Design and Analysis of Experiments, 3 Volume Set

This user-friendly 3-volume set reflects a modern and accessible approach to experimental design and analysis. This set includes all three volumes of Klaus Hinkelmann's "Design and Analysis of Experiments" books. These include: Design and Analysis of Experiments, Volume 1, introduction to Experimental Design, 2nd Edition Design and Analysis of Experiments, Volume 2, Advanced Experimental Design Design and Analysis of Experiments, Volume 3, Special Designs and Applications All the books are available for individual purchase or you can order the full set. Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions. Design and Analysis of Experiments, Volume 2 provides more detail about aspects of error control and treatment design, with emphasis on their historical development and practical significance, and the connections between them. Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Each volume is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business.  

Table of Contents:
Preface Contributors CHAPTER 1: Genetic Crosses Experiments 1.1 INTRODUCTION 1.2 BASIC OBJECTIVES AND MODELS 1.2.1 Generation Mean Analysis 1.2.2 Generation Variance Analysis 1.2.3 Covariance between Relatives 1.2.4 Mating (M) and Environmental (E) Designs 1.2.5 Fixed Effects and Random Effects Models 1.3 DIALLEL MATING DESIGN OF TYPE I 1.3.1 North Carolina Design I (NCI) 1.3.2 North Carolina Design II (NCII) 1.3.3 Sets of North Carolina Design II 1.3.4 North Carolina Design III (NCIII) 1.3.5 Line x Tester Approach 1.3.6 A Modified Line x Tester Approach 1.4 DIALLEL CROSSES: TYPE II DESIGNS 1.4.1 Hayman Approach for Diallel Analysis 1.4.2 Griffing's Method 1.5 PARTIAL DIALLEL CROSSES: NO BLOCKING OR COMPLETE BLOCKS 1.6 PARTIAL DIALLEL CROSSES IN INCOMPLETE BLOCKS 1.6.1 Construction of Mating-Environment Designs 1.6.2 Analysis of M-E Design 1.6.3 An Example of PDC in Incomplete Blocks 1.6.4 Other M-E Designs 1.7 OPTIMALITY 1.7.1 Optimal CDC Designs for Estimation of gca 1.7.2 Optimal Partial Diallel Crosses 1.7.3 Estimation of Heritability 1.8 ROBUSTNESS 1.9 THREE- OR HIGHER-WAY CROSSES 1.9.1 Triallel or Three-Way Crosses 1.9.2 Double- or Four-Way Crosses 1.10 COMPUTATION ACKNOWLEDGMENTS REFERENCES CHAPTER 2: Design of Gene Expression Microarray Experiments 2.1 INTRODUCTION 2.2 GENE EXPRESSION MICROARRAY TECHNOLOGY 2.2.1 Introduction 2.2.2 Definition of a Microarray 2.2.3 Using Microarrays to Measure Gene Expression 2.2.4 Types of Gene Expression in Microarrays 2.3 PREPROCESSING OF MICROARRAY FLUORESCENCE INTENSITIES 2.3.1 Introduction 2.3.2 Background Correction 2.3.3 Normalization 2.3.4 Summarization 2.4 INTRODUCTION TO GENE EXPRESSION MICROARRAY EXPERIMENTAL DESIGN 2.5 TWO-TREATMENT EXPERIMENTS USING TWO-COLOR MICROARRAYS 2.6 TWO-COLOR MICROARRAY EXPERIMENTS INVOLVING MORE THAN TWO TREATMENTS 2.7 MULTIFACTOR TWO-COLOR MICROARRAY EXPERIMENTS 2.7.1 Introduction 2.7.2 Admissible Designs 2.7.3 w-Optimal Designs 2.7.4 e-Efficiency 2.8 PHASE 2 DESIGNS FOR COMPLEX PHASE 1 DESIGNS REFERENCES CHAPTER 3: Spatial Analysis of Agricultural Field Experiments 3.1 INTRODUCTION 3.2 METHODS TO ACCOUNT FOR SPATIAL VARIATION 3.2.1 Design of Experiments 3.2.2 Spatial Analysis Methods 3.3 A SPATIAL LINEAR MIXED MODEL 3.3.1 Estimation, Prediction and Testing 3.3.2 The Spatial Modeling Process 3.4 ANALYSIS OF EXAMPLES 3.4.1 Herbicide Tolerance Trial 3.4.2 Variety Trial REFERENCES CHAPTER 4: Optimal Designs for Generalized Linear Models 4.1 INTRODUCTION 4.2 NOTATION AND BASIC CONCEPTS 4.2.1 Binary Data 4.2.2 Count Data 4.2.3 Optimality Criteria 4.3 TOOLS FOR FINDING LOCALLY OPTIMAL DESIGNS 4.3.1 Traditional Approaches 4.3.2 An Analytical Approach 4.4 GLMs WITH TWO PARAMETERS 4.5 GLMs WITH MULTIPLE PARAMETERS 4.5.1 GLMs with Multiple Covariates 4.5.2 GLMs with Group Effects

About the Author :
Klaus Hinkelmann, PhD, is Emeritus Professor of Statistics in the Department of Statistics at Virginia Polytechnic Institute and State University. A Fellow of the American Statistical Association and the American Association for the Advancement of Science, Dr. Hinkelmann has published extensively in the areas of design of experiments, statistical methods, and biometry.