This book explains how to solve the most important problems in multiple testing encountered in drug discovery, pre-clinical, and clinical trial applications. It presents relevant statistical methodology; illustrates the methodology using real-life examples from drug discovery experiments, pre-clinical studies, and clinical trials; and provides software code (SAS, S-Plus, R) for solving the problems. It describes statistical strategies for handling multiplicity issues in the pharmaceutical industry and covers basic/traditional multiple testing procedures as well as novel approaches to...

The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences.

The book supplies a...