Adaptive Treatment Strategies in Practice
(Sprache: Englisch)
The most up-to-date summary of current statistical research in personalized medicine, ideal for a broad audience of medical researchers.
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The most up-to-date summary of current statistical research in personalized medicine, ideal for a broad audience of medical researchers.
Inhaltsverzeichnis zu „Adaptive Treatment Strategies in Practice “
List of contributors; List of figures; Preface; 1. Introduction M. R. Kosorok and E. E. M. Moodie; Part I. Design of Trials for Estimating Dynamic Treatment Regimes: 2. DTRs and SMARTs: definitions, designs, and applications K. M. Kidwell; 3. Efficient design for clinically relevant intent-to-treat comparisons R. Dawson and P. W. Lavori; 4. SMART design, conduct, and analysis in oncology P. F. Thall; 5. Sample size calculations for clustered SMART designs P. Ghosh, Y. K. Cheung and B. Chakraborty; Part II. Practical Challenges in Dynamic Treatment Regime Analyses: 6. Analysis in the single-stage setting: an overview of estimation approaches for dynamic treatment regimes M. P. Wallace and E. E. M. Moodie; 7. G-estimation for dynamic treatment regimes in the longitudinal setting D. A. Stephens; 8. Outcome weighted learning methods for optimal dynamic treatment regimes Y. Q. Zhao; 9. Value search estimators for optimal dynamic treatment regimes M. Davidian, A. A. Tsiatis and E. B. Laber; 10. Evaluation of longitudinal dynamics with and without marginal structural working models M. Petersen, J. Schwab, E. Geng and M. J. van der Laan; 11. Imputation strategy for SMARTs S. M. Shortreed, E. B. Laber, J. Pineau and S. A. Murphy; 12. Clinical trials for personalized dose finding G. Chen and D. Zeng; 13. Methods for analyzing DTRs with censored survival data G. S. Johnson, A. Topp and A. S. Wahed; 14. Outcome weighted learning with a reject option M. Yuan; 15. Estimation of dynamic treatment regimes for complex outcomes: balancing benefits and risks K. A. Linn, E. B. Laber and L. A. Stefanski; 16. Practical reinforcement learning in dynamic treatment regimes R. D. Vincent, J. Pineau, N. Ybarra and I. El Naqa; 17. Reinforcement learning applications in clinical trials Y. F. Zhao; Bibliography; Index.
Bibliographische Angaben
- Autor: Michael R. Kosorok
- Maße: 17,7 x 25,6 cm, Kartoniert (TB), Englisch
- Verlag: Cambridge University Press
- ISBN-10: 1611974178
- ISBN-13: 9781611974171
- Erscheinungsdatum: 30.12.2015
Sprache:
Englisch
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