Statistical Methods for Dynamic Treatment Regimes Reinforcement Learning, Causal Inference, and Personalized Medicine /

• Κύριοι συγγραφείς: Chakraborty, Bibhas (Συγγραφέας), Moodie, Erica E.M (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2013.
• Σειρά: Statistics for Biology and Health,
• Θέματα: Statistics.; Health informatics.; Statistics for Life Sciences, Medicine, Health Sciences.; Statistics, general.; Health Informatics.

Statistical 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. This volume demonstrates these methods with their conceptual underpinnings and...

Πίνακας περιεχομένων:

• Introduction
• 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.