Determine required sample size for a given confidence interval width for Cohen's d
This function computes how many participants you need if you want to achieve a confidence interval of a given width. This is useful when you do a study and you are interested in how strongly twovariables are associated.
pwr.cohensdCI(d, w = 0.1, conf.level = 0.95, extensive = FALSE, silent=FALSE)
- The expected value(s) of Cohen's d.
- The half-width of the desired confidence interval (the margin of error).
- The confidence level of the desired confidence interval.
- Whether you want extensive results or just the sample size(s).
- Whether you want warnings or not.
The sample size(s) you need (or, if
TRUE, also the requested and resulting confidence interval bounds).
Peters, G. J. Y. & Crutzen, R. (forthcoming) An easy and foolproof method for establishing how effective an intervention of behavior change method is: required sample size for accurate parameter estimation in health psychology. Maxwell, S. E., Kelley, K., & Rausch, J. R. (2008). Sample size planning for statistical power and accuracy in parameter estimation. Annual Review of Psychology, 59, 537-63. https://doi.org/10.1146/annurev.psych.59.103006.093735 Cumming, G. (2013). The New Statistics: Why and How. Psychological Science, (November). https://doi.org/10.1177/0956797613504966
### If you want to estimate an expected effect size of ### 0.5 (tentatively qualified as a 'moderate' association), ### and you want to estimate with a maximum confidence interval ### width of .1 (e.g. from .45 to .55), you'll need a lot of people: pwr.cohensdCI(.5, w=.05); ### If you expect a smaller effect and are content with a less ### accurate estimation, you'll need way less (but still a lot): pwr.cohensdCI(.2, w=.1); ### If you want more extensive feedback: pwr.cohensdCI(.2, w=.1, extensive=TRUE); ### As Cohen's d becomes larger, the confidence interval widens and ### therefore, you need more people: pwr.cohensdCI(c(.2, .5, .8), w=.1);