dical and epidemiological research. Multiple testing theory provides a fram ework for defining and controlling appropriate error rates in order to prot ect against wrong conclusions. However, the corresponding multiple test pro cedures are underutilized in biomedical and epidemiological research. In th is article, the existing multiple test procedures are summarized for the mo st important multiplicity situations. It is emphasized that adjustments for multiple testing are required in confirmatory studies whenever results fro m multiple tests have to be combined in one final conclusion and decision. In case of multiple significance tests a note on the error rate that will b e controlled for is desirable. (C) 2001 Elsevier Science Inc. All rights re served.