Awards

• Winner of Winner of the 2009 Ziegel Prize.

Overview

"Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis. This book presents the theory and methods of optimum experimental design, making them available through the use of SAS programs. Little previous statistical knowledge is assumed. The first part of the book stresses the importance of models in the analysis of data and introduces least squares fitting and simple optimum experimental designs. The second part presents a more detailed discussion of the general theory and of a wide variety of experiments. The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations. The mathematical theory of the designs is developed in parallel with their construction in SAS, so providing motivation for the development of the subject. Many chapters cover self-contained topics drawn from science, engineering and pharmaceutical investigations, such as response surface designs, blocking of experiments, designs for mixture experiments and for nonlinear and generalized linear models. Understanding is aided by the provision of ""SAS tasks"" after most chapters as well as by more traditional exercises and a fully supported website. The authors are leading experts in key fields and this book is ideal for statisticians and scientists in academia, research and the process and pharmaceutical industries."

Full Product Details

Author:   Anthony Atkinson (London School of Economics) ,  Alexander Donev (Astra Zeneca) ,  Randall Tobias (SAS Institute Inc.)
Publisher:   Oxford University Press
Imprint:   Oxford University Press
Volume:   34
Dimensions:   Width: 17.30cm , Height: 3.30cm , Length: 24.70cm
Weight:   1.005kg
ISBN:  

9780199296590

ISBN 10:   0199296596
Pages:   528
Publication Date:   24 May 2007
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   To order  
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

Table of Contents

Preface I Background 1: Introduction 2: Some key ideas 3: Experimental strategies 4: The choice of a model 5: Models and least squares 6: Criteria for a good experiment 7: Standard designs 8: The analysis of experiments II Theory and applications 9: Optimum design theory 10: Criteria of optimality 11: D-optimum designs 12: Algorithms for the construction of exact D-optimum designs 13: Optimum experimental design with SAS 14: Experiments with both qualitative and quantitative factors 15: Blocking response surface designs 16: Mixture experiments 17: Nonlinear models 18: Bayesian optimum designs 19: Design augmentation 20: Model checking and designs for discriminating between models 21: Compound design criteria 22: Generalized linear models 23: Response transformation and structured variances 24: Time-dependent models with correlated observations 25: Further topics 26: Exercises Bibliography Author index Subject index

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