The quest for "power": contradictory hypotheses and inflated sample sizes.
To have the "power" of avoiding undersized clinical trials, the customary statistical strategy used in the past few decades is aimed at rejecting both a null stochastic hypothesis and a contradictory alternative hypothesis. This approach gives a trial the "power" to confirm the "insignificance" of differences much smaller than the large value of delta desired in trials done to show efficacy. In many instances, however, a prime problem is that the current "double-significance" approach produces sample sizes 2-3 times larger than needed for stochastic confirmation of large differences (> or =delta). The inflated sample sizes and consequent problems can be avoided if a realistic value for delta is chosen and maintained thereafter, and if an adequate "capacity" is calculated for "single significance."
Department of Medicine, Yale University School of Medicine, New Haven, Connecticut 06510, USA.
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Feinstein
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Concato
D015982:Bias; D002986:Clinical Trials as Topic / Q000592:standards*; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D015203:Reproducibility of Results; D018401:Sample Size; D013269:Stochastic Processes