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Dynamic Treatment Regimes - Statistical Methods for Precision Medicine (Paperback)
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Dynamic Treatment Regimes - Statistical Methods for Precision Medicine (Paperback)
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Dynamic Treatment Regimes: Statistical Methods for Precision
Medicine provides a comprehensive introduction to statistical
methodology for the evaluation and discovery of dynamic treatment
regimes from data. Researchers and graduate students in statistics,
data science, and related quantitative disciplines with a
background in probability and statistical inference and popular
statistical modeling techniques will be prepared for further study
of this rapidly evolving field. A dynamic treatment regime is a set
of sequential decision rules, each corresponding to a key decision
point in a disease or disorder process, where each rule takes as
input patient information and returns the treatment option he or
she should receive. Thus, a treatment regime formalizes how a
clinician synthesizes patient information and selects treatments in
practice. Treatment regimes are of obvious relevance to precision
medicine, which involves tailoring treatment selection to patient
characteristics in an evidence-based way. Of critical importance to
precision medicine is estimation of an optimal treatment regime,
one that, if used to select treatments for the patient population,
would lead to the most beneficial outcome on average. Key methods
for estimation of an optimal treatment regime from data are
motivated and described in detail. A dedicated companion website
presents full accounts of application of the methods using a
comprehensive R package developed by the authors. The authors'
website www.dtr-book.com includes updates, corrections, new papers,
and links to useful websites.
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