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Biostatistics Reveals New Insights in Sports Science, Sports Medicine, and Health

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 651

Special Issue Editors


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Guest Editor
Faculty of Education Health & Wellbeing, University of Wolverhampton William Penny Brookes (WD) Building Walsall Campus Gorway Road Walsall, Wolverhampton WS1 3BD, UK
Interests: biostatistics applied to health; sport and exercise sciences

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Guest Editor
Department of Physical Activity and Health, Newman University Birmingham, Genners Ln, Bartley Green, Birmingham B32 3NT, UK
Interests: Bayesian analysis, sports performance; predicting survival in cardiac patients; sport psychology; mental toughness; emotional intelligence and motivational climate; sport; health

E-Mail Website
Guest Editor
Faculty Research Centre for Sport, Exercise and Life Sciences, Coventry University, Priory St, Coventry CV1 5FB, UK
Interests: obesity; ergogenic aids; kinanthropometry; physical activity; active videogaming; exercise physiology; strength and conditioning; motor skills; motor competence
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Special Issue Information

Dear Colleagues,

Biostatistical approaches are key in understanding important aspects of sports performance, sports medicine, and health. In recent years, alongside traditional procedures, newer and more innovative methods of biostatistical analysis have been developed, which open up new opportunities to understand phenomena, revealing new insight related to sport, exercise, and health. This Special Issue invites contributions from across the spectrum of health, sport and exercise science, and sports medicine examining the importance and application of biostatistics in sports science, sports medicine, and health. This Special Issue is open to original research, review articles, short reports, brief commentaries, case reports, and meta-analyses related to biostatistics in sports science, sports medicine, and health. The keywords listed below suggest just a few of the many possibilities.

Potential topics include but are not limited to:

  • Bayesian statistics;
  • Allometry;
  • Non-linear regression;
  • R software;
  • Meta analysis and meta regression;
  • Machine learning;
  • Multilevel modelling;
  • Logistic regression;
  • Causal modelling;
  • Structural equation modelling.

Prof. Dr. Alan M. Nevill
Prof. Dr. Tony D. Myers
Prof. Dr. Michael Duncan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Bayesian statistics
  • allometry
  • non-linear regression
  • R software
  • meta analysis and meta regression
  • machine learning
  • multilevel modelling
  • logistic regression
  • causal modelling
  • structural equation modelling

Published Papers

There is no accepted submissions to this special issue at this moment.
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