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Cited by 9,128Statistical Methods in EpidemiologyMeta-analysis and systematic reviewsStatistical Methods in Clinical Trials

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

HOPKINS, WILLIAM G., MARSHALL, STEPHEN W., BATTERHAM, ALAN M., HANIN, JURI·2009·Medicine & Science in Sports & Exercise
DOI 10.1249/mss.0b013e31818cb278
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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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Crossref · 10.1249/mss.0b013e31818cb278

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Research works printed but not linked: 5

  1. Batterham, 2005, A decision tree for controlled trials., Sportscience, 9, 33
  2. Hopkins, 2004, Bias in Bland-Altman but not regression validity analyses., Sportscience, 8, 42
  3. Hopkins, 2006, Estimating sample size for magnitude-based inerences., Sportscience, 10, 63
  4. Hopkins, 2008, Research designs: choosing and fine-tuning a design for your study., Sportscience, 12, 12
  5. Hopkins, 2006, A spreadsheet for combining outcomes from several subject groups., Sportscience, 10, 51

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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)
ORCID
Venue
Medicine & Science in Sports & Exercise
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2009-01
Volume
41
Issue
1
Pages
3-12
ISSN
0195-9131 (ISSN-L)
DOI
10.1249/mss.0b013e31818cb278
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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