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Monitoring clinical trials often requires examining the interim findings to see if the sample size originally specified in the protocol will provide the required power against the null hypothesis when the alternative hypothesis is true, and to increase the sample size if necessary. This paper presents a new method, based on the overall response rate, for carrying out interim power evaluations when the observations have binomial distributions, without unblinding the treatment assignments or materially affecting the type I error rate. Simulation study results confirm the performance of the method.
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A. Lawrence Gould (Wed,) studied this question.
synapsesocial.com/papers/6a1f57b8e818a4c86e2aa53f — DOI: https://doi.org/10.1002/sim.4780110107
A. Lawrence Gould
Merck & Co., Inc., Rahway, NJ, USA (United States)
Statistics in Medicine
United States Military Academy
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