Downloads provided by UsageCountsFalse discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study
ARC| Industrial Transformation Training Centres - Grant ID: IC170100035 ,
ARC| Discovery Projects - Grant ID: DP170100907 ,
ARC| Discovery Early Career Researcher Award - Grant ID: DE170101134
Nguyen, Hien D.; Yee, Yohan; McLachlan, Geoffrey J.; Lerch, Jason P.;
False discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study
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.
Peer Reviewed
- Universitat Polite`cnica de Catalunya Spain
- University of Queensland Australia
- University of Queensland Australia
- Universitat Politècnica de Catalunya Spain
- Autonomous University of Barcelona Spain
Estadística matemàtica, grouped data, Discrete support, Classificació AMS::62 Statistics::62F Parametric inference, 310, 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
Estadística matemàtica, grouped data, Discrete support, Classificació AMS::62 Statistics::62F Parametric inference, 310, 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
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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