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Adaptive Design Theory and Implementation Using SAS and R, Second Edition [Paperback]

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  • Category: Books (Mathematics)
  • Author:  Chang, Mark
  • Author:  Chang, Mark
  • ISBN-10:  1138034231
  • ISBN-10:  1138034231
  • ISBN-13:  9781138034235
  • ISBN-13:  9781138034235
  • Publisher:  Chapman and Hall/CRC
  • Publisher:  Chapman and Hall/CRC
  • Pages:  706
  • Pages:  706
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Jun-2016
  • Pub Date:  01-Jun-2016
  • SKU:  1138034231-11-MPOD
  • SKU:  1138034231-11-MPOD
  • Item ID: 101233631
  • Seller: ShopSpell
  • Ships in: 2 business days
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  • Delivery by: Jun 30 to Jul 02
  • Notes: Brand New Book. Order Now.

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 Editionoffers 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.

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 Datalƒ*

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