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Fitting item response unfolding models to Likert-scale data using mirt in R

While a large family of unfolding models for Likert-scale response data have been developed for decades, very few applications of these models have been witnessed in practice. There may be several reasons why these have not appeared more widely in published research, however one obvious limitation a...

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Autores principales: Liu, Chen-Wei, Chalmers, R. Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5933773/
https://www.ncbi.nlm.nih.gov/pubmed/29723217
http://dx.doi.org/10.1371/journal.pone.0196292
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author Liu, Chen-Wei
Chalmers, R. Philip
author_facet Liu, Chen-Wei
Chalmers, R. Philip
author_sort Liu, Chen-Wei
collection PubMed
description While a large family of unfolding models for Likert-scale response data have been developed for decades, very few applications of these models have been witnessed in practice. There may be several reasons why these have not appeared more widely in published research, however one obvious limitation appears to be the absence of suitable software for model estimation. In this article, the authors demonstrate how the mirt package can be adopted to estimate parameters from various unidimensional and multidimensional unfolding models. To concretely demonstrate the concepts and recommendations, a tutorial and examples of R syntax are provided for practical guidelines. Finally, the performance of mirt is evaluated via parameter-recovery simulation studies to demonstrate its potential effectiveness. The authors argue that, armed with the mirt package, applying unfolding models to Likert-scale data is now not only possible but can be estimated to real-datasets with little difficulty.
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spelling pubmed-59337732018-05-18 Fitting item response unfolding models to Likert-scale data using mirt in R Liu, Chen-Wei Chalmers, R. Philip PLoS One Research Article While a large family of unfolding models for Likert-scale response data have been developed for decades, very few applications of these models have been witnessed in practice. There may be several reasons why these have not appeared more widely in published research, however one obvious limitation appears to be the absence of suitable software for model estimation. In this article, the authors demonstrate how the mirt package can be adopted to estimate parameters from various unidimensional and multidimensional unfolding models. To concretely demonstrate the concepts and recommendations, a tutorial and examples of R syntax are provided for practical guidelines. Finally, the performance of mirt is evaluated via parameter-recovery simulation studies to demonstrate its potential effectiveness. The authors argue that, armed with the mirt package, applying unfolding models to Likert-scale data is now not only possible but can be estimated to real-datasets with little difficulty. Public Library of Science 2018-05-03 /pmc/articles/PMC5933773/ /pubmed/29723217 http://dx.doi.org/10.1371/journal.pone.0196292 Text en © 2018 Liu, Chalmers http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liu, Chen-Wei
Chalmers, R. Philip
Fitting item response unfolding models to Likert-scale data using mirt in R
title Fitting item response unfolding models to Likert-scale data using mirt in R
title_full Fitting item response unfolding models to Likert-scale data using mirt in R
title_fullStr Fitting item response unfolding models to Likert-scale data using mirt in R
title_full_unstemmed Fitting item response unfolding models to Likert-scale data using mirt in R
title_short Fitting item response unfolding models to Likert-scale data using mirt in R
title_sort fitting item response unfolding models to likert-scale data using mirt in r
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5933773/
https://www.ncbi.nlm.nih.gov/pubmed/29723217
http://dx.doi.org/10.1371/journal.pone.0196292
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