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Adaptive Design Theory And Implementation Using Sas And R Second Edition 2nd Edition Mark Chang

  • SKU: BELL-4940064
Adaptive Design Theory And Implementation Using Sas And R Second Edition 2nd Edition Mark Chang
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Adaptive Design Theory And Implementation Using Sas And R Second Edition 2nd Edition Mark Chang instant download after payment.

Publisher: Chapman and Hall/CRC
File Extension: PDF
File size: 4.02 MB
Pages: 706
Author: Mark Chang
ISBN: 9781482256598, 1482256592
Language: English
Year: 2014
Edition: 2

Product desciption

Adaptive Design Theory And Implementation Using Sas And R Second Edition 2nd Edition Mark Chang by Mark Chang 9781482256598, 1482256592 instant download after payment.

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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