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Pseudoreplication in physiology: More means less

This article reviews how to analyze data from experiments designed to compare the cellular physiology of two or more groups of animals or people. This is commonly done by measuring data from several cells from each animal and using simple t tests or ANOVA to compare between groups. I use simulations...

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Detalles Bibliográficos
Autor principal: Eisner, David A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Rockefeller University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814346/
https://www.ncbi.nlm.nih.gov/pubmed/33464305
http://dx.doi.org/10.1085/jgp.202012826
Descripción
Sumario:This article reviews how to analyze data from experiments designed to compare the cellular physiology of two or more groups of animals or people. This is commonly done by measuring data from several cells from each animal and using simple t tests or ANOVA to compare between groups. I use simulations to illustrate that this method can give erroneous positive results by assuming that the cells from each animal are independent of each other. This problem, which may be responsible for much of the lack of reproducibility in the literature, can be easily avoided by using a hierarchical, nested statistics approach.