Abstract
Conditional power combines the findings of a partially completed study with assumptions about the future. The goal is to estimate the probability that the eventual study result will be incompatible with a criterion value, such as acceptable risk or the null hypothesis. Some history and motivation for conditional power calculations are provided, with examples illustrating the application to drug safety studies. This is an expository article suggesting that conditional power, which is well-established in clinical trials research, also has application to observational studies. The utility may be highest in regulatory settings where resources are limited and interim decisions have to be made accurately in the shortest possible time.
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