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Power and Sample Size

Learn how to calculate power, sample size, and effect size for research studies. Customize these key parameters to ensure reliable and meaningful results. Discover online resources for further exploration.

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Power and Sample Size

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  1. Power and Sample Size David M. Thompson, Ph.D., P.T. Associate ProfessorDept. of Biostatistics and EpidemiologyCollege of Public Health, OUHSC

  2. Power and sample size calculations POWER SAMPLE SIZE EFFECT SIZE Specify or estimate any two to calculate the third.

  3. Power • The probability of rejecting the null hypothesis when a specified alternative is true. • Both null and alternative hypotheses must be specified; the alternate hypothesis specifies a clinically meaningful effect size.

  4. Sample Size To calculate sample size, first must specify: •  • Power = (1-) • Effect size • Difference in means • Difference in proportions

  5. Effect size Meaningful and detectable difference in group means, proportions, etc. … …including estimate of within group variability

  6. In study planning: • Power is customarily prespecified at .8 or .9 • A minimal clinically important difference focuses the decision on the effect size, from which we calculate sample size. • If practical conditions constrain the sample size, we specify that, then calculate the effect size we have prespecified power to detect with that sample.

  7. Do it yourself resources Web primer on “hypothesis testing and statistical power” moon.ouhsc.edu/dthompso/CDM/power/hypoth.htm Java applets that explore influences of sample and effect sizes on power http://www.stat.uiowa.edu/~rlenth/Power/ Power and sample size programs (UCSF) http://www.biostat.ucsf.edu/sampsize.html

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