Effect size and power

Content

  • Measures of effect size
  • Power calculations
  • Interplay between sample size, effect and power

Learning objectives

At the end of the session, students should be capable of

  • correctly report effect size for common statistics in analysis of variance models
  • deduce the sample size necessary to replicate a study at a given power
  • explain the interplay between sample size, power and effect size.

Readings

Complementary readings

  • Chapters 3 (section Power of the \(F\) Test) and 4 (section Measures of Effects) of Maxwell et al. (2017).
  • Lakens (2013)
  • Steiger (2004)
  • Kelley & Preacher (2012)

Slides

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Tip

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Exercise

References

Kelley, K., & Preacher, K. (2012). On effect size. Psychological Methods, 17(2), 137–152. https://doi.org/10.1037/a0028086
Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for \(t\)-tests and ANOVAs. Frontiers in Psychology, 4, 863. https://doi.org/10.3389/fpsyg.2013.00863
Maxwell, S. E., Delaney, H. D., & Kelley, K. (2017). Designing experiments and analyzing data: A model comparison perspective (3rd ed.). routledge. https://doi.org/10.4324/9781315642956
Steiger, J. H. (2004). Beyond the \(F\) test: Effect size confidence intervals and tests of close fit in the analysis of variance and contrast analysis. Psychological Methods, 9, 164–182. https://doi.org/10.1037/1082-989X.9.2.164