Abstract
Planning and conducting interim analysis are important steps for long-term clinical trials. In this article, the concept of conditional power is combined with the classic analysis of variance (ANOVA) for a study of two-stage sample size re-estimation based on interim analysis. The overall Type I and Type II errors would be inflated by interim analysis. We compared the effects on re-estimating sample sizes with and without the adjustment of Type I and Type II error rates due to interim analysis.
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