Optimum Experimental Designs, with SAS

Paperback | May 24, 2007

byAnthony Atkinson, Alexander Donev, Randall Tobias

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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 previousstatistical 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 ofexperiments. 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 thesubject. 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.

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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 previousstatistical knowledge is assumed. The first par...

Anthony Atkinson is at the London School of Economics. Alexander Donev is with Astra Zeneca. Randall Tobias is with the SAS Institute Inc.

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Format:PaperbackDimensions:528 pages, 9.45 × 6.61 × 1.14 inPublished:May 24, 2007Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:019929660X

ISBN - 13:9780199296606

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Table of Contents

PrefaceI Background1. Introduction2. Some key ideas3. Experimental strategies4. The choice of a model5. Models and least squares6. Criteria for a good experiment7. Standard designs8. The analysis of experimentsII Theory and applications9. Optimum design theory10. Criteria of optimality11. D-optimum designs12. Algorithms for the construction of exact D-optimum designs13. Optimum experimental design with SAS14. Experiments with both qualitative and quantitative factors15. Blocking response surface designs16. Mixture experiments17. Nonlinear models18. Bayesian optimum designs19. Design augmentation20. Model checking and designs for discriminating between models21. Compound design criteria22. Generalized linear models23. Response transformation and structured variances24. Time-dependent models with correlated observations25. Further topics26. ExercisesBibliographyAuthor indexSubject index