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Books > Professional & Technical > Industrial chemistry & manufacturing technologies > Industrial chemistry > Pharmaceutical technology
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Multiple Testing Problems in Pharmaceutical Statistics (Paperback)
Loot Price: R1,507
Discovery Miles 15 070
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Multiple Testing Problems in Pharmaceutical Statistics (Paperback)
Series: Chapman & Hall/CRC Biostatistics Series
Expected to ship within 12 - 19 working days
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Useful Statistical Approaches for Addressing Multiplicity Issues
Includes practical examples from recent trials Bringing together
leading statisticians, scientists, and clinicians from the
pharmaceutical industry, academia, and regulatory agencies,
Multiple Testing Problems in Pharmaceutical Statistics explores the
rapidly growing area of multiple comparison research with an
emphasis on pharmaceutical applications. In each chapter, the
expert contributors describe important multiplicity problems
encountered in pre-clinical and clinical trial settings. The book
begins with a broad introduction from a regulatory perspective to
different types of multiplicity problems that commonly arise in
confirmatory controlled clinical trials, before giving an overview
of the concepts, principles, and procedures of multiple testing. It
then presents statistical methods for analyzing clinical dose
response studies that compare several dose levels with a control as
well as statistical methods for analyzing multiple endpoints in
clinical trials. After covering gatekeeping procedures for testing
hierarchically ordered hypotheses, the book discusses statistical
approaches for the design and analysis of adaptive designs and
related confirmatory hypothesis testing problems. The final chapter
focuses on the design of pharmacogenomic studies based on
established statistical principles. It also describes the analysis
of data collected in these studies, taking into account the
numerous multiplicity issues that occur. This volume explains how
to solve critical issues in multiple testing encountered in
pre-clinical and clinical trial applications. It presents the
necessary statistical methodology, along with examples and software
code to show how to use the methods in practice.
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