ArticleLaboratory animals2024
Simulation methodologies to determine statistical power in laboratory animal research studies.
Article in Laboratory animals, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Zebrafish behavioral assessment as a first-tier whole-organism NAM for developmental neurotoxicity: A multi-laboratory evaluation.Neurotoxicology · 2026Article
- Power calculations for larval zebrafish in light-dark transition test for developmental neurotoxicity.Neurotoxicology · 2026Article
- Assessing replicability and power estimates of behavioral performance of control rats across standardized pre-clinical and toxicology studies.Neurotoxicology and teratologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Null hypothesis significance testing is a statistical tool commonly employed throughout laboratory animal research. When experimental results are reported, the reproducibility of the results is of utmost importance. Establishing standard, robust, and adequately powered statistical methodology in the analysis of laboratory animal data is critical to ensure reproducible and valid results. Simulation studies are a reliable method for assessing the power of statistical tests, however, biologists may not be familiar with simulation studies for power despite their efficacy and accessibility. Through an example of simulated Harlan Sprague-Dawley (HSD) rat organ weight data, we highlight the importance of conducting power analyses in laboratory animal research. Using simulations to determine statistical power prior to an experiment is a financially and ethically sound way to validate statistical tests and to help ensure reproducibility of findings in line with the 4R principles of animal welfare.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.