Description
Book SynopsisStatistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine.
Trade ReviewFrom the reviews:
"Overall, the book provides an excellent reviewof DTRs up to date. After finishing reading the book, I planned to create a post-graduate seminar course on this topic using this book as a textbook. I enthusiastically recommend this book. This book will be a valuable reference for anyone interested and involved in research on personalized medicine." (Hyonggin An, Journal of Agricultural, Biological, and Environmental Statistics, April, 2015)
“The intended audience includes physicians, clinical researchers, physicians in training, statisticians, and medical students, as well as master’s and doctoral students in the field of biostatistics and epidemiology and computer scientists. … This book provides a concise summary of the key findings in the statistical literature of dynamic treatment regimes. … The simple language and well-organized chapters are unsurpassed attributes of this book. It will be an exceptional resource for quick review.” (Parthiv Amin, Doody’s Book Reviews, November, 2013)
Table of ContentsIntroduction.- The Data: Observational Studies and Sequentially Randomized Trials.- Statistical Reinforcement Learning.- Estimation of Optimal DTRs by Modeling Contrasts of Conditional Mean Outcomes.- Estimation of Optimal DTRs by Directly Modeling Regimes.- G-computation: Parametric Estimation of Optimal DTRs.- Estimation DTRs for Alternative Outcome Types.- Inference and Non-regularity.- Additional Considerations and Final Thoughts.- Glossary.- Index.- References.
