Preface
Part1: Study Design For Precision Medicine
1. Adaptive Designs for Precision Medicine: Fundamental Statistical Considerations
2. Small Sample, Sequential, Multiple Assignment, Randomized Trial Design and Analysis
3. Sequential Multiple Assignment Randomized Trial with Adaptive Randomization (SMART-AR) for Mobile Health Devices
4. Bayesian Dose-Finding in Two Treatment Cycles based on Efficacy and Toxicity
5. Agent-Based Modeling in Medical Research ? Example in Health Economics
6. Thompson Sampling for mHealth and Precision Health Applications
Part2: Estimation of Optimal Treatment Strategies
7. Constructing and Evaluating Optimal Treatment Sequences: An Introductory Guide for Bayesians
8. Measurement Error in Adaptive Treatment Strategies
9. Nonparametric Heterogeneous Treatment Effect Estimation in Repeated Cross Sectional Designs
10. Semiparametric Doubly Robust Targeted Double Machine Learning: A Review
11. Adversarial Monte Carlo Meta-Learning of Conditional Average Treatment Effects
12. Personalized Policy Learning
13. Bandit Algorithms for Precision Medicine
Part3: Precision Medicine in High Dimensions
14. Tailoring Variable Selection and Ranking for Optimal Treatment Decisions
15. Selecting Optimal Subgroups for Treatment Using Many Covariates
16. Statistical Learning Methods for Estimating Optimal Individualized Treatment Rules from Observational Data
17. Polygenic Risk Prediction for Precision Prevention
18. Post-Selection Inference for Individualized Treatment Rules with Nonparametric Confounding Control Bibliography