ArticleJournal of athletic training2025
Multiplying Alpha: When Statistical Tests Compound in Sports Medicine Research.
Article in Journal of athletic training, 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.
- To adjust or not to adjust? Matching statistical choices to scientific questions in exercise physiology and sport science.Frontiers in physiology · 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
Scientific inquiry aims to minimize bias and ensure accurate conclusions. A critical yet often overlooked issue in sports medicine and exercise science research is the family-wise error rate (FWER) and experimental-wise error rate (EWER), which increase with multiple statisticalinferences, inflating the risk of Type I errors. While FWER corrections are standard in post-hoc ANOVA tests, they are inconsistently applied in broader research contexts. Using an example from our research team of over 67 million regression models, we illustrate how failing to correct for FWER can create spurious findings. Approximately 3 million (4.4%) models werestatistically significant (p<0.05), aligning with the expected false-positive rate. This underscores the necessity of solutions such as preregistration, false discovery rate control, and Bayesian approaches. Without proper corrections, erroneous conclusions may mislead clinical decision- making and potentially harm patients, highlighting the importance of rigorous statistical methods in evidence-based sports medicine.
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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.