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.
