Cargando…
Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data
We assess the degree of phenotypic variation in a cohort of 24-month-old male C57BL/6 mice. Because murine studies often use small sample sizes, if the commonly relied upon assumption of a normal distribution of residuals is not met, it may inflate type I error rates. In this study, 3–20 mice are re...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449850/ https://www.ncbi.nlm.nih.gov/pubmed/34407413 http://dx.doi.org/10.1016/j.celrep.2021.109560 |
_version_ | 1784569500201385984 |
---|---|
author | Alfaras, Irene Ejima, Keisuke Teixeira, Camila Vieira Ligo Di Germanio, Clara Mitchell, Sarah J. Hamilton, Samuel Ferrucci, Luigi Price, Nathan L. Allison, David B. Bernier, Michel de Cabo, Rafael |
author_facet | Alfaras, Irene Ejima, Keisuke Teixeira, Camila Vieira Ligo Di Germanio, Clara Mitchell, Sarah J. Hamilton, Samuel Ferrucci, Luigi Price, Nathan L. Allison, David B. Bernier, Michel de Cabo, Rafael |
author_sort | Alfaras, Irene |
collection | PubMed |
description | We assess the degree of phenotypic variation in a cohort of 24-month-old male C57BL/6 mice. Because murine studies often use small sample sizes, if the commonly relied upon assumption of a normal distribution of residuals is not met, it may inflate type I error rates. In this study, 3–20 mice are resampled from the empirical distributions of 376 mice to create plasmodes, an approach for computing type I error rates and power for commonly used statistical tests without assuming a normal distribution of residuals. While all of the phenotypic and metabolic variables studied show considerable variability, the number of animals required to achieve adequate power is markedly different depending on the statistical test being performed. Overall, this work provides an analysis with which researchers can make informed decisions about the sample size required to achieve statistical power from specific measurements without a priori assumptions of a theoretical distribution. |
format | Online Article Text |
id | pubmed-8449850 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-84498502021-09-19 Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data Alfaras, Irene Ejima, Keisuke Teixeira, Camila Vieira Ligo Di Germanio, Clara Mitchell, Sarah J. Hamilton, Samuel Ferrucci, Luigi Price, Nathan L. Allison, David B. Bernier, Michel de Cabo, Rafael Cell Rep Article We assess the degree of phenotypic variation in a cohort of 24-month-old male C57BL/6 mice. Because murine studies often use small sample sizes, if the commonly relied upon assumption of a normal distribution of residuals is not met, it may inflate type I error rates. In this study, 3–20 mice are resampled from the empirical distributions of 376 mice to create plasmodes, an approach for computing type I error rates and power for commonly used statistical tests without assuming a normal distribution of residuals. While all of the phenotypic and metabolic variables studied show considerable variability, the number of animals required to achieve adequate power is markedly different depending on the statistical test being performed. Overall, this work provides an analysis with which researchers can make informed decisions about the sample size required to achieve statistical power from specific measurements without a priori assumptions of a theoretical distribution. 2021-08-17 /pmc/articles/PMC8449850/ /pubmed/34407413 http://dx.doi.org/10.1016/j.celrep.2021.109560 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ). |
spellingShingle | Article Alfaras, Irene Ejima, Keisuke Teixeira, Camila Vieira Ligo Di Germanio, Clara Mitchell, Sarah J. Hamilton, Samuel Ferrucci, Luigi Price, Nathan L. Allison, David B. Bernier, Michel de Cabo, Rafael Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data |
title | Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data |
title_full | Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data |
title_fullStr | Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data |
title_full_unstemmed | Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data |
title_short | Empirical versus theoretical power and type I error (false-positive) rates estimated from real murine aging research data |
title_sort | empirical versus theoretical power and type i error (false-positive) rates estimated from real murine aging research data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449850/ https://www.ncbi.nlm.nih.gov/pubmed/34407413 http://dx.doi.org/10.1016/j.celrep.2021.109560 |
work_keys_str_mv | AT alfarasirene empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT ejimakeisuke empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT teixeiracamilavieiraligo empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT digermanioclara empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT mitchellsarahj empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT hamiltonsamuel empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT ferrucciluigi empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT pricenathanl empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT allisondavidb empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT berniermichel empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata AT decaborafael empiricalversustheoreticalpowerandtypeierrorfalsepositiveratesestimatedfromrealmurineagingresearchdata |