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 773
Special Issue Editors
Interests: biostatistics applied to health; sport and exercise sciences
Interests: Bayesian analysis, sports performance; predicting survival in cardiac patients; sport psychology; mental toughness; emotional intelligence and motivational climate; sport; health
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
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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
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