A modified Benjamini–Hochberg multiple comparisons procedure for controlling the false discovery rate

When performing simultaneous statistical tests, the Type I error concept most commonly controlled by analysts is the familywise error rate, i.e., the probability of committing at least one Type I error. However, this criterion is unduly stringent for some practical situations and therefore may not b...

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Bibliographic Details
Published in:Journal of statistical planning and inference 2002-06, Vol.104 (2), p.351-362
Main Authors: Kwong, Koon Shing, Holland, Burt, Cheung, Siu Hung
Format: Article
Language:English
Subjects:
Exact sciences and technology
Familywise error rate
FDR
Linear inference, regression
Mathematics
MBH
Positive regression dependency
Probability and statistics
Sciences and techniques of general use
Statistics
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Summary:When performing simultaneous statistical tests, the Type I error concept most commonly controlled by analysts is the familywise error rate, i.e., the probability of committing at least one Type I error. However, this criterion is unduly stringent for some practical situations and therefore may not be appropriate. An alternative concept of error control was provided by Benjamini and Hochberg (J. Roy. Statist. Soc. B 57 (1995) 289) who advocate control of the expected proportion of falsely rejected hypotheses which they term the false discovery rate or FDR. These authors devised a step-up procedure for controlling the FDR. In this article, when the joint distribution of test statistics is known, continuous, and positive regression dependent on each one from a subset of true null hypotheses, we derive and discuss a modification of their procedure which affords increased power. An example is provided to illustrate our proposed method.
ISSN:0378-3758
1873-1171
DOI:10.1016/S0378-3758(01)00252-X