Description
Book Synopsis: 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.
Details
Are you interested in precision medicine and discovering treatment options that are tailored to individual patient characteristics? Look no further - Dynamic Treatment Regimes: Statistical Methods for Precision Medicine is the comprehensive guide you've been waiting for. Whether you're a researcher or a graduate student in statistics or data science, this book will equip you with the necessary tools to evaluate and discover dynamic treatment regimes from data.
With a background in probability and statistical inference, you'll dive into popular statistical modeling techniques that will enable you to make evidence-based decisions in the field of precision medicine. A dynamic treatment regime consists of sequential decision rules that guide clinicians in selecting the most suitable treatment option for each patient. By synthesizing patient information and considering key decision points in disease processes, treatment regimes ensure personalized care.
Precision medicine demands the estimation of optimal treatment regimes, ones that lead to the most beneficial outcomes for the patient population. In Dynamic Treatment Regimes, you'll explore key methods for estimating these optimal regimes from data. The authors provide detailed explanations and motivation for each method, empowering you to apply them effectively.
Ready to put theory into practice? Visit the authors' companion website at www.dtr-book.com to gain access to a comprehensive R package specifically designed for the application of these methods. The website also offers updates, corrections, new papers, and valuable website links to keep you informed and engaged.
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