On sample size and inference for two-stage adaptive designs |
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Authors: | Liu Q Chi G Y |
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Affiliation: | Clinical Biostatistics, Cephalon, Inc., West Chester, Pennsylvania 19380, USA. qliu@worldnet.att.net |
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Abstract: | Proschan and Hunsberger (1995, Biometrics 51, 1315-1324) proposed a two-stage adaptive design that maintains the Type I error rate. For practical applications, a two-stage adaptive design is also required to achieve a desired statistical power while limiting the maximum overall sample size. In our proposal, a two-stage adaptive design is comprised of a main stage and an extension stage, where the main stage has sufficient power to reject the null under the anticipated effect size and the extension stage allows increasing the sample size in case the true effect size is smaller than anticipated. For statistical inference, methods for obtaining the overall adjusted p-value, point estimate and confidence intervals are developed. An exact two-stage test procedure is also outlined for robust inference. |
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Keywords: | Adaptive design Adjusted confidence intervals Adjusted p-value Conditional error Exact inference Fisher's combination test Point estimate Sample size adjustment Type I error rate |
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