A Network approach to deal with the problem of examinee choice under item response theory

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Carolina Silva Pena
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Teoria da resposta do item
PERT (Análise de redes)
Teoria bayesiana de decisão estatistica
Engenharia de produção
Análise de Redes
Seleção de itens
Medidas de Centralidade
Teoria de
Resposta ao Item
Modelagem Bayesiana
Link de acesso: https://hdl.handle.net/1843/BUBD-AHSKQF
Resumo: In a typical questionnaire testing situation, the examinees are not allowed to choose which items they would rather answer. The main reason is a technical issue in obtaining satisfactory statistical estimates of examinees' abilities and items' difficulties. This paper introduces a new Item Response Theory (IRT) model that incorporates information from a novel representation of the questionnaire data, using network analysis. The questionnaire data set is coded as layers, the items are coded as nodes and the selected items are connected by edges. The new proposed Item Response Theory (IRT) model incorporates networkinformation using Bayesian estimation. Several simulation studies in which examinees are allowed to select a subset of items were performed. Results show substantial improvements in the parameters' recovery over the standard model. To the best of our knowledge, this is the first proposal to obtaining satisfactory IRT statistical estimates in some critical scenarios reported in literature.
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spelling A Network approach to deal with the problem of examinee choice under item response theoryTeoria da resposta do itemPERT (Análise de redes)Teoria bayesiana de decisão estatisticaEngenharia de produçãoAnálise de RedesSeleção de itensMedidas de CentralidadeTeoria deResposta ao ItemModelagem BayesianaIn a typical questionnaire testing situation, the examinees are not allowed to choose which items they would rather answer. The main reason is a technical issue in obtaining satisfactory statistical estimates of examinees' abilities and items' difficulties. This paper introduces a new Item Response Theory (IRT) model that incorporates information from a novel representation of the questionnaire data, using network analysis. The questionnaire data set is coded as layers, the items are coded as nodes and the selected items are connected by edges. The new proposed Item Response Theory (IRT) model incorporates networkinformation using Bayesian estimation. Several simulation studies in which examinees are allowed to select a subset of items were performed. Results show substantial improvements in the parameters' recovery over the standard model. To the best of our knowledge, this is the first proposal to obtaining satisfactory IRT statistical estimates in some critical scenarios reported in literature.Universidade Federal de Minas Gerais2019-08-13T09:24:52Z2025-09-09T00:49:39Z2019-08-13T09:24:52Z2016-12-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://hdl.handle.net/1843/BUBD-AHSKQFCarolina Silva Penainfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2025-09-09T00:49:39Zoai:repositorio.ufmg.br:1843/BUBD-AHSKQFRepositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2025-09-09T00:49:39Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv A Network approach to deal with the problem of examinee choice under item response theory
title A Network approach to deal with the problem of examinee choice under item response theory
spellingShingle A Network approach to deal with the problem of examinee choice under item response theory
Carolina Silva Pena
Teoria da resposta do item
PERT (Análise de redes)
Teoria bayesiana de decisão estatistica
Engenharia de produção
Análise de Redes
Seleção de itens
Medidas de Centralidade
Teoria de
Resposta ao Item
Modelagem Bayesiana
title_short A Network approach to deal with the problem of examinee choice under item response theory
title_full A Network approach to deal with the problem of examinee choice under item response theory
title_fullStr A Network approach to deal with the problem of examinee choice under item response theory
title_full_unstemmed A Network approach to deal with the problem of examinee choice under item response theory
title_sort A Network approach to deal with the problem of examinee choice under item response theory
author Carolina Silva Pena
author_facet Carolina Silva Pena
author_role author
dc.contributor.author.fl_str_mv Carolina Silva Pena
dc.subject.por.fl_str_mv Teoria da resposta do item
PERT (Análise de redes)
Teoria bayesiana de decisão estatistica
Engenharia de produção
Análise de Redes
Seleção de itens
Medidas de Centralidade
Teoria de
Resposta ao Item
Modelagem Bayesiana
topic Teoria da resposta do item
PERT (Análise de redes)
Teoria bayesiana de decisão estatistica
Engenharia de produção
Análise de Redes
Seleção de itens
Medidas de Centralidade
Teoria de
Resposta ao Item
Modelagem Bayesiana
description In a typical questionnaire testing situation, the examinees are not allowed to choose which items they would rather answer. The main reason is a technical issue in obtaining satisfactory statistical estimates of examinees' abilities and items' difficulties. This paper introduces a new Item Response Theory (IRT) model that incorporates information from a novel representation of the questionnaire data, using network analysis. The questionnaire data set is coded as layers, the items are coded as nodes and the selected items are connected by edges. The new proposed Item Response Theory (IRT) model incorporates networkinformation using Bayesian estimation. Several simulation studies in which examinees are allowed to select a subset of items were performed. Results show substantial improvements in the parameters' recovery over the standard model. To the best of our knowledge, this is the first proposal to obtaining satisfactory IRT statistical estimates in some critical scenarios reported in literature.
publishDate 2016
dc.date.none.fl_str_mv 2016-12-06
2019-08-13T09:24:52Z
2019-08-13T09:24:52Z
2025-09-09T00:49:39Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1843/BUBD-AHSKQF
url https://hdl.handle.net/1843/BUBD-AHSKQF
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv repositorio@ufmg.br
_version_ 1856414112430424064

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