The DOI matches its Crossref record; 27 of the 28 references it cites were found in a registry or an index.
Progressive Statistics for Studies in Sports Medicine and Exercise Science
Abstract
Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log…
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“The unexplained residual differences between studies, represented by the random effect, were large (~21%) but fell to moderate, when all predictors were included in the model (Hopkins et al., 2009).”
From Insulin resistance in polycystic ovary syndrome: a systematic review and meta-analysis of euglycaemic–hyperinsulinaemic clamp studies (2016) · cites this paper as Hopkins et al., 2009
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- Hopkins, 2004, Bias in Bland-Altman but not regression validity analyses., Sportscience, 8, 42
- Hopkins, 2006, Estimating sample size for magnitude-based inerences., Sportscience, 10, 63
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Buchheit, M., & Laursen, P. B. (2013) · Sports Medicine · doi:10.1007/s40279-013-0029-x · Cited by 1,490
Medicine & science in sports & exercise
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Milanović, Z., Sporiš, G., & Weston, M. (2015) · Sports Medicine · doi:10.1007/s40279-015-0365-0 · Cited by 923
Monitoring training status with HR measures: do all roads lead to Rome?
Buchheit, M. (2014) · Frontiers in Physiology · doi:10.3389/fphys.2014.00073 · Cited by 1,016
High-Intensity Interval Training, Solutions to the Programming Puzzle
Buchheit, M., & Laursen, P. B. (2013) · Sports Medicine · doi:10.1007/s40279-013-0066-5 · Cited by 970
Metadata
- Authors
- HOPKINS, W. G., MARSHALL, S. W., BATTERHAM, A. M., & HANIN, J.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Teesside University (GB)
- Research Institute for Olympic Sports (FI)
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2009-01
- Volume
- 41
- Issue
- 1
- Pages
- 3-12
- ISSN
- 0195-9131 (ISSN-L)
- OpenAlex
- W2020794622
- Cited by
- 9,128
- References
- 28
- Citations by year
- 2026: 571 · 2025: 765 · 2024: 856 · 2023: 735 · 2022: 882 · 2021: 901 · 2020: 887 · 2019: 750 · 2018: 767 · 2017: 588 · 2016: 360 · 2015: 284 · 2014: 305 · 2013: 175 · 2012: 115
- FWCI
- 57.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medicine & Science in Sports & Exercise (publishedVersion)
- PubMed (publishedVersion)
- Victoria University Research Repository (Victoria University) (submittedVersion)
- Teesside University Research Portal (Teesside University) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- estimation precision, null hypothesis testing, sample size justification, nonparametric statistics, limits of agreement, qualitative research, research ethics approval, covariates, logarithmic transformation, outliers, measurement error, bias, reporting guidelines, sports medicine, kinesiology
- MeSH terms
- Data Interpretation, Statistical, Humans, Research Design, Sports Medicine, Exercise, Sample Size, Biomedical Research
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