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 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.
Journal of Statistical Planning and Inference
KWONG, Koon Shing; HOLLAND, Burt; and Cheung, Siu Hung.
A Modified Benjamini–Hochberg Multiple Comparisons Procedure for Controlling the False Discovery Rate. (2002). Journal of Statistical Planning and Inference. 104, (2), 351-362. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/316