Description

Book Synopsis

Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer.

Features:

  • Describes the connection between causal analysis and statistical inference
  • Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichm

Bayesian Precision Medicine

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    £999.99

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    A Hardback by Peter F. Thall

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      View other formats and editions of Bayesian Precision Medicine by Peter F. Thall

      Publisher: CRC Press
      Publication Date: 5/7/2024
      ISBN13: 9781032754468, 978-1032754468
      ISBN10: 103275446X

      Description

      Book Synopsis

      Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer.

      Features:

      • Describes the connection between causal analysis and statistical inference
      • Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichm

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