False discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study
Nguyen, Hien (La Trobe University (Victòria, Austràlia). Department of Mathematics and Statistics)
Yee, Yohan (Hospital for Sick Children (Toronto, Canadà). Mouse Imaging Centre)
McLachlan, Geoffrey (University of Queensland. School of Mathematics and Physics)
Lerch, Jason (Hospital for Sick Children (Toronto, Canadà). Mouse Imaging Centre)

Data:	2019
Resum:	False discovery rate (FDR) control is important in multiple testing scenarios that are common in neuroimaging experiments, and p-values from such experiments may often arise from some discretely supported distribution or may be grouped in some way. Two situations that may lead to discretely supported distributions are when the p-values arise from Monte Carlo or permutation tests are used. Grouped p-values may occur when p-values are quantized for storage. In the neuroimaging context, grouped p-values may occur when data are stored in an integer-encoded form. We present a method for FDR control that is applicable in cases where only p-values are available for inference, and when those p-values are discretely supported or grouped. We assess our method via a comprehensive set of simulation scenarios and find that our method can outperform commonly used FDR control schemes in various cases. An implementation to a mouse imaging data set is used as an example to demonstrate the applicability of our approach.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Censored data ; Data quantization ; Discrete support ; Empirical-bayes ; False discovery rate control ; Grouped data ; Incompletely observed data ; Mixture model
Publicat a:	SORT : statistics and operations research transactions, Vol. 43 Núm. 2 (July-December 2019) , p. 237-258, ISSN 2013-8830

Adreça alternativa: https://raco.cat/index.php/SORT/article/view/361349
DOI: 10.2436/20.8080.02.87

22 p, 1.1 MB

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