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Group sequential and confirmatory ad...
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Wassmer, Gernot.
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Group sequential and confirmatory adaptive designs in clinical trials
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Group sequential and confirmatory adaptive designs in clinical trials / by Gernot Wassmer, Werner Brannath.
作者:
Wassmer, Gernot.
其他作者:
Brannath, Werner.
出版者:
Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:
xxiii, 410 p. :ill., digital ;24 cm.
內容註:
Part I Group Sequential Designs -- Repeated Significance Tests Procedures with Equally Sized Stages -- Procedures with Unequally Sized Stages -- Confidence Intervals, p -Values, and Point Estimation -- Applications -- Part II Adaptive Confirmatory Designs with a Single Hypothesis: Adaptive Group Sequential Tests -- Decision Tools for Adaptive Designs -- Estimation and p-Values for Two-stage Adaptive Designs -- Adaptive Designs with Survival Data -- Part III Adaptive Designs with Multiple Hypotheses: Multiple Testing in Adaptive Designs -- Applications and Case Studies -- Appendix - Software for Adaptive Designs -- Index.
Contained By:
Springer Nature eBook
標題:
Clinical trials. -
電子資源:
https://doi.org/10.1007/978-3-031-89669-9
ISBN:
9783031896699
Group sequential and confirmatory adaptive designs in clinical trials
Wassmer, Gernot.
Group sequential and confirmatory adaptive designs in clinical trials
[electronic resource] /by Gernot Wassmer, Werner Brannath. - Second edition. - Cham :Springer Nature Switzerland :2025. - xxiii, 410 p. :ill., digital ;24 cm. - Springer series in pharmaceutical statistics,2366-8709. - Springer series in pharmaceutical statistics..
Part I Group Sequential Designs -- Repeated Significance Tests Procedures with Equally Sized Stages -- Procedures with Unequally Sized Stages -- Confidence Intervals, p -Values, and Point Estimation -- Applications -- Part II Adaptive Confirmatory Designs with a Single Hypothesis: Adaptive Group Sequential Tests -- Decision Tools for Adaptive Designs -- Estimation and p-Values for Two-stage Adaptive Designs -- Adaptive Designs with Survival Data -- Part III Adaptive Designs with Multiple Hypotheses: Multiple Testing in Adaptive Designs -- Applications and Case Studies -- Appendix - Software for Adaptive Designs -- Index.
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.
ISBN: 9783031896699
Standard No.: 10.1007/978-3-031-89669-9doiSubjects--Topical Terms:
724498
Clinical trials.
LC Class. No.: R853.C55 / W37 2025
Dewey Class. No.: 615.50724
Group sequential and confirmatory adaptive designs in clinical trials
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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.
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