Unit of analysis issues in laboratory based research:

Nicholas Parsons, Dawn Teare, Alice Sitch

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
247 Downloads (Pure)

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.
Original languageEnglish
JournaleLife
Early online date10 Jan 2018
DOIs
Publication statusE-pub ahead of print - 10 Jan 2018

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