Abstract
Single-laboratory studies conducted under highly standardized conditions are the gold standard in preclinical animal research. Using simulations based on 440 preclinical studies across 13 different interventions in animal models of stroke, myocardial infarction, and breast cancer, we compared the accuracy of effect size estimates between single-laboratory and multi-laboratory study designs. Single-laboratory studies generally failed to predict effect size accurately, and larger sample sizes rendered effect size estimates even less accurate. By contrast, multi-laboratory designs including as few as 2 to 4 laboratories increased coverage probability by up to 42 percentage points without a need for larger sample sizes. These findings demonstrate that within-study standardization is a major cause of poor reproducibility. More representative study samples are required to improve the external validity and reproducibility of preclinical animal research and to prevent wasting animals and resources for inconclusive research.
Original language | English |
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Pages (from-to) | e2003693 |
Journal | PLoS Biology |
Volume | 16 |
Issue number | 2 |
DOIs | |
Publication status | Published - 22 Feb 2018 |
Keywords
- Journal Article
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Emily Sena
- Deanery of Clinical Sciences - Personal Chair of Meta Science and Translational Medicine
- Centre for Clinical Brain Sciences
- Edinburgh Neuroscience
- Collaborative Approach to Meta Analysis and Review of Animal Data from Experimental Studies
- Cerebrovascular Research Group
Person: Academic: Research Active , Academic: Research Active (Research Assistant)