Bayesian Approaches in Oncology Using R and OpenBUGS — 1st Edition

📘 Bayesian Approaches in Oncology Using R and OpenBUGS — 1st Edition

🔎 Book Overview and Topics

A statistical methods reference devoted to Bayesian modeling in cancer-related research, illustrated through workflows that use R and OpenBUGS.

Topics and Research Coverage

• Bayesian probability, prior distributions and posterior inference.
• Model assumptions and interpretation of uncertainty.
• Markov chain Monte Carlo methods and computation.
• Clinical trial design and sample-size considerations.
• Survival or outcome modeling in oncology research.
• Software workflow, diagnostic checks and model validation.
• Reporting statistical findings to clinical collaborators.

Study Perspective

Software-based examples are intended to develop statistical understanding. Reproducing a published example may require compatible software versions, datasets and computational setup, none of which are automatically included with a PDF.

Who Will Find It Useful?

Biostatisticians, clinical trial methodologists, oncology researchers and graduate students in quantitative health science.

PDF eBook Details

Language: English. Format: Digital PDF reference. This WordPress product is an unpublished draft with one PDF link configured. The edition and complete contents of the linked file still need checking; printed materials, equipment, certificates and standalone online services are not included.

Publisher’s Edition Reference

Author: Atanu Bhattacharjee.
Publisher: Chapman & Hall / CRC Press.
Edition: First (2021).
eBook ISBN: 9780429329449.

These details identify the published edition represented by the cover. The website’s linked PDF should still be checked against the publisher’s edition before publication.

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Read the detailed coverage and bibliographic information above to decide whether this book is a useful reference for your professional or academic work.

📚 Digital edition: This draft remains unavailable for purchase until the matching PDF and edition are verified.