Clinical Trial Design: Bayesian and Frequentist Adaptive Methods [Format Kindle] Author: Guosheng Yin | Language: English | ISBN:
B00DAB1F8W | Format: PDF, EPUB
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Revue de presse
“In summary, this book is useful for anyone interested in design and analysis of clinical studies. The main strengths of this book are the well–balanced approach between statistical theories and statistical analysis methods of the design issues involved in clinical trials. I would suggest the usage of this book as a Master’s level course in biostatistics.” ( Journal of Biopharmaceutical Statistics , 1 May 2013) “The author should be commended; the text is well written and packed with information that belies the book’s trim size." ( Drug Information Journal , 30 October 2012) “The book accompanied with software developed at MD Anderson Cancer Center provides an excellent reference for everyone who works in clinical trial field.” ( Biometrics , 1 July 2012)
Présentation de l'éditeur
A balanced treatment of the theories, methodologies, and design issues involved in clinical trials using statistical methodsThere has been enormous interest and development in Bayesian adaptive designs, especially for early phases of clinical trials. However, for phase III trials, frequentist methods still play a dominant role through controlling type I and type II errors in the hypothesis testing framework. From practical perspectives, Clinical Trial Design: Bayesian and Frequentist Adaptive Methods provides comprehensive coverage of both Bayesian and frequentist approaches to all phases of clinical trial design. Before underpinning various adaptive methods, the book establishes an overview of the fundamentals of clinical trials as well as a comparison of Bayesian and frequentist statistics.
Recognizing that clinical trial design is one of the most important and useful skills in the pharmaceutical industry, this book provides detailed discussions on a variety of statistical designs, their properties, and operating characteristics for phase I, II, and III clinical trials as well as an introduction to phase IV trials. Many practical issues and challenges arising in clinical trials are addressed. Additional topics of coverage include:
Risk and benefit analysis for toxicity and efficacy trade-offs
Bayesian predictive probability trial monitoring
Bayesian adaptive randomization
Late onset toxicity and response
Dose finding in drug combination trials
Targeted therapy designs
The author utilizes cutting-edge clinical trial designs and statistical methods that have been employed at the world's leading medical centers as well as in the pharmaceutical industry. The software used throughout the book is freely available on the book's related website, equipping readers with the necessary tools for designing clinical trials.
Clinical Trial Design is an excellent book for courses on the topic at the graduate level. The book also serves as a valuable reference for statisticians and biostatisticians in the pharmaceutical industry as well as for researchers and practitioners who design, conduct, and monitor clinical trials in their everyday work.
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