Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21028
Full metadata record
DC FieldValueLanguage
dc.contributor.authorHERMANS, Lisa-
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorKenward, M.G.-
dc.contributor.authorVAN DER ELST, Wim-
dc.contributor.authorNassiri, Vahid-
dc.contributor.authorAERTS, Marc-
dc.contributor.authorVERBEKE, Geert-
dc.date.accessioned2016-04-19T14:24:18Z-
dc.date.available2016-04-19T14:24:18Z-
dc.date.issued2015-
dc.identifier.citationFriedl, Herwig; Wagner, Helga (Ed.). Proceedings of the 30th International Workshop on Statistical Modelling, p. 215-220-
dc.identifier.urihttp://hdl.handle.net/1942/21028-
dc.description.abstractThere are many contemporary designs that do not use a random sample of a fixed, a priori determined size. In case of informative cluster sizes, the cluster size is influenced by the the cluster’s data, but here we cope with some issues that even occur when the cluster size and the data are unrelated. First, fitting models to clusters of varying sizes is often more complicated than when all cluster have the same size. Secondly, in such cases, there usually is no so-called complete sufficient statistic (Molenberghs et al., 2014).-
dc.description.sponsorshipGeert Molenberghs, Mike Kenward, Marc Aerts, Geert Verbeke and Wim van der Elst gratefully acknowledge support from IAP research Network P7/06 of the Belgian Government (Belgian Science Policy) and Geert Molenberghs and Geert Verbeke from ExaScience Project.-
dc.language.isoen-
dc.rightsThis paper was published as a part of the proceedings of the 30th International Workshop on Statistical Modelling, Johannes Kepler Universit¨at Linz, 6–10 July 2015. The copyright remains with the author(s). Permission to reproduce or extract any parts of this abstract should be requested from the author(s).-
dc.subject.otherlikelihood inference; pseudo-likelihood; random cluster size-
dc.titleClusters with random size: maximum likelihood versus weighted estimation-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsFriedl, Herwig-
local.bibliographicCitation.authorsWagner, Helga-
local.bibliographicCitation.conferencedate06-10/07/2015-
local.bibliographicCitation.conferencenameThe 30th International Workshop on Statistical Modelling (IWSM)-
local.bibliographicCitation.conferenceplaceJohannes Kepler University, Linz, Austria-
dc.identifier.epage220-
dc.identifier.spage215-
local.bibliographicCitation.jcatC2-
dc.description.notesE-mail for correspondence: lisa.hermans@uhasselt.be-
local.type.refereedRefereed-
local.type.specifiedAbstract-
local.bibliographicCitation.btitleProceedings of the 30th International Workshop on Statistical Modelling-
item.fulltextWith Fulltext-
item.fullcitationHERMANS, Lisa; MOLENBERGHS, Geert; Kenward, M.G.; VAN DER ELST, Wim; Nassiri, Vahid; AERTS, Marc & VERBEKE, Geert (2015) Clusters with random size: maximum likelihood versus weighted estimation. In: Friedl, Herwig; Wagner, Helga (Ed.). Proceedings of the 30th International Workshop on Statistical Modelling, p. 215-220.-
item.accessRightsOpen Access-
item.contributorHERMANS, Lisa-
item.contributorMOLENBERGHS, Geert-
item.contributorKenward, M.G.-
item.contributorVAN DER ELST, Wim-
item.contributorNassiri, Vahid-
item.contributorAERTS, Marc-
item.contributorVERBEKE, Geert-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
IWSM-2015-Proceedings-Vol1.215-220.pdf458.65 kBAdobe PDFView/Open
Show simple item record

Page view(s)

66
checked on Jun 21, 2022

Download(s)

96
checked on Jun 21, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.