Bootstrapping data with multiple levels of variation

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dc.contributor.authorField, Chris
dc.contributor.authorPang, Zhen
dc.contributor.authorWelsh, Alan
dc.date.accessioned2015-12-07T22:51:07Z
dc.date.issued2008
dc.date.updated2016-02-24T11:06:29Z
dc.description.abstractThe authors consider general estimators for the mean and variance parameters in the random effect model and in the transformation model for data with multiple levels of variation. They show that these estimators have different distributions under the two
dc.identifier.issn0319-5724
dc.identifier.urihttp://hdl.handle.net/1885/27309
dc.publisherStatistical Society of Canada
dc.sourceCanadian Journal of Statistics
dc.subjectBest linear unbiased prediction hierarchical
dc.subjectData
dc.subjectMixed model
dc.subjectQuasi-likelihood estimation
dc.subjectRandom effect
dc.subjectUnbalanced data
dc.titleBootstrapping data with multiple levels of variation
dc.typeJournal article
local.bibliographicCitation.lastpage539
local.bibliographicCitation.startpage521
local.contributor.affiliationField, Chris, Dalhousie University
local.contributor.affiliationPang, Zhen, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationWelsh, Alan, College of Physical and Mathematical Sciences, ANU
local.contributor.authoruidPang, Zhen, u4300909
local.contributor.authoruidWelsh, Alan, u8204947
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor010405 - Statistical Theory
local.identifier.ariespublicationu4379881xPUB50
local.identifier.citationvolume36
local.identifier.scopusID2-s2.0-59149102920
local.identifier.thomsonID000267403600003
local.type.statusPublished Version

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