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Statistical Methods for Dynamic Treatment Regimes Reinforcement Learning, Causal Inference, and Personalized Medicine /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
|
| Edición: | 1st ed. 2013. |
| Colección: | Statistics for Biology and Health,
76 |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.