Design and Analysis of Experiments, Special Designs and Applications

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John Wiley & Sons, Feb 14, 2012 - Mathematics - 600 pages
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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.


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Genetic Crosses Experiments
Design of Gene Expression Microarray Experiments
Spatial Analysis of Agricultural Field Experiments
Optimal Designs for Generalized Linear Models
Design and Analysis of Randomized Clinical Trials
Monitoring Randomized Clinical Trials
Adaptive Randomization in Clinical Trials
Designs for Choice Experiments for the Multinomial Logit
Computer Experiments
Designs for LargeScale Simulation Experiments with
Robust Parameter Designs
SplitPlot Response Surface Designs
Design and Analysis of Experiments for Directional Data
Author Index

Search Linear Model for Identification and Discrimination
Minimum Aberration and Related Criteria for Fractional

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About the author (2012)

KLAUS HINKELMANN, PhD, is Professor Emeritus of Statistics at the Virginia Polytechnic Institute and State University Department of Statistics. A Fellow of the American Statistical Association and the American Association for the Advancement of Science, Dr. Hinkelmann has published extensively in the areas of design of experiments, statistical methods, and biometry.