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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...

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Detalles Bibliográficos
Autores principales: Courtney, Matthew G. R., Chang, Kevin C. T., Mei, Bing, Meissel, Kane, Rowe, Luke I., Issayeva, Laila B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
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.
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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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