Dynamic Treatment Regimes

Dynamic Treatment Regimes

EnglishEbook
Tsiatis, Anastasios A.
Taylor & Francis Ltd
EAN: 9780429532221
Available online
CZK 1,504
Common price CZK 1,671
Discount 10%
pc

Detailed information

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.

EAN 9780429532221
ISBN 0429532229
Binding Ebook
Publisher Taylor & Francis Ltd
Publication date December 19, 2019
Pages 618
Language English
Country United Kingdom
Authors Davidian, Marie (North Carolina State University, Raleigh, USA); Holloway, Shannon T. (North Carolina State University, Raleigh, USA); Laber, Eric B; Tsiatis, Anastasios A.