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rmcorrShiny: A web and standalone application for repeated measures correlation

We describe a web and standalone Shiny app for calculating the common, linear within-individual association for repeated assessments of paired measures with multiple individuals: repeated measures correlation (rmcorr). This tool makes rmcorr more widely accessible, providing a graphical interface fo...

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Detalles Bibliográficos
Autores principales: Marusich, Laura R., Bakdash, Jonathan Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456376/
https://www.ncbi.nlm.nih.gov/pubmed/34621514
http://dx.doi.org/10.12688/f1000research.55027.2
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author Marusich, Laura R.
Bakdash, Jonathan Z.
author_facet Marusich, Laura R.
Bakdash, Jonathan Z.
author_sort Marusich, Laura R.
collection PubMed
description We describe a web and standalone Shiny app for calculating the common, linear within-individual association for repeated assessments of paired measures with multiple individuals: repeated measures correlation (rmcorr). This tool makes rmcorr more widely accessible, providing a graphical interface for performing and visualizing the output of analysis with rmcorr. In contrast to rmcorr, most widely used correlation techniques assume paired data are independent. Incorrectly analyzing repeated measures data as independent will likely produce misleading results. Using aggregation or separate models to address the issue of independence may obscure meaningful patterns and will also tend to reduce statistical power. rmcorrShiny (repeated measures correlation Shiny) provides a simple and accessible solution for computing the repeated measures correlation. It is available at: https://lmarusich.shinyapps.io/shiny_rmcorr/.
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spelling pubmed-84563762021-10-06 rmcorrShiny: A web and standalone application for repeated measures correlation Marusich, Laura R. Bakdash, Jonathan Z. F1000Res Software Tool Article We describe a web and standalone Shiny app for calculating the common, linear within-individual association for repeated assessments of paired measures with multiple individuals: repeated measures correlation (rmcorr). This tool makes rmcorr more widely accessible, providing a graphical interface for performing and visualizing the output of analysis with rmcorr. In contrast to rmcorr, most widely used correlation techniques assume paired data are independent. Incorrectly analyzing repeated measures data as independent will likely produce misleading results. Using aggregation or separate models to address the issue of independence may obscure meaningful patterns and will also tend to reduce statistical power. rmcorrShiny (repeated measures correlation Shiny) provides a simple and accessible solution for computing the repeated measures correlation. It is available at: https://lmarusich.shinyapps.io/shiny_rmcorr/. F1000 Research Limited 2021-11-08 /pmc/articles/PMC8456376/ /pubmed/34621514 http://dx.doi.org/10.12688/f1000research.55027.2 Text en Copyright: © 2021 Marusich LR and Bakdash JZ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Marusich, Laura R.
Bakdash, Jonathan Z.
rmcorrShiny: A web and standalone application for repeated measures correlation
title rmcorrShiny: A web and standalone application for repeated measures correlation
title_full rmcorrShiny: A web and standalone application for repeated measures correlation
title_fullStr rmcorrShiny: A web and standalone application for repeated measures correlation
title_full_unstemmed rmcorrShiny: A web and standalone application for repeated measures correlation
title_short rmcorrShiny: A web and standalone application for repeated measures correlation
title_sort rmcorrshiny: a web and standalone application for repeated measures correlation
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456376/
https://www.ncbi.nlm.nih.gov/pubmed/34621514
http://dx.doi.org/10.12688/f1000research.55027.2
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