Chang | Adaptive Design Theory and Implementation Using SAS and R | Buch | 978-1-138-03423-5 | sack.de

Buch, Englisch, 706 Seiten, Format (B × H): 156 mm x 235 mm, Gewicht: 975 g

Reihe: Chapman & Hall/CRC Biostatistics Series

Chang

Adaptive Design Theory and Implementation Using SAS and R

Buch, Englisch, 706 Seiten, Format (B × H): 156 mm x 235 mm, Gewicht: 975 g

Reihe: Chapman & Hall/CRC Biostatistics Series

ISBN: 978-1-138-03423-5
Verlag: CRC Press


Get Up to Speed on Many Types of Adaptive Designs

Since the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials.

New to the Second Edition

- Twelve new chapters covering blinded and semi-blinded sample size reestimation design, pick-the-winners design, biomarker-informed adaptive design, Bayesian designs, adaptive multiregional trial design, SAS and R for group sequential design, and much more

- More analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switching

- New material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trials

- Twenty new SAS macros and R functions

- Enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials

Covering even more adaptive designs, this book provides biostatisticians, clinical scientists, and regulatory reviewers with up-to-date details on this innovative area in pharmaceutical research and development. Practitioners will be able to improve the efficiency of their trial design, thereby reducing the time and cost of drug development.
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Zielgruppe


Professional Practice & Development


Autoren/Hrsg.


Weitere Infos & Material


Introduction. Classic Design. Theory of Hypothesis-Based Adaptive Design. Method with Direct Combination of P-Values. Method with Inverse-Normal P-Values. Adaptive Non-Inferiority Design with Paired Binary Data. Trial Design and Analysis with Incomplete Paired Data. Implementation of N-Stage Adaptive Designs. Conditional Error Function Method and Conditional Power. Recursive Adaptive Design. Unblinded Sample-Size Re-Estimation Design. Blinded Sample Size Re-Estimation. Adaptive Design with Co-Primary Endpoint. Multiple-Endpoint Adaptive Design. Pick-the-Winners Design. The Add-Arms Design for Unimodal Response. Biomarker-Adaptive Design. Biomarker-Informed Adaptive Design. Survival Modeling and Adaptive Treatment Switching. Response-Adaptive Allocation Design. Bayecian Adaptive Dose Finding Design. Bayesian Phase I-II Adaptive Design. Adaptive Design for Biosimilarity Trial. Multi-Regional Adaptive Trial Design. Bayesian Adaptive Design. Planning, Execution, Analysis, and Reporting. Data Analysis of Adaptive Design. Debates in Adaptive Designs. SAS Adaptive Design Modules: SEQDESIGN Procedure. Appendices. Bibliography. Index.



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