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When neuroscience met clinical pathology: partitioning experimental variation to aid data interpretation in neuroscience

Research output: Contribution to journalArticle

Nick D Jeffery, Simon T Bate, Sina Safayi, Matt Howard, Lawrence Moon, Unity Jeffery

Original languageEnglish
JournalEuropean Journal of Neuroscience
DOIs
E-pub ahead of print29 Jan 2018

Documents

  • Jeffery et al 2018 preprint

    Jeffery_et_al_2018_preprint.pdf, 1.23 MB, application/pdf

    Uploaded date:27 Mar 2018

    Version:Submitted manuscript

King's Authors

Abstract

In animal experiments, neuroscientists typically assess the effectiveness of interventions by comparing the average response of groups of treated and untreated animals. While providing useful insights, focusing only on group effects risks overemphasis of small, statistically significant but physiologically unimportant differences. Such differences can be created by analytical variability or physiological within-individual variation, especially if the number of animals in each group is small enough that one or two outlier values can have considerable impact on the summary measures for the group. This article is protected by copyright. All rights reserved.

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