Handbook of design and analysis of experiments

Table of Contents:

Section I General Principles

1. History and overview of design and analysis of experiments
2. Introduction to linear models

Section II Designs for Linear Models

3. Blocking with independent responses
4. Crossover designs
5. Responses surface experiments and designs
6. Design for linear regression models with correlated errors

Section III Designs Accommodating Multiple Factors

7. Regular fractional factorial designs
8. Multistratum fractional factorial designs
9. Nonregular factorial and supersaturated designs
10. Structures defined by factors
11. Algebraic method in experimental design

Section IV Optimal Design for Nonlinear and Spatial Models

12. Optimal design for nonlinear and spatial models: introduction and historical overview
13. Designs for generalized linear models
14. Designs for selected nonlinear models
15. Optimal design for spatial models

Section V Computer Experiments

16. Design of computer experiments: introduction and background
17. Latin hypercubes and space-filling designs
18. Design for sensitivity analysis
19. Expected improvement design

Section VI Cross-Cutting Issues

20. Robustness of design
21. Algorithmic searches for optimal design

Section VII Design for Contemporary Applications

22. Design for discrete choice experiments
23. Plate designs in high-throughput screening experiments for drug discovery
24. Up-and-down designs for dose-finding
25. Optimal design for event-related fMRI studies

Handbook of Design and Analysis of Experiments provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook gives a unified treatment of a wide range of topics, covering the latest developments.

This carefully edited collection of 25 chapters in seven sections synthesizes the state of the art in the theory and applications of designed experiments and their analyses. Written by leading researchers in the field, the chapters offer a balanced blend of methodology and applications.

The first section presents a historical look at experimental design and the fundamental theory of parameter estimation in linear models. The second section deals with settings such as response surfaces and block designs in which the response is modeled by a linear model, the third section covers designs with multiple factors (both treatment and blocking factors), and the fourth section presents optimal designs for generalized linear models, other nonlinear models, and spatial models. The fifth section addresses issues involved in designing various computer experiments. The sixth section explores "cross-cutting" issues relevant to all experimental designs, including robustness and algorithms. The final section illustrates the application of experimental design in recently developed areas.

This comprehensive handbook equips new researchers with a broad understanding of the field’s numerous techniques and applications. The book is also a valuable reference for more experienced research statisticians working in engineering and manufacturing, the basic sciences, and any discipline that depends on controlled experimental investigation.

(https://www.crcpress.com/Handbook-of-Design-and-Analysis-of-Experiments/Dean-Morris-Stufken-Bingham/p/book/9781466504332)