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Published online by Cambridge University Press: 17 April 2022
This chapter handles power and sample size estimation used for study design. A very flexible method to estimate power is to simulate. Binomial confidence intervals can be used on the simulated power estimates to determine the number of simulations needed for the precision desired. To determine sample size by simulation, we introduce an algorithm based on methods for dose finding studies, that does not need a large number of replications at each different sample size tried. We present a general normal theory approximation, to give approximate sample sizes for designs that use simple tests such as the two-sample t-test, and the two-sample difference in binomial proportions test. We generalize to cases with unequal allocation between arms, or more complicated tests such as the logrank test. We discuss modifications to sample sizes for nonadherence or missing data.
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