Summary and Info
Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS, JMP, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.Content: Chapter 1 Genetic Crosses Experiments (pages 1–71): Murari Singh, Sudhir Gupta and Rajender ParsadChapter 2 Design of Gene Expression Microarray Experiments (pages 73–108): Dan NettletonChapter 3 Spatial Analysis of Agricultural Field Experiments (pages 109–136): Joanne K. Stringer, Alison B. Smith and Brian R. CullisChapter 4 Optimal Designs for Generalized Linear Models (pages 137–164): John Stufken and Min YangChapter 5 Design and Analysis of Randomized Clinical Trials (pages 165–211): Janet Wittes and Zi?Fan YuChapter 6 Monitoring Randomized Clinical Trials (pages 213–249): Eric S. Leifer and Nancy L. GellerChapter 7 Adaptive Randomization in Clinical Trials (pages 251–281): Lanju Zhang and William F. RosenbergerChapter 8 Search Linear Model for Identification and Discrimination (pages 283–298): Subir GhoshChapter 9 Minimum Aberration and Related Criteria for Fractional Factorial Designs (pages 299–329): Hegang H. Chen and Ching?Shui ChengChapter 10 Designs for Choice Experiments for the Multinomial Logit Model (pages 331–378): Deborah J. Street and Leonie BurgessChapter 11 Computer Experiments (pages 379–411): Max D. MorrisChapter 12 Designs for Large?Scale Simulation Experiments, with Applications to Defense and Homeland Security (pages 413–441): Susan M. Sanchez, Thomas W. Lucas, Paul J. Sanchez, Christopher J. Nannini and Hong WanChapter 13 Robust Parameter Designs (pages 443–469): Timothy J. Robinson and Christine M. Anderson?CookChapter 14 Split?Plot Response Surface Designs (pages 471–500): G. Geoffrey ViningChapter 15 Design and Analysis of Experiments for Directional Data (pages 501–532): Sango B. Otieno and Christine M. Anderson?Cook
More About the Author
David Balding is an Australian statistician and Professor in Statistical Genetics at University College London.
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