Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..

In this project, we propose to extend and spread the Multidimensional Item Response Theory (MIRT) models, by introducing and developing new models, based on some of those developed for the unidimensional case. Furthermore, we will study the problem where one item could be measuring more than one con...

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Autores:
Tipo de recurso:
Fecha de publicación:
2017
Institución:
Ministerio de Ciencia Tecnología e Innovación
Repositorio:
Repositorio Institucional de Minciencias
Idioma:
spa
OAI Identifier:
oai:repositorio.minciencias.gov.co:20.500.14143/37867
Acceso en línea:
https://colciencias.metadirectorio.org/handle/11146/37867
http://colciencias.metabiblioteca.com.co
Palabra clave:
MIRT models
Differential functioning
Latent regression
Multiple constructs
Latent models
Rights
openAccess
License
http://purl.org/coar/access_right/c_abf2
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spelling Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..MIRT modelsDifferential functioningLatent regressionMultiple constructsLatent modelsIn this project, we propose to extend and spread the Multidimensional Item Response Theory (MIRT) models, by introducing and developing new models, based on some of those developed for the unidimensional case. Furthermore, we will study the problem where one item could be measuring more than one construct. The project has been designed to attack several problems existing when a large test is thought to measure more than one construct, and it is applied to a big population. Examples of such tests are those applied by Unversidad Nacional and ICFES. Specifically, we propose the development of MIRT models for including random effects in the item parameters for modeling the differential functioning of the items in the presence of several populations; the modeling of longitudinal data in the case of multidimensional data in tests that are repeated in the time and the introduction of latent regressions for explaining the responses of multidimensional tests by means of explanatory variables based on available socio-demographic information of the responders. Additionally, we propose the introduction of some statistical descriptive tools for detecting the dimensionality of the latent traits and for confirmatory analysis. We propose not only the theoretically development of the models, but also, their implementation in a package for the R statistical system.Universidad Nacional de Colombia (Bogotá, Colombia)COL0001736 - CT&S - UNCOL0033739 - INFERENCIA BAYESIANAMontenegro Díaz, Alvaro Mauricio2020-02-26T15:12:29Z2020-12-17T21:57:43Z2020-02-26T15:12:29Z2020-12-17T21:57:43Z2017-06-28Informe de investigaciónhttp://purl.org/coar/resource_type/c_18wsTextinfo:eu-repo/semantics/reporthttps://purl.org/redcol/resource_type/PIDinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/version/c_71e4c1898caa6e32info:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_93fc36 páginas.application/pdfhttps://colciencias.metadirectorio.org/handle/11146/37867ColcienciasRepositorio Colcienciashttp://colciencias.metabiblioteca.com.cospaInforme;2013-2017info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by/4.0/oai:repositorio.minciencias.gov.co:20.500.14143/378672023-11-29T17:31:15Z
dc.title.none.fl_str_mv Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
title Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
spellingShingle Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
MIRT models
Differential functioning
Latent regression
Multiple constructs
Latent models
title_short Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
title_full Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
title_fullStr Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
title_full_unstemmed Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
title_sort Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..
dc.contributor.none.fl_str_mv Universidad Nacional de Colombia (Bogotá, Colombia)
COL0001736 - CT&S - UN
COL0033739 - INFERENCIA BAYESIANA
dc.subject.none.fl_str_mv MIRT models
Differential functioning
Latent regression
Multiple constructs
Latent models
topic MIRT models
Differential functioning
Latent regression
Multiple constructs
Latent models
description In this project, we propose to extend and spread the Multidimensional Item Response Theory (MIRT) models, by introducing and developing new models, based on some of those developed for the unidimensional case. Furthermore, we will study the problem where one item could be measuring more than one construct. The project has been designed to attack several problems existing when a large test is thought to measure more than one construct, and it is applied to a big population. Examples of such tests are those applied by Unversidad Nacional and ICFES. Specifically, we propose the development of MIRT models for including random effects in the item parameters for modeling the differential functioning of the items in the presence of several populations; the modeling of longitudinal data in the case of multidimensional data in tests that are repeated in the time and the introduction of latent regressions for explaining the responses of multidimensional tests by means of explanatory variables based on available socio-demographic information of the responders. Additionally, we propose the introduction of some statistical descriptive tools for detecting the dimensionality of the latent traits and for confirmatory analysis. We propose not only the theoretically development of the models, but also, their implementation in a package for the R statistical system.
publishDate 2017
dc.date.none.fl_str_mv 2017-06-28
2020-02-26T15:12:29Z
2020-12-17T21:57:43Z
2020-02-26T15:12:29Z
2020-12-17T21:57:43Z
dc.type.none.fl_str_mv Informe de investigación
http://purl.org/coar/resource_type/c_18ws
Text
info:eu-repo/semantics/report
https://purl.org/redcol/resource_type/PID
info:eu-repo/semantics/submittedVersion
http://purl.org/coar/version/c_71e4c1898caa6e32
info:eu-repo/semantics/submittedVersion
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_93fc
status_str submittedVersion
dc.identifier.none.fl_str_mv https://colciencias.metadirectorio.org/handle/11146/37867
Colciencias
Repositorio Colciencias
http://colciencias.metabiblioteca.com.co
url https://colciencias.metadirectorio.org/handle/11146/37867
http://colciencias.metabiblioteca.com.co
identifier_str_mv Colciencias
Repositorio Colciencias
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv Informe;
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv 36 páginas.
application/pdf
dc.coverage.none.fl_str_mv 2013-2017
institution Ministerio de Ciencia Tecnología e Innovación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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