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:
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:Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
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
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
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