ArticleAmerican journal of epidemiology2022
Casting New Light on Statistical Power: An Illuminating Analogy and Strategies to Avoid Underpowered Trials.
Article in American journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 11 citations in OpenAlex.
- Physiotherapy with integrated virtual reality for patients with severe chronic low back pain: cluster-randomized controlled trial (VARIETY).BMC musculoskeletal disorders · 2026Trial
- Electrochemotherapy Following Surgical Cytoreduction for the Treatment of Recurrent Equine Sarcoids: A Retrospective Study of 23 Lesions.Veterinary sciences · 2026Article
- Patterns of care and outcomes following external ventricular drain placement: Insights from the England HES administrative data set.Brain & spine · 2026Article
- Prematurity and Low Birth Weight Among Food-Secure and Food-Insecure Households: A Comparative Study in Surabaya, Indonesia.Nutrients · 2025Article
- Digital health outreach to promote postpartum screening after gestational diabetes: A randomized factorial pilot study.PEC innovation · 2024Article
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
Abstract
Current standards for methodological rigor and trial reporting underscore the critical issue of statistical power. Still, the chance of detecting most effects reported in randomized controlled trials in medicine and other disciplines is currently lower than winning a toss of a fair coin. Here we propose that investigators who retain a practical understanding of how statistical power works can proactively avoid the potentially devastating consequences of underpowered trials. We first offer a vivid, carefully constructed analogy that illuminates the underlying relationships among 3 of the 5 essential parameters-namely, statistical power, effect size, and sample size-while holding the remaining 2 parameters constant (type of statistical test and significance level). Second, we extend the analogy to a set of critical scenarios in which investigators commonly miss detecting intervention effects due to insufficient statistical power. Third, we highlight effective pragmatic strategies for the design and conduct of sufficiently powered trials, without increasing sample size.
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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.