On Sample-Size and Power Calculations for Studies Using Confidence Intervals

A recent trend in epidemiologic analysis has been away from significance tests and toward confidence intervals. In accord with this trend, several authors have proposed the use of expected confidence intervals in the design of epidemiologic studies. This paper discusses how expected confidence intervals, if not properly centered, can be misleading indicators of the discriminatory power of a study. To rectify such problems, the study must be designed so that the confidence interval has a high probability of not containing at least one plausible but incorrect parameter value. To achieve this end, conventional formulas for power and sample size may be used. Expected intervals, if properly centered, can be used to design uniformly powerful studies but will yield sample-size requirements far in excess of previously proposed methods.