Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/13048
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dc.contributor.authorMurison, Robert Den
dc.contributor.authorScott, Jim Men
dc.date.accessioned2013-07-19T14:49:00Z-
dc.date.issued2013-
dc.identifier.citationAnimal Production Science, 53(7-8), p. 643-648en
dc.identifier.issn1836-5787en
dc.identifier.issn1836-0939en
dc.identifier.urihttps://hdl.handle.net/1959.11/13048-
dc.description.abstractThe present paper explains the statistical inference that can be drawn from an unreplicated field experiment that investigated three different pasture and grazing management strategies. The experiment was intended to assess these three strategies as whole farmlet systems where scale of the experiment precluded replication. The experiment was planned so that farmlets were allocated to matched paddocks on the basis of background variables that were measured across each paddock before the start of the experiment. These conditioning variables were used in the statistical model so that farmlet effects could be discerned from the longitudinal profiles of the responses. The purpose is to explain the principles by which longitudinal data collected from the experiment were interpreted. Two datasets, including (1) botanical composition and (2) hogget liveweights, are used in the present paper as examples. Inferences from the experiment are guarded because we acknowledge that the use of conditioning variables and matched paddocks does not provide the same power as replication. We, nevertheless, conclude that the differences observed are more likely to have been due to treatment effects than to random variation or bias.en
dc.languageenen
dc.publisherCSIRO Publishingen
dc.relation.ispartofAnimal Production Scienceen
dc.titleStatistical methodologies for drawing causal inference from an unreplicated farmlet experiment conducted by the Cicerone Projecten
dc.typeJournal Articleen
dc.identifier.doi10.1071/AN11331en
dcterms.accessRightsGolden
dc.subject.keywordsApplied Statisticsen
local.contributor.firstnameRobert Den
local.contributor.firstnameJim Men
local.subject.for2008010401 Applied Statisticsen
local.subject.seo2008830311 Sheep - Woolen
local.subject.seo2008830406 Sown Pastures (excl. Lucerne)en
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailrmurison@une.edu.auen
local.profile.emailjscott@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20121127-121039en
local.publisher.placeAustraliaen
local.format.startpage643en
local.format.endpage648en
local.identifier.scopusid84884539964en
local.peerreviewedYesen
local.identifier.volume53en
local.identifier.issue7-8en
local.access.fulltextYesen
local.contributor.lastnameMurisonen
local.contributor.lastnameScotten
dc.identifier.staffune-id:rmurisonen
dc.identifier.staffune-id:jscotten
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:13257en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleStatistical methodologies for drawing causal inference from an unreplicated farmlet experiment conducted by the Cicerone Projecten
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorMurison, Robert Den
local.search.authorScott, Jim Men
local.uneassociationUnknownen
local.year.published2013en
local.subject.for2020490501 Applied statisticsen
local.subject.seo2020100413 Sheep for woolen
local.subject.seo2020100505 Sown pastures (excl. lucerne)en
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