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...

Full description

Autores:
Montenegro Díaz, Alvaro Mauricio
Tipo de recurso:
Investigation report
Fecha de publicación:
2017
Institución:
Ministerio de Ciencia, Tecnología e Innovación
Repositorio:
Repositorio 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 Montenegro Díaz, Alvaro Mauricio2e7596b37d6b67cc52900295220ef51b-1Universidad Nacional de Colombia (Bogotá, Colombia)COL0001736 - CT&S - UNCOL0033739 - INFERENCIA BAYESIANA2020-02-26T15:12:29Z2020-12-17T21:57:43Z2020-02-26T15:12:29Z2020-12-17T21:57:43Z2017-06-28https://colciencias.metadirectorio.org/handle/11146/37867ColcienciasRepositorio Colcienciashttp://colciencias.metabiblioteca.com.coIn 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.36 páginas.spaInforme;Multidimensional Item Response Theory models for practical application in large tests designed to measure multiple constructs..Informe de investigaciónhttp://purl.org/coar/resource_type/c_18wshttp://purl.org/coar/resource_type/c_93fcTextinfo:eu-repo/semantics/reporthttps://purl.org/redcol/resource_type/PIDinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/version/c_71e4c1898caa6e32info:eu-repo/semantics/submittedVersion2013-2017info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by/4.0/MIRT modelsDifferential functioningLatent regressionMultiple constructsLatent modelsEstudiantes, Profesores, Comunidad científica colombiana, etc.110156933802Departamento Administrativo de Ciencia, Tecnología e Innovación [CO] ColcienciasPrograma Nacional en Ciencias BásicasExtending and spread the use of the MIRT models in large test apply by big institutions like ICFES and Universidad Nacional in Colombia.PublicationORIGINAL110156933802.pdf110156933802.pdfInforme finalapplication/pdf10424307https://repositorio.minciencias.gov.co/bitstreams/20f6d6ef-200f-406f-af8b-27c2660a6519/download647d1f50393687eae26d73fd13f35ac7MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814800https://repositorio.minciencias.gov.co/bitstreams/6860ace8-253c-46a4-8ce1-4b7ba7e3b137/download8ffe28672ea88fddc177fe365a489039MD52license.txtlicense.txttext/plain; charset=utf-80https://repositorio.minciencias.gov.co/bitstreams/78cba307-1c3f-46a2-9ebe-da41444f5c17/downloadd41d8cd98f00b204e9800998ecf8427eMD55TEXT110156933802.pdf.txt110156933802.pdf.txtExtracted texttext/plain36https://repositorio.minciencias.gov.co/bitstreams/4a1f8720-4870-4760-82ed-37bc9eaf3bce/download359c989e7470416468f7ad84d3dda8c9MD53THUMBNAIL110156933802.pdf.jpg110156933802.pdf.jpgGenerated Thumbnailimage/jpeg8731https://repositorio.minciencias.gov.co/bitstreams/20cbc1d5-fed1-48d0-a4e2-efa54880b7b8/download0b7a50549f593f3f7b1764d85a2c39aeMD5420.500.14143/37867oai:repositorio.minciencias.gov.co:20.500.14143/378672023-11-29 17:31:15.033restrictedhttps://repositorio.minciencias.gov.coRepositorio Institucional de Mincienciascendoc@minciencias.gov.co
dc.title.spa.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.creator.fl_str_mv Montenegro Díaz, Alvaro Mauricio
dc.contributor.author.none.fl_str_mv Montenegro Díaz, Alvaro Mauricio
dc.contributor.corporatename.spa.fl_str_mv Universidad Nacional de Colombia (Bogotá, Colombia)
dc.contributor.researchgroup.none.fl_str_mv COL0001736 - CT&S - UN
COL0033739 - INFERENCIA BAYESIANA
dc.subject.proposal.spa.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.issued.none.fl_str_mv 2017-06-28
dc.date.accessioned.none.fl_str_mv 2020-02-26T15:12:29Z
2020-12-17T21:57:43Z
dc.date.available.none.fl_str_mv 2020-02-26T15:12:29Z
2020-12-17T21:57:43Z
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https://creativecommons.org/licenses/by/4.0/
dc.format.extent.spa.fl_str_mv 36 páginas.
dc.coverage.projectdates.spa.fl_str_mv 2013-2017
institution Ministerio de Ciencia, Tecnología e Innovación
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