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Nested row-column designs for near-factorial experiments with two treatment factors and one control treatment

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dc.contributor.authorBailey, Rosemary Anne
dc.contributor.authorLacka, Agnieszka
dc.date.accessioned2015-04-23T14:31:02Z
dc.date.available2015-04-23T14:31:02Z
dc.date.issued2015-10
dc.identifier179649696
dc.identifierba091a94-3ead-4918-86ee-e7d92ca6984d
dc.identifier84929944800
dc.identifier000356749000006
dc.identifier.citationBailey , R A & Lacka , A 2015 , ' Nested row-column designs for near-factorial experiments with two treatment factors and one control treatment ' , Journal of Statistical Planning and Inference , vol. 165 , pp. 63-77 . https://doi.org/10.1016/j.jspi.2015.04.003en
dc.identifier.issn0378-3758
dc.identifier.otherORCID: /0000-0002-8990-2099/work/39600098
dc.identifier.urihttps://hdl.handle.net/10023/6556
dc.descriptionThe authors also thank Queen Mary, University of London, the University of St Andrews and the Poznan University of Life Sciences for financial support. The second author was also supported by the British-Polish Young Scientists Programme, grant WAR/342/116.en
dc.description.abstractThis paper presents some methods of designing experiments in a block design with nested rows and columns. The treatments consist of all combinations of levels of two treatment factors, with an additional control treatment.
dc.format.extent15
dc.format.extent244897
dc.language.isoeng
dc.relation.ispartofJournal of Statistical Planning and Inferenceen
dc.subjectBlock designs with nested rows and columnsen
dc.subjectControl treatmenten
dc.subjectMixed modelsen
dc.subjectNear-factorial experimenten
dc.subjectSupplemented balanceen
dc.subjectSupplemented partial balanceen
dc.subjectQA Mathematicsen
dc.subjectQH301 Biologyen
dc.subjectT-NDASen
dc.subject.lccQAen
dc.subject.lccQH301en
dc.titleNested row-column designs for near-factorial experiments with two treatment factors and one control treatmenten
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Interdisciplinary Research in Computational Algebraen
dc.identifier.doi10.1016/j.jspi.2015.04.003
dc.description.statusPeer revieweden


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