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Bayesian approaches in oncology using R and OpenBUGS. (English) Zbl 1453.62004

Boca Raton, FL: CRC Press (ISBN 978-0-367-35050-5/hbk; 978-0-429-32944-9/ebook). xv, 243 p. (2021).
Publisher’s description: The book serves two audiences: those who are familiar with the theory and applications of Bayesian approach and wish to learn or enhance their skills in R and OpenBUGS, and those who are enrolled in R and OpenBUGS-based course for Bayesian approach implementation. For those who have never used R/OpenBUGS, the book begins with a self-contained introduction to R that lays the foundation for later chapters.
Many books on the Bayesian approach and the statistical analysis are advanced, and many are theoretical. While most of them do cover the objective, the fact remains that data analysis can not be performed without actually doing it, and this means using dedicated statistical software. There are several software packages, all with their specific objective. Finally, all packages are free to use, are versatile with problem-solving, and are interactive with R and OpenBUGS.
This book continues to cover a range of techniques related to oncology that grow in statistical analysis. It intended to make a single source of information on Bayesian statistical methodology for oncology research to cover several dimensions of statistical analysis. The book explains data analysis using real examples and includes all the R and OpenBUGS codes necessary to reproduce the analyses. The idea is to overall extending the Bayesian approach in oncology practice. It presents four sections to the statistical application framework:
Bayesian in clinical research and sample size calcuation
Bayesian in time-to-event data analysis
Bayesian in longitudinal data analysis
Bayesian in diagnostics test statistics

This book is intended as a first course in Bayesian biostatistics for oncology students. An oncologist can find useful guidance for implementing Bayesian in research work. It serves as a practical guide and an excellent resource for learning the theory and practice of Bayesian methods for the applied statistician, biostatistician, and data scientist.

MSC:

62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62P10 Applications of statistics to biology and medical sciences; meta analysis
62F15 Bayesian inference
62-04 Software, source code, etc. for problems pertaining to statistics
92C50 Medical applications (general)
92C40 Biochemistry, molecular biology
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