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What exercise and sport scientists don't understand.

H D Speed1, M B Andersen

  • 1Victoria University, Melbourne, Australia. Harriet.Speed@vu.edu.au

Journal of Science and Medicine in Sport
|June 6, 2000
PubMed
Summary

Exercise and sport science research in the Australian Journal of Science and Medicine in Sport (AJSMS) is likely underpowered, particularly for detecting small effects. Studies rarely reported or interpreted effect sizes, and experiment-wise Type I error rates were high.

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Area of Science:

  • Exercise Science
  • Sports Medicine
  • Sport Psychology

Background:

  • Research design and statistical power are critical for valid scientific findings.
  • Previous analyses have indicated potential issues with statistical power in various scientific fields.

Purpose of the Study:

  • To evaluate the statistical power, effect size reporting, and Type I error control in studies published in the Australian Journal of Science and Medicine in Sport (AJSMS) between 1996 and 1997.
  • To identify potential limitations in research design and interpretation within exercise and sport science.

Main Methods:

  • Analysis of 29 studies published in AJSMS in 1996-1997.
  • Computation of statistical power for small, medium, and large effects using Cohen's conventions.
  • Examination of effect size reporting and interpretation, and control of experiment-wise (EW) Type I error rates.

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Main Results:

  • Median power to detect small, medium, and large effects was .14, .65, and .97, respectively.
  • Effect size reporting was infrequent, and their interpretation was rarer.
  • The mean EW Type I error rate across studies was .49.

Conclusions:

  • Research in exercise and sport science, as represented in AJSMS during this period, was likely underpowered, especially for small effects.
  • Inadequate attention to effect sizes and experiment-wise error rates may lead to substantial Type I and Type II errors.
  • Researchers are urged to conduct power analyses, report and interpret effect sizes, and control for EW error to improve research quality.