Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/74450
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | - |
dc.creator | Fu, Q | - |
dc.creator | Guo, X | - |
dc.creator | Land, KC | - |
dc.date.accessioned | 2018-03-29T07:16:50Z | - |
dc.date.available | 2018-03-29T07:16:50Z | - |
dc.identifier.issn | 0361-0926 | - |
dc.identifier.uri | http://hdl.handle.net/10397/74450 | - |
dc.language.iso | en | en_US |
dc.publisher | Marcel Dekker | en_US |
dc.rights | © 2017 Taylor & Francis Group, LLC | en_US |
dc.rights | This 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.subject | Grouped and right-censored count data | en_US |
dc.subject | Mixed poisson models | en_US |
dc.subject | MLE-GRC | en_US |
dc.subject | Multinomial distribution | en_US |
dc.subject | Zero-inflated Poisson distribution | en_US |
dc.title | A Poisson-multinomial mixture approach to grouped and right-censored counts | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 427 | - |
dc.identifier.epage | 447 | - |
dc.identifier.volume | 47 | - |
dc.identifier.issue | 2 | - |
dc.identifier.doi | 10.1080/03610926.2017.1303736 | - |
dcterms.abstract | Although 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.accessRights | open access | - |
dcterms.bibliographicCitation | Communications in statistics. Theory and methods, 2018, v. 47, no. 2, p. 427-447 | - |
dcterms.isPartOf | Communications in statistics. Theory and methods | - |
dcterms.issued | 2018 | - |
dc.identifier.scopus | 2-s2.0-85029438618 | - |
dc.identifier.rosgroupid | 2017000054 | - |
dc.description.ros | 2017-2018 > Academic research: refereed > Publication in refereed journal | - |
dc.description.validate | 201802 bcrc | - |
dc.description.oa | Accepted Manuscript | - |
dc.identifier.FolderNumber | a0765-n04 | - |
dc.identifier.SubFormID | 1538 | - |
dc.description.fundingSource | Others | - |
dc.description.fundingText | 1-ZVEB | - |
dc.description.pubStatus | Published | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
a0765-n04_1538.pdf | Pre-Published version | 1.9 MB | Adobe PDF | View/Open |
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