This book will use the new guidance as a framework for developing and implementing comprehensive analysis plans for clinical trials that support the development and approval of medical interventions.

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