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This book provides an up-to-date review of the general principles and techniques of confirmatory adaptive designs, a generalization of group sequential designs. With these designs, interim analyses are performed in order to stop a trial prematurely under control of the Type I error rate. In adaptive designs, it is also permissible to perform a data-driven change of relevant aspects of the study design at interim stages. This includes, for example, a sample-size reassessment, a treatment-arm selection, or a selection of a pre-specified sub-population.
First introduced in the 1990s, this popular adaptive methodology has become the focus of intense discussion and is still a rapidly growing field of statistical research. The book describes adaptive design methodology at an elementary level, while also considering design and planning issues. It also looks at methods for analyzing an adaptively planned trial, such as estimation methods and methods for determining an overall p-value. Part I provides the group sequential preliminaries required to understand and apply the adaptive design methodology supplied in Parts II and III. Many examples are included that illustrate the practical applications of the techniques. An overview of recent developments is given and, new to this edition, detailed descriptions of the R commands used for the calculations are provided. The R package rpact, which is available on CRAN, allows for the recalculation of most tables and results presented in the monograph. The required knowledge of R has been kept to a minimum, and an online Shiny app has been made available for rpact.
Primarily written for applied statisticians from academia and industry who are interested in confirmatory adaptive designs, the text is also suitable for an advanced statistical course for applied statisticians or clinicians with a sound statistical background.