Beta-binomial/gamma-poisson regression models for repeated counts with random parameters

Bibliographic Details
Main Author: Lora, Mayra Ivanoff
Publication Date: 2011
Other Authors: Singer, Julio M.
Language: eng
Source: Repositório Institucional do FGV (FGV Repositório Digital)
DOI: 10.1214/10-BJPS118
Download full: http://hdl.handle.net/10438/23234
http://dx.doi.org/10.1214/10-BJPS118
Summary: Beta-binomial/Poisson models have been used by many authors to model multivariate count data. Lora and Singer [Stat. Med. 27 (2008) 3366-3381] extended such models to accommodate repeated multivariate count data with overdipersion in the binomial component. To overcome some of the limitations of that model, we consider a beta-binomial/gamma-Poisson alternative that also allows for both overdispersion and different covariances between the Poisson counts. We obtain maximum likelihood estimates for the parameters using a Newton-Raphson algorithm and compare both models in a practical example.
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spelling Lora, Mayra IvanoffSinger, Julio M.FGV2018-05-10T13:36:05Z2018-05-10T13:36:05Z2011-070013-0133 / 1468-0297http://hdl.handle.net/10438/23234http://dx.doi.org/10.1214/10-BJPS11810.1214/10-BJPS118000296130000006Singer, Julio/0000-0001-6515-9643Singer, Julio/C-1232-2013Beta-binomial/Poisson models have been used by many authors to model multivariate count data. Lora and Singer [Stat. Med. 27 (2008) 3366-3381] extended such models to accommodate repeated multivariate count data with overdipersion in the binomial component. To overcome some of the limitations of that model, we consider a beta-binomial/gamma-Poisson alternative that also allows for both overdispersion and different covariances between the Poisson counts. We obtain maximum likelihood estimates for the parameters using a Newton-Raphson algorithm and compare both models in a practical example.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq); Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazilp. 218-235engBrazilian Statistical AssociationBrazilian journal of probability and statisticsWeb of Sciencereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVBivariate countsLongitudinal dataOverdispersionRandom effectsRegression modelsTrialsNumberMatemáticaDistribuição binomialMatrizes randômicasBeta-binomial/gamma-poisson regression models for repeated counts with random parametersArticle (Journal/Review)info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessTEXT000296130000006.pdf.txt000296130000006.pdf.txtExtracted texttext/plain40012https://repositorio.fgv.br/bitstreams/938faa75-e286-4aef-bdcf-6b196048ed79/downloadf17caf43d385f97edc73ec5adb98c639MD56ORIGINAL000296130000006.pdf000296130000006.pdfapplication/pdf143884https://repositorio.fgv.br/bitstreams/8da6be55-e6b2-4cd7-9865-9f90929ef39b/downloadadd5dfba07115bed0d882fbb274167daMD51THUMBNAIL000296130000006.pdf.jpg000296130000006.pdf.jpgGenerated Thumbnailimage/jpeg4760https://repositorio.fgv.br/bitstreams/0f8e25e1-27e6-4c9b-9d65-be8dfa237485/downloadae7a00e9875e938ce1e24950d03a6500MD5710438/232342023-11-07 22:19:13.636open.accessoai:repositorio.fgv.br:10438/23234https://repositorio.fgv.brRepositório InstitucionalPRIhttp://bibliotecadigital.fgv.br/dspace-oai/requestopendoar:39742023-11-07T22:19:13Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)false
dc.title.eng.fl_str_mv Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
title Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
spellingShingle Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
Lora, Mayra Ivanoff
Bivariate counts
Longitudinal data
Overdispersion
Random effects
Regression models
Trials
Number
Matemática
Distribuição binomial
Matrizes randômicas
title_short Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
title_full Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
title_fullStr Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
title_full_unstemmed Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
title_sort Beta-binomial/gamma-poisson regression models for repeated counts with random parameters
author Lora, Mayra Ivanoff
author_facet Lora, Mayra Ivanoff
Singer, Julio M.
author_role author
author2 Singer, Julio M.
author2_role author
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.author.fl_str_mv Lora, Mayra Ivanoff
Singer, Julio M.
dc.subject.eng.fl_str_mv Bivariate counts
Longitudinal data
Overdispersion
Random effects
Regression models
Trials
Number
topic Bivariate counts
Longitudinal data
Overdispersion
Random effects
Regression models
Trials
Number
Matemática
Distribuição binomial
Matrizes randômicas
dc.subject.area.por.fl_str_mv Matemática
dc.subject.bibliodata.por.fl_str_mv Distribuição binomial
Matrizes randômicas
description Beta-binomial/Poisson models have been used by many authors to model multivariate count data. Lora and Singer [Stat. Med. 27 (2008) 3366-3381] extended such models to accommodate repeated multivariate count data with overdipersion in the binomial component. To overcome some of the limitations of that model, we consider a beta-binomial/gamma-Poisson alternative that also allows for both overdispersion and different covariances between the Poisson counts. We obtain maximum likelihood estimates for the parameters using a Newton-Raphson algorithm and compare both models in a practical example.
publishDate 2011
dc.date.issued.fl_str_mv 2011-07
dc.date.accessioned.fl_str_mv 2018-05-10T13:36:05Z
dc.date.available.fl_str_mv 2018-05-10T13:36:05Z
dc.type.driver.fl_str_mv Article (Journal/Review)
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/23234
http://dx.doi.org/10.1214/10-BJPS118
dc.identifier.issn.none.fl_str_mv 0013-0133 / 1468-0297
dc.identifier.doi.none.fl_str_mv 10.1214/10-BJPS118
dc.identifier.WoS.none.fl_str_mv 000296130000006
dc.identifier.orcid.none.fl_str_mv Singer, Julio/0000-0001-6515-9643
dc.identifier.researcherid.none.fl_str_mv Singer, Julio/C-1232-2013
identifier_str_mv 0013-0133 / 1468-0297
10.1214/10-BJPS118
000296130000006
Singer, Julio/0000-0001-6515-9643
Singer, Julio/C-1232-2013
url http://hdl.handle.net/10438/23234
http://dx.doi.org/10.1214/10-BJPS118
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.eng.fl_str_mv Brazilian journal of probability and statistics
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv p. 218-235
dc.publisher.none.fl_str_mv Brazilian Statistical Association
publisher.none.fl_str_mv Brazilian Statistical Association
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional do FGV (FGV Repositório Digital)
instname:Fundação Getulio Vargas (FGV)
instacron:FGV
instname_str Fundação Getulio Vargas (FGV)
instacron_str FGV
institution FGV
reponame_str Repositório Institucional do FGV (FGV Repositório Digital)
collection Repositório Institucional do FGV (FGV Repositório Digital)
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