Clustering Ordinal Data via Latent Variable Models

DC FieldValueLanguage
dc.contributor.authorMcParland, Damien
dc.contributor.authorGormley, Isobel Claire
dc.date.accessioned2013-04-25T13:59:27Z
dc.date.available2013-04-25T13:59:27Z
dc.date.copyright2013, Springer International Publishing Switzerland
dc.date.issued2011-08
dc.identifier.isbn978-3-319-00034-3
dc.identifier.urihttp://hdl.handle.net/10197/4284
dc.descriptionIFCS 2011 Symposium of the International Federation of Classification Societies (IFCS), August 30, 2011, Frankfurten
dc.description.abstractItem response modelling is a well established method for analysing ordinal response data. Ordinal data are typically collected as responses to a number of questions or items. The observed data can be viewed as discrete versions of an underlying latent Gaussian variable. Item response models assume that this latent variable (and therefore the observed ordinal response) is a function of both respondent specific and item specific parameters. However, item response models assume a homogeneous population in that the item specific parameters are assumed to be the same for all respondents. Often a population is heterogeneous and clusters of respondents exist; members of different clusters may view the items differently. A mixture of item response models is developed to provide clustering capabilities in the context of ordinal response data. The model is estimated within the Bayesian paradigm and is illustrated through an application to an ordinal response data set resulting from a clinical trial involving self-assessment of arthritis.en
dc.language.isoenen
dc.publisherSpringer
dc.relation.ispartofBerthold Lausen, Dirk Van den Poel, Alfred Ultsch (eds.). Algorithms from and for Nature and Life : Classification and Data Analysis
dc.rightsThe final publication is available at www.springerlink.com
dc.subjectStatistics and Computing/Statistics Programs
dc.subjectComputer Applications in Social and Behavioral Sciences
dc.titleClustering Ordinal Data via Latent Variable Modelsen
dc.typeConference Publicationen
dc.internal.authorcontactotherdamien.mcparland@ucd.ie
dc.internal.availabilityFull text availableen
dc.statusPeer revieweden
dc.identifier.doi10.1007/978-3-319-00035-0_12-
dc.neeo.contributorMcParland|Damien|aut|-
dc.neeo.contributorGormley|Isobel Claire|aut|-
dc.description.othersponsorshipScience Foundation Irelanden
dc.description.adminAuthor's name is listed as "ISOBEL Claire Gormley" on the actual paper. ASen
dc.internal.rmsid306919362
dc.date.updated2013-04-19T16:10:45Z
item.grantfulltextopen-
item.fulltextWith Fulltext-
Appears in Collections:Mathematics and Statistics Research Collection
Files in This Item:
File Description SizeFormat 
McParlandGormley_CameraReadyVersion.pdf171.69 kBAdobe PDFDownload
Show simple item record

SCOPUSTM   
Citations 50

4
Last Week
0
Last month
checked on Jun 22, 2018

Page view(s) 20

159
checked on May 25, 2018

Download(s) 20

260
checked on May 25, 2018

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.