Optimum Experimental Designs, with SAS [Paperback]

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