ArticleLaboratory animals2025
Giving less power to statistical power.
Article in Laboratory animals, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Comment on "glycemic status and left atrial structure and function in adults with metabolic syndrome and overweight-obesity".International journal of cardiology. Cardiovascular risk and prevention · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Researchers often need to justify their choice of sample size, particularly in fields such as animal and clinical research, where there are obvious ethical concerns about relying on too many or too few study subjects. The common approach is still to depend on statistical power calculations, typically carried out using simple formulas and default values. Over-reliance on power, however, not only carries the baggage of statistical hypothesis tests that have been criticized for decades, but also blocks an opportunity to strengthen the research in the design phase by learning about challenges in interpretation before the study is carried out. We recommend constructing a 'quantitative backdrop' in the planning stage of a study, which means explicitly connecting ranges of possible research outcomes to their expected real-life implications. Such a backdrop can facilitate
Indexed as
Identifiers
What OpenQuestion holds
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.