Obtaining power or obtaining precision. Delineating methods of sample-size planning

Eval Health Prof. 2003 Sep;26(3):258-87. doi: 10.1177/0163278703255242.


Sample-size planning historically has been approached from a power analytic perspective in order to have some reasonable probability of correctly rejecting the null hypothesis. Another approach that is not as well-known is one that emphasizes accuracy in parameter estimation (AIPE). From the AIPE perspective, sample size is chosen such that the expected width of a confidence interval will be sufficiently narrow. The rationales of both approaches are delineated and two procedures are given for estimating the sample size from the AIPE perspective for a two-group mean comparison. One method yields the required sample size, such that the expected width of the computed confidence interval will be the value specified. A modification allows for a defined degree of probabilistic assurance that the width of the computed confidence interval will be no larger than specified. The authors emphasize that the correct conceptualization of sample-size planning depends on the research questions and particular goals of the study.

MeSH terms

  • Analysis of Variance
  • Confidence Intervals
  • Data Interpretation, Statistical*
  • Health Services Research / methods
  • Health Services Research / statistics & numerical data
  • Humans
  • Models, Statistical
  • Research Design
  • Sample Size*
  • United States