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Sensitivity of discrete symmetry metrics: Implications for metric choice

Gait asymmetry is present in several pathological populations, including those with Parkinson’s disease, Huntington’s disease, and stroke survivors. Previous studies suggest that commonly used discrete symmetry metrics, which compare single bilateral variables, may not be equally sensitive to underl...

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Detalles Bibliográficos
Autores principales: Hill, Allen, Nantel, Julie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119531/
https://www.ncbi.nlm.nih.gov/pubmed/35588125
http://dx.doi.org/10.1371/journal.pone.0268581
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author Hill, Allen
Nantel, Julie
author_facet Hill, Allen
Nantel, Julie
author_sort Hill, Allen
collection PubMed
description Gait asymmetry is present in several pathological populations, including those with Parkinson’s disease, Huntington’s disease, and stroke survivors. Previous studies suggest that commonly used discrete symmetry metrics, which compare single bilateral variables, may not be equally sensitive to underlying effects of asymmetry, and the use of a metric with low sensitivity could result in unnecessarily low statistical power. The purpose of this study was to provide a comprehensive assessment of the sensitivity of commonly used discrete symmetry metrics to better inform design of future studies. Monte Carlo simulations were used to estimate the statistical power of each symmetry metric at a range of asymmetry magnitudes, group/condition variabilities, and sample sizes. Power was estimated by repeated comparison of simulated symmetric and asymmetric data with a paired t-test, where the proportion of significant results is equivalent to the power. Simulation results confirmed that not all common discrete symmetry metrics are equally sensitive to reference effects of asymmetry. Multiple symmetry metrics exhibit equivalent sensitivities, but the most sensitive discrete symmetry metric in all cases is a bilateral difference (e.g. left—right). A ratio (e.g. left/right) has poor sensitivity when group/condition variability is not small, but a log-transformation produces increased sensitivity. Additionally, two metrics which included an absolute value in their definitions showed increased sensitivity when the absolute value was removed. Future studies should consider metric sensitivity when designing analyses to reduce the possibility of underpowered research.
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spelling pubmed-91195312022-05-20 Sensitivity of discrete symmetry metrics: Implications for metric choice Hill, Allen Nantel, Julie PLoS One Research Article Gait asymmetry is present in several pathological populations, including those with Parkinson’s disease, Huntington’s disease, and stroke survivors. Previous studies suggest that commonly used discrete symmetry metrics, which compare single bilateral variables, may not be equally sensitive to underlying effects of asymmetry, and the use of a metric with low sensitivity could result in unnecessarily low statistical power. The purpose of this study was to provide a comprehensive assessment of the sensitivity of commonly used discrete symmetry metrics to better inform design of future studies. Monte Carlo simulations were used to estimate the statistical power of each symmetry metric at a range of asymmetry magnitudes, group/condition variabilities, and sample sizes. Power was estimated by repeated comparison of simulated symmetric and asymmetric data with a paired t-test, where the proportion of significant results is equivalent to the power. Simulation results confirmed that not all common discrete symmetry metrics are equally sensitive to reference effects of asymmetry. Multiple symmetry metrics exhibit equivalent sensitivities, but the most sensitive discrete symmetry metric in all cases is a bilateral difference (e.g. left—right). A ratio (e.g. left/right) has poor sensitivity when group/condition variability is not small, but a log-transformation produces increased sensitivity. Additionally, two metrics which included an absolute value in their definitions showed increased sensitivity when the absolute value was removed. Future studies should consider metric sensitivity when designing analyses to reduce the possibility of underpowered research. Public Library of Science 2022-05-19 /pmc/articles/PMC9119531/ /pubmed/35588125 http://dx.doi.org/10.1371/journal.pone.0268581 Text en © 2022 Hill, Nantel 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
Hill, Allen
Nantel, Julie
Sensitivity of discrete symmetry metrics: Implications for metric choice
title Sensitivity of discrete symmetry metrics: Implications for metric choice
title_full Sensitivity of discrete symmetry metrics: Implications for metric choice
title_fullStr Sensitivity of discrete symmetry metrics: Implications for metric choice
title_full_unstemmed Sensitivity of discrete symmetry metrics: Implications for metric choice
title_short Sensitivity of discrete symmetry metrics: Implications for metric choice
title_sort sensitivity of discrete symmetry metrics: implications for metric choice
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119531/
https://www.ncbi.nlm.nih.gov/pubmed/35588125
http://dx.doi.org/10.1371/journal.pone.0268581
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