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Title: Chebyshev's inequality for non-parametric testing with small N and α in microarray research
Alternate Title: Chebyshev's inequality for non-parametric testing with small N and alpha in microarray research
Author (s): Allison, D.B.
Beasley, T.M.
Brand, J.P.L.
Gadbury, Gary L.
Mountz, J.D.
Page, G.P.
Department/Lab Affiliations: Cloud & Aerosol Science Lab
Mathematics & Statistics
Keywords: Tchebysheff's inequality
alpha
probability distribution
Issue Date: 2004
Publisher: Royal Statistical Society
Citation: Beasley TM, Page GP, Brand JPL, Gadbury GL, Mountz JD, Allison DB (2004). Chebyshev’s inequality for non-parametric testing with small N and α in microarray research. Journal of the Royal Statistical Society, Series C (Applied Statistics). 53, 95 – 108.
Abstract: Microarrays are a powerful new technology that allow for the measurement of the expression of thousands of genes simultaneously. Owing to relatively high costs, sample sizes tend to be quite small. If investigators apply a correction for multiple testing, a very small p-value will be required to declare significance. We use modifications to Chebyshev's inequality to develop a testing procedure that is nonparametric and yields p-values on the interval [0, 1]. We evaluate its properties via simulation and show that it both holds the type I error rate below nominal levels in almost all conditions and can yield p-values denoting significance even with very small sample sizes and stringent corrections for multiple testing.
Type: Article - Journal
text
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URL:
http://dx.doi.org/10.1111/j.1467-9876.2004.00428.x
http://scholarsmine.mst.edu/post_prints/SubjectTreatmentInteraction_09007dcc804f09ea.html



titleChebyshev's inequality for non-parametric testing with small N and α in microarray research
title.alternativeChebyshev's inequality for non-parametric testing with small N and alpha in microarray research
contributor.authorAllison, D.B.
contributor.authorBeasley, T.M.
contributor.authorBrand, J.P.L.
contributor.authorGadbury, Gary L.
contributor.authorMountz, J.D.
contributor.authorPage, G.P.
contributor.deptlabCloud & Aerosol Science Lab
contributor.deptlabMathematics & Statistics
subjectTchebysheff's inequality
subjectalpha
subjectprobability distribution
date.issued2004
publisherRoyal Statistical Society
identifier.URI
http://dx.doi.org/10.1111/j.1467-9876.2004.00428.x
identifier.URI
http://scholarsmine.mst.edu/post_prints/SubjectTreatmentInteraction_09007dcc804f09ea.html
identifier.citationBeasley TM, Page GP, Brand JPL, Gadbury GL, Mountz JD, Allison DB (2004). Chebyshev’s inequality for non-parametric testing with small N and α in microarray research. Journal of the Royal Statistical Society, Series C (Applied Statistics). 53, 95 – 108.
description.abstractMicroarrays are a powerful new technology that allow for the measurement of the expression of thousands of genes simultaneously. Owing to relatively high costs, sample sizes tend to be quite small. If investigators apply a correction for multiple testing, a very small p-value will be required to declare significance. We use modifications to Chebyshev's inequality to develop a testing procedure that is nonparametric and yields p-values on the interval [0, 1]. We evaluate its properties via simulation and show that it both holds the type I error rate below nominal levels in almost all conditions and can yield p-values denoting significance even with very small sample sizes and stringent corrections for multiple testing.
typeArticle - Journal
type.DCMITypetext
type.statusPostprint
rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
rights.URI
http://www.rss.org.uk/main.asp?page=0
date.accessioned2007-04-11T17:00:48Z
date.available2007-04-11T17:00:48Z
identifier.persist.URI
http://scholarsmine.mst.edu/post_prints/SubjectTreatmentInteraction_09007dcc804f09ea.html