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Point estimation, confidence intervals, and P-values for optimal adaptive two-stage designs with normal endpoints

Due to the dependency structure in the sampling process, adaptive trial designs create challenges in point and interval estimation and in the calculation of P-values. Optimal adaptive designs, which are designs where the parameters governing the adaptivity are chosen to maximize some performance cri...

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Bibliographic Details
Main Authors: Meis, Jan (Author) , Pilz, Maximilian (Author) , Bokelmann, Björn (Author) , Herrmann, Carolin (Author) , Rauch, Geraldine (Author) , Kieser, Meinhard (Author)
Format: Article (Journal)
Language:English
Published: 15 April 2024
In: Statistics in medicine
Year: 2024, Volume: 43, Issue: 8, Pages: 1577-1603
ISSN:1097-0258
DOI:10.1002/sim.10020
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1002/sim.10020
Verlag, kostenfrei, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.10020
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Author Notes:Jan Meis, Maximilian Pilz, Björn Bokelmann, Carolin Herrmann, Geraldine Rauch, Meinhard Kieser
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Summary:Due to the dependency structure in the sampling process, adaptive trial designs create challenges in point and interval estimation and in the calculation of P-values. Optimal adaptive designs, which are designs where the parameters governing the adaptivity are chosen to maximize some performance criterion, suffer from the same problem. Various analysis methods which are able to handle this dependency structure have already been developed. In this work, we aim to give a comprehensive summary of these methods and show how they can be applied to the class of designs with planned adaptivity, of which optimal adaptive designs are an important member. The defining feature of these kinds of designs is that the adaptive elements are completely prespecified. This allows for explicit descriptions of the calculations involved, which makes it possible to evaluate different methods in a fast and accurate manner. We will explain how to do so, and present an extensive comparison of the performance characteristics of various estimators between an optimal adaptive design and its group-sequential counterpart.
Item Description:Veröffentlicht: 10. Februar 2024
Gesehen am 18.06.2024
Physical Description:Online Resource
ISSN:1097-0258
DOI:10.1002/sim.10020

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