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Main description:
Provides timely applications, modifications, and extensionsof experimental designs for a variety of disciplines
Design and Analysis of Experiments, Volume 3: Special Designsand Applications continues building upon the philosophicalfoundations of experimental design by providing important, modernapplications of experimental design to the many fields that utilizethem. The book also presents optimal and efficient designs forpractice and covers key topics in current statistical research.
Featuring contributions from leading researchers and academics,the book demonstrates how the presented concepts are used acrossvarious fields from genetics and medicinal and pharmaceuticalresearch to manufacturing, engineering, and national security. Eachchapter includes an introduction followed by the historicalbackground as well as in–depth procedures that aid in theconstruction and analysis of the discussed designs. Topicalcoverage includes:
- Genetic cross experiments, microarray experiments, and varietytrials
- Clinical trials, group–sequential designs, and adaptivedesigns
- Fractional factorial, search, and choice designs, and optimaldesigns for generalized linear models
- Computer experiments with applications to homelandsecurity
- Robust parameter designs and split–plot type response surfacedesigns
- Analysis of directional data experiments
Throughout the book, illustrative and numerical examples utilizeSAS®, JMP®, and R software programs to demonstrate thediscussed techniques. Related data sets and software applicationsare available on the book′s related FTP site.
Design and Analysis of Experiments, Volume 3 is an idealtextbook for graduate courses in experimental design and alsoserves as a practical, hands–on reference for statisticians andresearchers across a wide array of subject areas, includingbiological sciences, engineering, medicine, and business.
Back cover:
Provides timely applications, modifications, and extensionsof experimental designs for a variety of disciplines
Design and Analysis of Experiments, Volume 3: Special Designsand Applications continues building upon the philosophicalfoundations of experimental design by providing important, modernapplications of experimental design to the many fields that utilizethem. The book also presents optimal and efficient designs forpractice and covers key topics in current statistical research.
Featuring contributions from leading researchers and academics,the book demonstrates how the presented concepts are used acrossvarious fields from genetics and medicinal and pharmaceuticalresearch to manufacturing, engineering, and national security. Eachchapter includes an introduction followed by the historicalbackground as well as in–depth procedures that aid in theconstruction and analysis of the discussed designs. Topicalcoverage includes:
- Genetic cross experiments, microarray experiments, and varietytrials
- Clinical trials, group–sequential designs, and adaptivedesigns
- Fractional factorial, search, and choice designs, and optimaldesigns for generalized linear models
- Computer experiments with applications to homelandsecurity
- Robust parameter designs and split–plot type response surfacedesigns
- Analysis of directional data experiments
Throughout the book, illustrative and numerical examples utilizeSAS®, JMP®, and R software programs to demonstrate thediscussed techniques. Related data sets and software applicationsare available on the book′s related FTP site.
Design and Analysis of Experiments, Volume 3 is an idealtextbook for graduate courses in experimental design and alsoserves as a practical, hands–on reference for statisticians andresearchers across a wide array of subject areas, includingbiological sciences, engineering, medicine, and business.
Contents:
Preface xvii
Contributors xxi
1 Genetic Crosses Experiments 1
Murari Singh, Sudhir Gupta, and Rajender Parsad
1.1 Introduction, 1
1.2 Basic Objectives and Models, 2
1.3 Diallel Mating Design of Type I, 8
1.4 Diallel Crosses: Type II Designs, 14
1.5 Partial Diallel Crosses: No Blocking or Complete Blocks,25
1.6 Partial Diallel Crosses in Incomplete Blocks, 32
1.7 Optimality, 44
1.8 Robustness, 59
1.9 Three– or Higher–Way Crosses, 61
1.10 Computation, 65
2 Design of Gene Expression Microarray Experiments 73
Dan Nettleton
2.1 Introduction, 73
2.2 Gene Expression Microarray Technology, 74
2.3 Preprocessing of Microarray Fluorescence Intensities, 76
2.4 Introduction to Gene Expression Microarray ExperimentalDesign, 80
2.5 Two–Treatment Experiments Using Two–Color Microarrays,81
2.6 Two–Color Microarray Experiments Involving More Than TwoTreatments, 86
2.7 Multifactor Two–Color Microarray Experiments, 89
2.8 Phase 2 Designs for Complex Phase 1 Designs, 94
3 Spatial Analysis of Agricultural Field Experiments109
Joanne K. Stringer, Alison B. Smith, and Brian R.Cullis
3.1 Introduction, 109
3.2 Methods to Account for Spatial Variation, 110
3.3 A Spatial Linear Mixed Model, 116
3.4 Analysis of Examples, 122
4 Optimal Designs for Generalized Linear Models 137
John Stufken and Min Yang
4.1 Introduction, 137
4.2 Notation and Basic Concepts, 141
4.3 Tools for Finding Locally Optimal Designs, 145
4.4 GLMs with Two Parameters, 149
4.5 GLMs with Multiple Parameters, 155
4.6 Summary and Concluding Comments, 161
5 Design and Analysis of Randomized Clinical Trials 165
Janet Wittes and Zi–Fan Yu
5.1 Overview, 165
5.2 Components of a Randomized Clinical Trial, 168
5.3 Bias, 175
5.4 Statistical Analysis of Randomized Clinical Trials, 182
5.5 Failure Time Studies, 184
5.6 Other Topics, 206
6 Monitoring Randomized Clinical Trials 213
Eric S. Leifer and Nancy L. Geller
6.1 Introduction, 213
6.2 Normally Distributed Outcomes, 215
6.3 Brownian Motion Properties, 217
6.4 Brief Historical Overview of Group Sequential Methods,219
6.5 Dichotomous Outcomes, 223
6.6 Time–to–Event Outcomes, 225
6.7 Unconditional Power, 227
6.8 Conditional Power, 229
6.9 Spending Functions, 232
6.10 Flexibility and Properties of Spending Functions, 233
6.11 Modifying the Trial s Sample Size Based on a NuisanceParameter, 235
6.12 Sample Size Modification Based on the Interim TreatmentEffect, 240
6.13 Concluding Remarks, 246
7 Adaptive Randomization in Clinical Trials 251
Lanju Zhang and William F. Rosenberger
7.1 Introduction, 251
7.2 Adaptive Randomization Procedures, 252
7.3 Likelihood–Based Inference, 264
7.4 Randomization–Based Inference, 269
7.5 Conclusions and Practical Considerations, 276
8 Search Linear Model for Identification and Discrimination283
Subir Ghosh
8.1 Introduction, 283
8.2 General Linear Model with Fixed Effects, 284
8.3 Search Linear Model, 285
8.4 Applications, 288
8.5 Effects of Noise in Performance Comparison, 293
9 Minimum Aberration and Related Criteria for FractionalFactorial Designs 299
Hegang H. Chen and Ching–Shui Cheng
9.1 Introduction, 299
9.2 Projections of Fractional Factorial Designs, 302
9.3 Estimation Capacity, 304
9.4 Clear Two–Factor Interactions, 307
9.5 Estimation Index, 310
9.6 Estimation Index, Minimum Aberration, and Maximum EstimationCapacity, 314
9.7 Complementary Design Theory for Minimum Aberration Designs,315
9.8 Nonregular Designs and Orthogonal Arrays, 317
9.9 Generalized Minimum Aberration, 320
9.10 Optimal Fractional Factorial Block Designs, 322
10 Designs for Choice Experiments for the Multinomial LogitModel 331
Deborah J. Street and Leonie Burgess
10.1 Introduction, 331
10.2 Definitions, 332
10.3 The MNL Model, 335
10.4 Design Comparisons, 338
10.5 Optimal Designs for DCEs, 340
10.6 Using Combinatorial Designs to Construct DCEs, 364
10.7 Bayesian Work, 368
10.8 Best Worst Experiments, 368
10.9 Miscellaneous Topics, 370
11 Computer Experiments 379
Max D. Morris
11.1 Introduction, 379
11.2 Sensitivity/Uncertainty Analysis, 382
11.3 Gaussian Stochastic Process Models, 385
11.4 Inference, 389
11.5 Experimental Designs, 398
11.6 Multivariate Output, 403
11.7 Multiple Data Sources, 406
11.8 Conclusion, 409
12 Designs for Large–Scale Simulation Experiments, withApplications to Defense and Homeland Security 413
Susan M. Sanchez, Thomas W. Lucas, Paul J. Sanchez,Christopher J. Nannini, and Hong Wan
12.1 Introduction, 413
12.2 Philosophy: Evolution of Computational Experiments, 414
12.3 Application: U.S. Army Unmanned Aerial Vehicle (UAV) MixStudy, 422
12.4 Parting Thoughts, 437
13 Robust Parameter Designs 443
Timothy J. Robinson and Christine M. Anderson–Cook
13.1 Introduction, 443
13.2 Taguchi Signal–to–Noise Ratio Approach, 445
13.3 Dual Model Response Surface Methodology, 448
13.4 Single Model Response Surface Methods Using CombinedArrays, 451
13.5 Computer Generated Combined Arrays, 461
13.6 RPD Involving Quantitative and Qualitative Factors, 465
13.7 Conclusions, 466
14 Split–Plot Response Surface Designs 471
G. Geoffrey Vining
14.1 Introduction, 471
14.2 Differences between Agricultural and IndustrialExperimentation, 472
14.3 OLS GLS Equivalent Second–Order Split–Plot Designsand Analysis, 482
14.4 Exact Tests for the Coeffi cients, 488
14.5 Proper Residuals for Checking Assumptions, 493
14.6 "Optimal" Second–Order Split–Plot Designs, 496
15 Design and Analysis of Experiments for Directional Data501
Sango B. Otieno and Christine M. Anderson–Cook
15.1 Summary, 501
15.2 Introduction and Historical Background, 501
15.3 ANOVA for Circular Data, 509
15.4 ANOVA for Cylindrical Data, 521
15.5 ANOVA for Spherical Data, 524
15.6 Conclusions, 530
References, 531
Author Index 533
Subject Index 545
PRODUCT DETAILS
Publisher: John Wiley & Sons Ltd (Wiley–Blackwell)
Publication date: March, 2012
Pages: 600
Dimensions: 164.00 x 241.00 x 35.16
Weight: 916g
Availability: Not available (reason unspecified)
Subcategories: Epidemiology
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