Craig Mallinckrodt, Geert Molenberghs, Ilya Lipkovich, Bohdana Ratitch
Chapman and Hall/CRC
December 23, 2019 Forthcoming
Reference - 312 Pages - 20 B/W Illustrations
ISBN 9781138592506 - CAT# K386970
Series: Chapman & Hall/CRC Biostatistics Series
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The concepts of estimands, analyses (estimators) and sensitivity are interrelated. Therefore, great need exists for an integrated approach to these topics. This book acts as a practical guide to developing and implementing statistical analysis plans by explaining fundamental concepts using accessible language; providing technical details; providing real world examples and providing SAS and R code to implement analyses. The updated ICH guideline raises new analytic and cross-functional challenges for statisticians. Gaps between different communities have come to surface, such as between causal inference and clinical trialists, as well as between clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence.
This book lays out a path towards bridging some of these gaps. It offers:
Jointly, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial as well as academic perspective.
Part 1: Setting the Stage. 1. Introduction. 2. A Real World View of Why Estimands are Important. Part 2: Estimands. 3. Estimands: Overview and Concepts. 4. Choosing Estimands in Clinical Trials. 5. Dealing with Inter-Current events. 6. The Estimand Decision Tree. 7. Case Studies: Real World Examples in Choosing Estimands. Part 3: Estimators. 8. Analysis Framework for Dealing with Inter-Current Events. 9. Estimators for Composite Approaches. 10. Introduction to Hypothetical Approaches for De-Jure Estimands. 11. Likelihood Based Methods. 12. Multiple Imputation. 13. Introduction to Hypothetical Approaches for De Facto Estimors. 14. Model-based Approaches to MNAR. 15. Multiple Imputation Based Approaches for Controlled Imputation. 16. Likelihood Based Approaches for Controlled Imputation. 17. Approaches for Categorical Repeated Measures. 18. Approaches to Time-to-Event Endpoints. 19. Principal Stratification Approaches. Part 4: Sensitivity Analysis. 20. Basic Ideas and Concepts. 21. Sensitivity for Composite Approaches. 22. Sensitivity for Hypothetical Approaches. 23. Sensitivity for Time to Event Endpoints. 24. Sensitivity for Principal Stratification Approaches.