Stratified-adjusted versus unstratified assessment of sample size and power for analyses of proportions

  • John M. Lachin
  • Oliver M. Bautista
Chapter
Part of the Cancer Treatment and Research book series (CTAR, volume 75)

Abstract

In any scientific investigation, it is important to evaluate the adequacy of sample size with regard to one’s ability to provide clear answers to the questions posed. In many cases, this assessment is based upon the power of a statistical test for the comparison of two groups with respect to the probability of some event or characteristic in two independent samples of subjects. In the simplest case, the proportions of subjects with some characteristic are compared between the two groups using a standard chi-square or Z-test for a 2 × 2 table. Various authors have described expressions for the approximate power of the large sample chi-square test, the most widely used being the expression based upon the large sample Z-test for two proportions of Halperin et al. [1]. This and other widely used procedures for the evaluation of sample size on the basis of power are reviewed by Lachin [2] and Donner [3], among others. This approach is based upon an unconditional or marginal assessment of the treatment group difference without consideration of other covariate effects.

Keywords

Adjusted Odds Ratio Positive Real Root Unadjusted Odds Ratio Adjusted Power Common Odds Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • John M. Lachin
  • Oliver M. Bautista

There are no affiliations available

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