Targeted Learning in Data Science Causal Inference for Complex Longitudinal Studies /

• Κύριοι συγγραφείς: van der Laan, Mark J. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Rose, Sherri (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Springer Series in Statistics,
• Θέματα: Statistics .; Big data.; Biostatistics.; Biomedical engineering.; Public health.; Statistical Theory and Methods.; Big Data/Analytics.; Statistics for Life Sciences, Medicine, Health Sciences.; Biomedical Engineering/Biotechnology.; Public Health.

This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by usin...

Πίνακας περιεχομένων:

• Abbreviations and Notation
• Philosophy of Targeted Learning in Data Science
• Part I: Introductory Chapters
• 1. The Statistical Estimation Problem in Complex Longitudinal Big Data
• 2. Longitudinal Causal Models
• 3. Super Learner for Longitudinal Problems
• 4. Longitudinal Targeted Maximum Likelihood Estimation (LTMLE)
• 5. Understanding LTMLE
• 6. Why LTMLE?
• Part II:Additional Core Topics
• 7. One-Step TMLE
• IV: Observational Longitudinal Data
• 19. Super Learning in the ICU
• 20. Stochastic Single-Time-Point Interventions
• 21. Stochastic Multiple-Time-Point Interventions on Monitoring and Treatment
• 22. Collaborative LTMLE
• Part V: Optimal Dynamic Regimes
• 23. Targeted Adaptive Designs Learning the Optimal Dynamic Treatment
• 24. Targeted Learning of the Optimal Dynamic Treatment
• 25. Optimal Dynamic Treatments under Resource Constraints
• Part VI: Computing
• 26. ltmle() for R
• 27. Scaled Super Learner for R
• 28. Scaling CTMLE for Julia
• Part VII: Special Topics.-29. Data-Adaptive Target Parameters
• 30. Double Robust Inference for LTMLE
• 31. Higher-Order TMLE
• Appendix
• A. Online Targeted Learning Theory
• B. Computerization of the calculation of efficient influence curve
• C. TMLE applied to Capture/Recapture
• D. TMLE for High Dimensional Linear Regression
• E. TMLE of Causal Effect Based on Observing a Single Time Series.