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Design and Analysis of Clinical Trials: Concepts and Methodologies

  • ISBN 9780470887653
  • Author: Chow, Shein-Chung
  • Publ Date: 2014-01-03
  • Edition: 3
  • Binding: Hardback

$247.83
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Praise for the Second Edition:

"...a grand feast for biostatisticians. It stands ready to satisfy the appetite of any pharmaceutical scientist with a respectable statistical appetite." -Journal of Clinical Research Best Practices

The Third Edition of Design and Analysis of Clinical Trials provides complete, comprehensive, and expanded coverage of recent health treatments and interventions. Featuring a unified presentation, the book provides a well-balanced summary of current regulatory requirements and recently developed statistical methods as well as an overview of the various designs and analyses that are utilized at different stages of clinical research and development. Additional features of this Third Edition include:

* New chapters on biomarker development and target clinical trials, adaptive design, trials for evaluating diagnostic devices, statistical methods for translational medicine, and traditional Chinese medicine

* A balanced overview of current and emerging clinical issues as well as newly developed statistical methodologies

* Practical examples of clinical trials that demonstrate everyday applicability, with illustrations and examples to explain key concepts

* New sections on bridging studies and global trials, QT studies, multinational trials, comparative effectiveness trials, and the analysis of QT/QTc prolongation

* A complete and balanced presentation of clinical and scientific issues, statistical concepts, and methodologies for bridging clinical and statistical disciplines

* An update of each chapter that reflects changes in regulatory requirements for the drug review and approval process and recent developments in statistical design and methodology for clinical research and development

Design and Analysis of Clinical Trials, Third Edition continues to be an ideal clinical research reference for academic, pharmaceutical, medical, and regulatory scientists/researchers, statisticians, and graduate-level students.
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