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autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects
In this paper, we present autopsych, a novel online tool that allows school assessment experts, test developers, and researchers to perform routine psychometric analyses and equating of student test data and to examine the effect of student demographic and group conditions on student test performanc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505029/ https://www.ncbi.nlm.nih.gov/pubmed/34634792 http://dx.doi.org/10.1371/journal.pone.0257682 |
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author | Courtney, Matthew G. R. Chang, Kevin C. T. Mei, Bing Meissel, Kane Rowe, Luke I. Issayeva, Laila B. |
author_facet | Courtney, Matthew G. R. Chang, Kevin C. T. Mei, Bing Meissel, Kane Rowe, Luke I. Issayeva, Laila B. |
author_sort | Courtney, Matthew G. R. |
collection | PubMed |
description | In this paper, we present autopsych, a novel online tool that allows school assessment experts, test developers, and researchers to perform routine psychometric analyses and equating of student test data and to examine the effect of student demographic and group conditions on student test performance. The app extends current open-source software by providing (1) extensive embedded result narration and summaries for written reports, (2) improved handling of partial credit data via customizable item-person Wright maps, (3) customizable item- and person-flagging systems, (4) item-response theory model constraints and controls, (5) many-facets Rasch analysis to examine item bias, (6) Rasch fixed item equating for mapping student ability across test forms, (7) tabbed spreadsheet outputs and immediate options for secondary data analysis, (8) customizable graphical color schemes, (9) extended ANOVA analysis for examining group differences, and (10) inter-rater reliability analyses for the verifying the consistency of rater scoring systems. We present the app’s architecture and functionalities and test its performance with simulated and real-world small-, medium-, and large-scale assessment data. Implications and planned future developments are also discussed. |
format | Online Article Text |
id | pubmed-8505029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85050292021-10-12 autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects Courtney, Matthew G. R. Chang, Kevin C. T. Mei, Bing Meissel, Kane Rowe, Luke I. Issayeva, Laila B. PLoS One Research Article In this paper, we present autopsych, a novel online tool that allows school assessment experts, test developers, and researchers to perform routine psychometric analyses and equating of student test data and to examine the effect of student demographic and group conditions on student test performance. The app extends current open-source software by providing (1) extensive embedded result narration and summaries for written reports, (2) improved handling of partial credit data via customizable item-person Wright maps, (3) customizable item- and person-flagging systems, (4) item-response theory model constraints and controls, (5) many-facets Rasch analysis to examine item bias, (6) Rasch fixed item equating for mapping student ability across test forms, (7) tabbed spreadsheet outputs and immediate options for secondary data analysis, (8) customizable graphical color schemes, (9) extended ANOVA analysis for examining group differences, and (10) inter-rater reliability analyses for the verifying the consistency of rater scoring systems. We present the app’s architecture and functionalities and test its performance with simulated and real-world small-, medium-, and large-scale assessment data. Implications and planned future developments are also discussed. Public Library of Science 2021-10-11 /pmc/articles/PMC8505029/ /pubmed/34634792 http://dx.doi.org/10.1371/journal.pone.0257682 Text en © 2021 Courtney et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Courtney, Matthew G. R. Chang, Kevin C. T. Mei, Bing Meissel, Kane Rowe, Luke I. Issayeva, Laila B. autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects |
title | autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects |
title_full | autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects |
title_fullStr | autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects |
title_full_unstemmed | autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects |
title_short | autopsych: An R Shiny tool for the reproducible Rasch analysis, differential item functioning, equating, and examination of group effects |
title_sort | autopsych: an r shiny tool for the reproducible rasch analysis, differential item functioning, equating, and examination of group effects |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505029/ https://www.ncbi.nlm.nih.gov/pubmed/34634792 http://dx.doi.org/10.1371/journal.pone.0257682 |
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