Bayesian Thinking in Biostatistics (eBook, ePUB)

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With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research.

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"This thoroughly modern Bayesian book by leaders in developing and applying Bayesian methods is a "must have" as a textbook or a reference volume. Rosner, Laud and Johnson make the case for Bayesian approaches by melding clear exposition on methodology with serious attention to a broad array of illuminating applications. These are activated by excellent coverage of computing methods and provision of code. Their content on model assessment, robustness, data-analytic approaches and predictive assessments (these pioneered by Seymour Geisser) are essential to valid practice. The numerous exercises and professional advice make the book ideal as a text for an intermediate-level course for aspiring statisticians, domain scientists and policy