The control of the false discovery rate in fixed sequence multiple testing
Document Type
Article
Publication Date
1-1-2017
Abstract
Controlling false discovery rate (FDR) is a powerful approach to multiple testing. In many applications, the tested hypotheses have an inherent hierarchical structure. In this paper, we focus on the fixed sequence structure where the testing order of the hypotheses has been strictly specified in advance. We are motivated to study such a structure, since it is the most basic of hierarchical structure, yet it is often seen in real applications such as statistical process control and streaming data analysis. We first consider a conventional fixed sequence method that stops testing once an acceptance occurs, and develop such a method controlling FDR under both arbitrary and negative dependencies. The method under arbitrary dependency is shown to be unimprovable without losing control of FDR and, unlike existing FDR methods; it cannot be improved even by restricting to the usual positive regression dependence on subset (PRDS) condition. To account for any potential mistakes in the ordering of the tests, we extend the conventional fixed sequence method to one that allows more but a given number of acceptances. Simulation studies show that the proposed procedures can be powerful alternatives to existing FDR controlling procedures. The proposed procedures are illustrated through a real data set from a microarray experiment.
Identifier
85035771980 (Scopus)
Publication Title
Electronic Journal of Statistics
External Full Text Location
https://doi.org/10.1214/17-EJS1359
ISSN
19357524
First Page
4649
Last Page
4673
Issue
2
Volume
11
Grant
DMS-1006021
Fund Ref
Natural Resources Wales
Recommended Citation
Lynch, Gavin; Guo, Wenge; Sarkar, Sanat K.; and Finner, Helmut, "The control of the false discovery rate in fixed sequence multiple testing" (2017). Faculty Publications. 10043.
https://digitalcommons.njit.edu/fac_pubs/10043
