The Annals of Statistics
- Ann. Statist.
- Volume 39, Number 1 (2011), 556-583.
Power-enhanced multiple decision functions controlling family-wise error and false discovery rates
Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Šidák procedure for FWER control and the Benjamini–Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual p-values, as is the case, for example, with the Šidák, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing p-value based procedures whose theoretical validity is contingent on each of these p-value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional “large M, small n” data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.
Ann. Statist., Volume 39, Number 1 (2011), 556-583.
First available in Project Euclid: 15 February 2011
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Benjamini–Hochberg procedure Bonferroni procedure decision process false discovery rate (FDR) family wise error rate (FWER) Lagrangian optimization Neyman–Pearson most powerful test microarray analysis reverse martingale missed discovery rate (MDR) multiple decision function and process multiple hypotheses testing optional sampling theorem power function randomized p-values generalized multiple decision p-values ROC function Šidák procedure
Peña, Edsel A.; Habiger, Joshua D.; Wu, Wensong. Power-enhanced multiple decision functions controlling family-wise error and false discovery rates. Ann. Statist. 39 (2011), no. 1, 556--583. doi:10.1214/10-AOS844. https://projecteuclid.org/euclid.aos/1297779856
- Supplementary material: Supplement to “Power-Enhanced Multiple Decision Functions Controlling Family-Wise Error and False Discovery Rates”. The proofs of lemmas, propositions, theorems and corollaries are provided in this supplemental article .