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Adaptive Design Theory and Implementation Using SAS and R
Contributor(s): Chang, Mark (Author)
ISBN: 1482256592     ISBN-13: 9781482256598
Publisher: CRC Press
OUR PRICE:   $190.00  
Product Type: Hardcover - Other Formats
Published: December 2014
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Additional Information
BISAC Categories:
- Mathematics | Probability & Statistics - General
- Medical | Pharmacology
- Medical | Biostatistics
Dewey: 610.72
Series: Chapman & Hall/CRC Biostatistics
Physical Information: 1.4" H x 6.2" W x 9.3" (2.46 lbs) 706 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

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.