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Estimands, Estimators and Sensitivity Analysis in Clinical Trials

By: (Author) Bohdana Ratitch , (Author) Craig Mallinckrodt , (Author) Geert Molenberghs , (Author) Ilya Lipkovich

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Ksh 20,700.00

Format: Hardback or Cased Book

ISBN-10: 1138592501

ISBN-13: 9781138592506

Series: Chapman & Hall/CRC Biostatistics Series

Publisher: Taylor & Francis Ltd

Imprint: CRC Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Feb 10th, 2020

Print length: 318 Pages

Weight: 660 grams

Dimensions (height x width x thickness): 24.00 x 16.10 x 2.50 cms

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  • Description

  • Reviews

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.

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, real-world examples, and 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 among clinicians, statisticians, and regulators when it comes to communicating decision-making objectives, assumptions, and interpretations of evidence.

This book lays out a path toward bridging some of these gaps. It offers

A common language and unifying framework along with the technical details and practical guidance to help statisticians meet the challenges

A thorough treatment of intercurrent events (ICEs), i.e., postrandomization events that confound interpretation of outcomes and five strategies for ICEs in ICH E9 (R1)

Details on how estimands, integrated into a principled study development process, lay a foundation for coherent specification of trial design, conduct, and analysis needed to overcome the issues caused by ICEs:

A perspective on the role of the intention-to-treat principle

Examples and case studies from various areas

Example code in SAS and R

A connection with causal inference

Implications and methods for analysis of longitudinal trials with missing data

Together, the authors have offered the readers their ample expertise in clinical trial design and analysis, from an industrial and academic perspective.


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