Handbook of Design and Analysis of Experiments (Chapman & Hall/CRC Handbooks of Modern Statistical Methods 7)

This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas. Content: General Principles History and Overview of Design and Analysis of Experiments Klaus Hinkelmann Introduction to Linear Models Linda M. Haines Designs for Linear Models Blocking with Independent Responses John P. Morgan Crossover Designs Mausumi Bose and Aloke Dey Response Surface Experiments and Designs Andre I. Khuri and Siuli Mukhopadhyay Design for Linear Regression Models with Correlated Errors Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky Designs Accommodating Multiple Factor Regular Fractional Factorial Designs Robert Mee and Angela Dean Multistratum Fractional Factorial Designs Derek Bingham Nonregular Factorial and Supersaturated Designs Hongquan Xu Structures Defined by Factors R.A. Bailey Algebraic Method in Experimental Design Hugo Maruri-Aguilar and Henry P. Wynn Optimal Design for Nonlinear and Spatial Models Optimal Design for Nonlinear and Spatial Models: Introduction and Historical Overview Douglas P. Wiens Designs for Generalized Linear Models Anthony C. Atkinson and David C. Woods Designs for Selected Nonlinear Models Stefanie Biedermann and Min Yang Optimal Design for Spatial Models Zhengyuan Zhu and Evangelos Evangelou Computer Experiments Design of Computer Experiments: Introduction and Background Max Morris and Leslie Moore Latin Hypercubes and Space-Filling Designs C. Devon Lin and Boxin Tang Design for Sensitivity Analysis William Becker and Andrea Saltelli Expected Improvement Designs William I. Notz Cross-Cutting Issues Robustness of Design Douglas P. Wiens Algorithmic Searches for Optimal Designs Abhyuday Mandal, Weng Kee Wong, and Yaming Yu Design for Contemporary Applications Design for Discrete Choice Experiments Heiko Grossmann and Rainer Schwabe Plate Designs in High-Throughput Screening Experiments for Drug Discovery Xianggui Qu (Harvey) and Stanley Young Up-and-Down Designs for Dose-Finding Nancy Flournoy and Assaf P. Oron Optimal Design for Event-Related fMRI Studies Jason Ming-Hung Kao and John Stufken Index Cover 1 Series 3 Contents 8 Preface 12 Editors 16 Contributors 18 Section I: General Principles 22 Chapter 1: History and Overview of Design and Analysis of Experiments 24 Chapter 2: Introduction to Linear Models 84 Section II: Designs for Linear Models 118 Chapter 3: Blocking with Independent Responses 120 Chapter 4: Crossover Designs 180 Chapter 5: Response Surface Experiments and Designs 218 Chapter 6: Design for Linear Regression Models with Correlated Errors 258 Section III: Designs Accommodating Multiple Factors 298 Chapter 7: Regular Fractional Factorial Designs 300 Chapter 8: Multistratum Fractional Factorial Designs 342 Chapter 9: Nonregular Factorial and Supersaturated Designs 360 Chapter 10: Structures Defined by Factors 392 Chapter 11: Algebraic Method in Experimental Design 436 Section IV: Optimal Design for Nonlinear and Spatial Models 476 Chapter 12: Optimal Design for Nonlinear and Spatial Models: Introduction and Historical Overview 478 Chapter 13: Designs for Generalized Linear Models 492 Chapter 14: Designs for Selected Nonlinear Models 536 Chapter 15: Optimal Design for Spatial Models 570 Section V: Computer Experiments 596 Chapter 16: Design of Computer Experiments: Introduction and Background 598 Chapter 17: Latin Hypercubes and Space-Filling Designs 614 Chapter 18: Design for Sensitivity Analysis 648 Chapter 19: Expected Improvement Designs 696 Section VI: Cross-Cutting Issues 738 Chapter 20: Robustness of Design 740 Chapter 21: Algorithmic Searches for Optimal Designs 776 Section VII: Design for Contemporary Applications 806 Chapter 22: Design for Discrete Choice Experiments 808 Chapter 23: Plate Designs in High-Throughput Screening Experiments for Drug Discovery 854 Chapter 24: Up-and-Down Designs for Dose-Finding 878 Chapter 25: Optimal Design for Event-Related fMRI Studies 916 Back Cover 946 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