Sequential Experimentation in Clinical Trials: Design and Analysis is
developed from decades of work in research groups, statistical pedagogy,
and workshop participation. Different parts of the book can be used for
short courses on clinical trials, translational medical research, and
sequential experimentation. The authors have successfully used the book
to teach innovative clinical trial designs and statistical methods for
Statistics Ph.D. students at Stanford University. There are additional
online supplements for the book that include chapter-specific exercises
and information.
Sequential Experimentation in Clinical Trials: Design and Analysis
covers the much broader subject of sequential experimentation that
includes group sequential and adaptive designs of Phase II and III
clinical trials, which have attracted much attention in the past three
decades. In particular, the broad scope of design and analysis problems
in sequential experimentation clearly requires a wide range of
statistical methods and models from nonlinear regression analysis,
experimental design, dynamic programming, survival analysis, resampling,
and likelihood and Bayesian inference. The background material in these
building blocks is summarized in Chapter 2 and Chapter 3 and certain
sections in Chapter 6 and Chapter 7. Besides group sequential tests and
adaptive designs, the book also introduces sequential change-point
detection methods in Chapter 5 in connection with pharmacovigilance and
public health surveillance. Together with dynamic programming and
approximate dynamic programming in Chapter 3, the book therefore covers
all basic topics for a graduate course in sequential analysis designs.
