Abstract
If the prior experience with the study treatments is insufficient for a persistent pre-specification of relevant and realistic treatment effects, the effect and corresponding sample sizes may be reassessed at an interim analysis from unblinded interim data. In this case designs are required that guarantee Type I error rate control. Bauer (Biometrie und Informatik in Medizin und Biologie 20:130–148, 1989) and Bauer and Köhne (Biometrics 50:1029–1041, 1994), on the one hand, and Proschan and Hunsberger (Biometrics 51:1315–1324, 1995), on the other hand, have independently suggested designs that control Type I error rates after such data driven types of sample size adjustments. This chapter is devoted to adaptive designs as suggested by these pioneering papers as well as newer developments including the CRP principle due to Müller and Schäfer (Biometrics 57:886–891, 2001). We will focus in this chapter on two-stage adaptive designs with an adaptation of the sample size, although the method allows for other types of adaptations such as changing test statistics or changing hypotheses, as well as for the multi-stage generalization.
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Wassmer, G., Brannath, W. (2016). Adaptive Group Sequential Tests. In: Group Sequential and Confirmatory Adaptive Designs in Clinical Trials. Springer Series in Pharmaceutical Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-32562-0_6
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