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Methods and Applications of Sample Size Calculation and Recalculation in Clinical Trials (Paperback, 1st ed. 2020)
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Methods and Applications of Sample Size Calculation and Recalculation in Clinical Trials (Paperback, 1st ed. 2020)
Series: Springer Series in Pharmaceutical Statistics
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This book provides an extensive overview of the principles and
methods of sample size calculation and recalculation in clinical
trials. Appropriate calculation of the required sample size is
crucial for the success of clinical trials. At the same time, a
sample size that is too small or too large is problematic due to
ethical, scientific, and economic reasons. Therefore, state-of-the
art methods are required when planning clinical trials. Part I
describes a general framework for deriving sample size calculation
procedures. This enables an understanding of the common principles
underlying the numerous methods presented in the following
chapters. Part II addresses the fixed sample size design, where the
required sample size is determined in the planning stage and is not
changed afterwards. It covers sample size calculation methods for
superiority, non-inferiority, and equivalence trials, as well as
comparisons between two and more than two groups. A wide range of
further topics is discussed, including sample size calculation for
multiple comparisons, safety assessment, and multi-regional trials.
There is often some uncertainty about the assumptions to be made
when calculating the sample size upfront. Part III presents methods
that allow to modify the initially specified sample size based on
new information that becomes available during the ongoing trial.
Blinded sample size recalculation procedures for internal pilot
study designs are considered, as well as methods for sample size
reassessment in adaptive designs that use unblinded data from
interim analyses. The application is illustrated using numerous
clinical trial examples, and software code implementing the methods
is provided. The book offers theoretical background and practical
advice for biostatisticians and clinicians from the pharmaceutical
industry and academia who are involved in clinical trials. Covering
basic as well as more advanced and recently developed methods, it
is suitable for beginners, experienced applied statisticians, and
practitioners. To gain maximum benefit, readers should be familiar
with introductory statistics. The content of this book has been
successfully used for courses on the topic.
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