Estimands, Estimators and Sensitivity Analysis in Clinical Trials

Section I Setting the Stage
1. Introduction
2. Why Are Estimands Important?
Section II Estimands
3. Estimands and How to Define Them
4. Strategies for Dealing with Intercurrent Events
5. Examples from Actual Clinical Trials in Choosing and
Specifying Estimands
6. Causal Inference and Estimands
7. Putting the Principles into Practice
Section III Estimators and Sensitivity
8. Overview of Estimators
9. Modeling Considerations
10. Overview of Analyses for Composite Intercurrent Event
Strategies
11. Overview of Analyses for Hypothetical Intercurrent Event
Strategies
12. Overview of Analyses for Principal Stratification Intercurrent
Event Strategies
13. Overview of Analyses for While-on-Treatment
Intercurrent Event Strategies
14. Overview of Analyses for Treatment Policy Intercurrent
Event Strategies
15. Missing Data
16. Sensitivity Analyses
Section IV Technical Details on Selected Analyses
17. Example Data
18. Direct Maximum Likelihood
19. Multiple Imputation
20. Inverse Probability Weighted Generalized Estimated
Equations
21. Doubly Robust Methods
22. Reference-Based Imputation
23. Delta Adjustment
24. Overview of Principal Stratification Methods
Section V Case Studies: Detailed Analytic Examples
25. Analytic Case Study of Depression Clinical Trials
26. Analytic Case Study Based on the ACTG 175 HIV Trial