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dc.contributor.authorBrien, C. J.
dc.contributor.authorBailey, Rosemary Anne
dc.date.accessioned2013-04-15T14:01:04Z
dc.date.available2013-04-15T14:01:04Z
dc.date.issued2010-10
dc.identifier.citationBrien , C J & Bailey , R A 2010 , ' Decomposition tables for experiments. II. Two–one randomizations ' , Annals of Statistics , vol. 38 , no. 5 , pp. 3164-3190 . https://doi.org/10.1214/09-AOS785en
dc.identifier.issn0090-5364
dc.identifier.otherPURE: 49887485
dc.identifier.otherPURE UUID: 416d7305-624b-49bb-a235-b4e476da1091
dc.identifier.otherWOS: 000282402800018
dc.identifier.otherScopus: 77957575510
dc.identifier.otherORCID: /0000-0002-8990-2099/work/39600090
dc.identifier.urihttp://hdl.handle.net/10023/3479
dc.description.abstractWe investigate structure for pairs of randomizations that do not follow each other in a chain. These are unrandomized-inclusive, independent, coincident or double randomizations. This involves taking several structures that satisfy particular relations and combining them to form the appropriate orthogonal decomposition of the data space for the experiment. We show how to establish the decomposition table giving the sources of variation, their relationships and their degrees of freedom, so that competing designs can be evaluated. This leads to recommendations for when the different types of multiple randomization should be used.
dc.format.extent27
dc.language.isoeng
dc.relation.ispartofAnnals of Statisticsen
dc.rights© Institute of Mathematical Statistics, 2010. This is an open access articleen
dc.subjectAnalysis of varianceen
dc.subjectBalanceen
dc.subjectDecomposition tableen
dc.subjectDesign of experimentsen
dc.subjectEfficiency factoren
dc.subjectIntertier interactionen
dc.subjectMultiphase experimentsen
dc.subjectMultitiered experimentsen
dc.subjectOrthogonal decompositionen
dc.subjectPseudofactoren
dc.subjectStructureen
dc.subjectTieren
dc.subjectQA Mathematicsen
dc.subject.lccQAen
dc.titleDecomposition tables for experiments. II. Two–one randomizationsen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.Statisticsen
dc.contributor.institutionUniversity of St Andrews.Centre for Interdisciplinary Research in Computational Algebraen
dc.identifier.doihttps://doi.org/10.1214/09-AOS785
dc.description.statusPeer revieweden


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