Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74450
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Applied Mathematics-
dc.creatorFu, Q-
dc.creatorGuo, X-
dc.creatorLand, KC-
dc.date.accessioned2018-03-29T07:16:50Z-
dc.date.available2018-03-29T07:16:50Z-
dc.identifier.issn0361-0926-
dc.identifier.urihttp://hdl.handle.net/10397/74450-
dc.language.isoenen_US
dc.publisherMarcel Dekkeren_US
dc.rights© 2017 Taylor & Francis Group, LLCen_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Communications in Statistics - Theory and Methods on 13 Sep 2017 (Published online), available online: http://www.tandfonline.com/10.1080/03610926.2017.1303736.en_US
dc.subjectGrouped and right-censored count dataen_US
dc.subjectMixed poisson modelsen_US
dc.subjectMLE-GRCen_US
dc.subjectMultinomial distributionen_US
dc.subjectZero-inflated Poisson distributionen_US
dc.titleA Poisson-multinomial mixture approach to grouped and right-censored countsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage427-
dc.identifier.epage447-
dc.identifier.volume47-
dc.identifier.issue2-
dc.identifier.doi10.1080/03610926.2017.1303736-
dcterms.abstractAlthough count data are often collected in social, psychological, and epidemiological surveys in grouped and right-censored categories, there is a lack of statistical methods simultaneously taking both grouping and right-censoring into account. In this research, we propose a new generalized Poisson-multinomial mixture approach to model grouped and right-censored (GRC) count data. Based on a mixed Poisson-multinomial process for conceptualizing grouped and right-censored count data, we prove that the new maximum-likelihood estimator (MLE-GRC) is consistent and asymptotically normally distributed for both Poisson and zero-inflated Poisson models. The use of the MLE-GRC, implemented in an R function, is illustrated by both statistical simulation and empirical examples. This research provides a tool for epidemiologists to estimate incidence from grouped and right-censored count data and lays a foundation for regression analyses of such data structure.-
dcterms.accessRightsopen access-
dcterms.bibliographicCitationCommunications in statistics. Theory and methods, 2018, v. 47, no. 2, p. 427-447-
dcterms.isPartOfCommunications in statistics. Theory and methods-
dcterms.issued2018-
dc.identifier.scopus2-s2.0-85029438618-
dc.identifier.rosgroupid2017000054-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201802 bcrc-
dc.description.oaAccepted Manuscript-
dc.identifier.FolderNumbera0765-n04-
dc.identifier.SubFormID1538-
dc.description.fundingSourceOthers-
dc.description.fundingText1-ZVEB-
dc.description.pubStatusPublished-
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
a0765-n04_1538.pdfPre-Published version1.9 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

185
Last Week
3
Last month
Citations as of Oct 13, 2024

Downloads

127
Citations as of Oct 13, 2024

SCOPUSTM   
Citations

10
Last Week
0
Last month
Citations as of Oct 10, 2024

WEB OF SCIENCETM
Citations

9
Last Week
0
Last month
Citations as of Oct 10, 2024

Google ScholarTM

Check

Altmetric


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