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Point estimation, confidence intervals, and P-values for optimal adaptive two-stage designs with normal endpoints.
Meis, Jan; Pilz, Maximilian; Bokelmann, Björn; Herrmann, Carolin; Rauch, Geraldine; Kieser, Meinhard.
Afiliação
  • Meis J; Institute of Medical Biometry, University of Heidelberg, Heidelberg, Germany.
  • Pilz M; Institute of Medical Biometry, University of Heidelberg, Heidelberg, Germany.
  • Bokelmann B; Institute of Biometry and Clinical Epidemiology, Charité- Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Herrmann C; Institute of Biometry and Clinical Epidemiology, Charité- Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Rauch G; Institute of Biometry and Clinical Epidemiology, Charité- Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Kieser M; Technische Universität Berlin, Berlin, Germany.
Stat Med ; 43(8): 1577-1603, 2024 Apr 15.
Article em En | MEDLINE | ID: mdl-38339872
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article