Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/10912
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dc.contributor.authorBRUCKERS, Liesbeth-
dc.contributor.authorSERROYEN, Jan-
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorSlaets, Herman-
dc.contributor.authorGoeyvaerts, Willem-
dc.date.accessioned2010-05-18T11:24:26Z-
dc.date.availableNO_RESTRICTION-
dc.date.available2010-05-18T11:24:26Z-
dc.date.issued2010-
dc.identifier.citationJOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 59. p. 495-512-
dc.identifier.issn0035-9254-
dc.identifier.urihttp://hdl.handle.net/1942/10912-
dc.description.abstractPersistent disturbing behaviour refers to a chronic condition in highly unstable, therapy resistant psychiatric patients. Because these patients are difficult to maintain in their natural living environment and even in hospital wards, purposely designed residential psychiatric facilities need to be established. Therefore, it is important to define and circumscribe the group carefully. Serroyen and co-workers, starting from the longitudinal analysis of a score based on data from the Belgian national psychiatric registry, undertook a discriminant analysis to distinguish persistent disturbing behaviour patients from a control group. They also indicated that there is scope for further subdividing the persistent disturbing behaviour patients into two subgroups, using conventional cluster analysis techniques. We employ a variety of novel longitudinal-data-based cluster analysis techniques. These are based on either conventional growth models, growth-mixture models or latent class growth models. Unlike in earlier analyses, where some evidence for two groups was found, there now is an indication of three groups, which is a finding with high practical and organizational relevance.-
dc.description.sponsorshipThe authors gratefully acknowledge financial support from the Interuniversity Attraction Pole research network P6/03 of the Belgian Government (Belgian Science Policy).-
dc.language.isoen-
dc.publisherWILEY-BLACKWELL PUBLISHING, INC-
dc.subject.othergrowth curves; growth mixture models; latent class growth models; linear mixed models-
dc.subject.otherGrowth curves; Growth mixture models; Latent class growth models; Linear mixed models-
dc.titleLatent class analysis of persistent disturbing behaviour patients by using longitudinal profiles-
dc.typeJournal Contribution-
dc.identifier.epage512-
dc.identifier.spage495-
dc.identifier.volume59-
local.format.pages18-
local.bibliographicCitation.jcatA1-
dc.description.notes[Bruckers, Liesbeth] Hasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium. liesbeth.bruckers@uhasselt.be-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1111/j.1467-9876.2009.00704.x-
dc.identifier.isi000276500600007-
item.fullcitationBRUCKERS, Liesbeth; SERROYEN, Jan; MOLENBERGHS, Geert; Slaets, Herman & Goeyvaerts, Willem (2010) Latent class analysis of persistent disturbing behaviour patients by using longitudinal profiles. In: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 59. p. 495-512.-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.validationecoom 2011-
item.contributorGoeyvaerts, Willem-
item.contributorBRUCKERS, Liesbeth-
item.contributorSERROYEN, Jan-
item.contributorMOLENBERGHS, Geert-
item.contributorSlaets, Herman-
crisitem.journal.issn0035-9254-
crisitem.journal.eissn1467-9876-
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