ArticleStatistics and its interface2011
Accurate and flexible power calculations on the spot: Applications to genomic research.
Article in Statistics and its interface, 2011. 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.
- The effectiveness of breakfast recommendations on weight loss: a randomized controlled trial.The American journal of clinical nutrition · 2014Trial
- From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022Review
- Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.Human genetics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Often investigators need to calculate power to demonstrate feasibility of proposed genetic studies for grant proposals or simply to aid in their own study planning. Frequently, power can be easily calculated using a closed form formula. However, in some situations such formulae for calculating power have not been derived and derivation on demand may be difficult if not impossible. In these situations investigators typically perform simulations specific to the study. Yet such simulations can be computationally extensive and take weeks to months depending on the circumstances. Here, we provide a simple method to rapidly estimate power when one has power estimates available for corresponding situations that differ from the situation of interest only in sample size and/or alpha (type I error) level desired. We show by application to multiple published results from the genomics field that these methods are generally very accurate and applicable to a broad range of genomic studies.
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.