Academic Journal
False discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study
| Title: | False discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study |
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| Authors: | Nguyen, Hien D., Yee, Yohan, McLachlan, Geoffrey J., Lerch, Jason P. |
| Source: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Dipòsit Digital de Documents de la UAB Universitat Autònoma de Barcelona SORT-Statistics and Operations Research Transactions; 2019: Vol.: 43 Núm.: 2 July-December; 237-258 oai:raco.cat:article/361349 Repositori Institucional de la Universitat Rovira i Virgili Universitat Rovira i virgili (URV) |
| Publisher Information: | Institut d'Estadística de Catalunya, 2019. |
| Publication Year: | 2019 |
| Subject Terms: | Estadística matemàtica, grouped data, Discrete support, Classificació AMS::62 Statistics::62F Parametric inference, data quantization, Classificació AMS::62 Statistics::62P Applications, Package, Maximum-Likelihood, Choice, Models, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Anàlisi de supervivència (Biometria), 62 Statistics::62F Parametric inference [Classificació AMS], Empirical-bayes, 2613 Statistics and Probability, 62 Statistics::62N Survival analysis and censored data [Classificació AMS], Projections, Mixture model, discrete support, 62 Statistics [Classificació AMS], Classificació AMS::62 Statistics, mixture model, Histogram, Stria Terminalis, Null Distribution, Estadística matemàtica--Aplicacions, Classificació AMS::62 Statistics::62N Survival analysis and censored data, Data quantization, Grouped data, 62 Statistics::62P Applications [Classificació AMS], 1803 Management Science and Operations Research, false discovery rate control, False discovery rate control, 1804 Statistics, empirical-Bayes, Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], Incompletely observed data, Censored data, Probability and Uncertainty, Networks, Bed Nuclei, incompletely observed data |
| Description: | 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. |
| Document Type: | Article |
| File Description: | application/pdf; application/zip |
| Language: | English |
| DOI: | 10.2436/20.8080.02.87 |
| Access URL: | http://hdl.handle.net/2117/362065 https://ddd.uab.cat/record/218269 http://hdl.handle.net/20.500.11797/RP4691 https://hdl.handle.net/2117/362065 https://espace.library.uq.edu.au/view/UQ:2d32f46/UQ2d32f46_OA.pdf https://dialnet.unirioja.es/servlet/articulo?codigo=7214091 https://espace.library.uq.edu.au/view/UQ:2d32f46 |
| Rights: | CC BY NC ND |
| Accession Number: | edsair.dedup.wf.002..bbd2a0f39bdd5f7c53222a5cca3d0a2d |
| Database: | OpenAIRE |
| DOI: | 10.2436/20.8080.02.87 |
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