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Elife. 2018 Jan 10;7. pii: e32486. doi: 10.7554/eLife.32486.

Unit of analysis issues in laboratory-based research.

Author information

1
Warwick Medical School, University of Warwick, Coventry, United Kingdom.
2
Sheffield School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.
3
Public Health Building, University of Birmingham, Birmingham, United Kingdom.

Abstract

Many studies in the biomedical research literature report analyses that fail to recognise important data dependencies from multilevel or complex experimental designs. Statistical inferences resulting from such analyses are unlikely to be valid and are often potentially highly misleading. Failure to recognise this as a problem is often referred to in the statistical literature as a unit of analysis (UoA) issue. Here, by analysing two example datasets in a simulation study, we demonstrate the impact of UoA issues on study efficiency and estimation bias, and highlight where errors in analysis can occur. We also provide code (written in R) as a resource to help researchers undertake their own statistical analyses.

KEYWORDS:

Science Forum; epidemiology; experimental design; global health; mixed-effects models; statistics

PMID:
29319501
PMCID:
PMC5762161
DOI:
10.7554/eLife.32486
[Indexed for MEDLINE]
Free PMC Article

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