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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.
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.
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