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.

• PrefaceContributorsCHAPTER 1: Genetic Crosses Experiments1.1 INTRODUCTION1.2 BASIC OBJECTIVES AND MODELS1.2.1 Generation Mean Analysis1.2.2 Generation Variance Analysis1.2.3 Covariance between Relatives1.2.4 Mating (M) and Environmental (E) Designs1.2.5 Fixed Effects and Random Effects Models1.3 DIALLEL MATING DESIGN OF TYPE I1.3.1 North Carolina Design I (NCI)1.3.2 North Carolina Design II (NCII)1.3.3 Sets of North Carolina Design II1.3.4 North Carolina Design III (NCIII)1.3.5 Line x Tester Approach 1.3.6 A Modified Line x Tester Approach1.4 DIALLEL CROSSES: TYPE II DESIGNS1.4.1 Hayman Approach for Diallel Analysis1.4.2 Griffing's Method1.5 PARTIAL DIALLEL CROSSES: NO BLOCKING OR COMPLETE BLOCKS1.6 PARTIAL DIALLEL CROSSES IN INCOMPLETE BLOCKS1.6.1 Construction of Mating-Environment Designs1.6.2 Analysis of M-E Design1.6.3 An Example of PDC in Incomplete Blocks1.6.4 Other M-E Designs1.7 OPTIMALITY1.7.1 Optimal CDC Designs for Estimation of gca1.7.2 Optimal Partial Diallel Crosses1.7.3 Estimation of Heritability1.8 ROBUSTNESS1.9 THREE- OR HIGHER-WAY CROSSES 1.9.1 Triallel or Three-Way Crosses1.9.2 Double- or Four-Way Crosses1.10 COMPUTATIONACKNOWLEDGMENTSREFERENCESCHAPTER 2: Design of Gene Expression Microarray Experiments2.1 INTRODUCTION2.2 GENE EXPRESSION MICROARRAY TECHNOLOGY2.2.1 Introduction2.2.2 Definition of a Microarray2.2.3 Using Microarrays to Measure Gene Expression2.2.4 Types of Gene Expression in Microarrays2.3 PREPROCESSING OF MICROARRAY FLUORESCENCE INTENSITIES2.3.1 Introduction2.3.2 Background Correction2.3.3 Normalization2.3.4 Summarization 2.4 INTRODUCTION TO GENE EXPRESSION MICROARRAY EXPERIMENTAL DESIGN2.5 TWO-TREATMENT EXPERIMENTS USING TWO-COLOR MICROARRAYS2.6 TWO-COLOR MICROARRAY EXPERIMENTS INVOLVING MORE THAN TWO TREATMENTS2.7 MULTIFACTOR TWO-COLOR MICROARRAY EXPERIMENTS2.7.1 Introduction2.7.2 Admissible Designs2.7.3 w-Optimal Designs2.7.4 e-Efficiency2.8 PHASE 2 DESIGNS FOR COMPLEX PHASE 1 DESIGNSREFERENCESCHAPTER 3: Spatial Analysis of Agricultural Field Experiments3.1 INTRODUCTION3.2 METHODS TO ACCOUNT FOR SPATIAL VARIATION3.2.1 Design of Experiments3.2.2 Spatial Analysis Methods 3.3 A SPATIAL LINEAR MIXED MODEL3.3.1 Estimation, Prediction and Testing3.3.2 The Spatial Modeling Process3.4 ANALYSIS OF EXAMPLES3.4.1 Herbicide Tolerance Trial3.4.2 Variety TrialREFERENCESCHAPTER 4: Optimal Designs for Generalized Linear Models4.1 INTRODUCTION4.2 NOTATION AND BASIC CONCEPTS4.2.1 Binary Data4.2.2 Count Data4.2.3 Optimality Criteria4.3 TOOLS FOR FINDING LOCALLY OPTIMAL DESIGNS4.3.1 Traditional Approaches4.3.2 An Analytical Approach4.4 GLMs WITH TWO PARAMETERS4.5 GLMs WITH MULTIPLE PARAMETERS4.5.1 GLMs with Multiple Covariates 4.5.2 GLMs with Group Effects

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.

• PrefaceContributorsCHAPTER 1: Genetic Crosses Experiments1.1 INTRODUCTION1.2 BASIC OBJECTIVES AND MODELS1.2.1 Generation Mean Analysis1.2.2 Generation Variance Analysis1.2.3 Covariance between Relatives1.2.4 Mating (M) and Environmental (E) Designs1.2.5 Fixed Effects and Random Effects Models1.3 DIALLEL MATING DESIGN OF TYPE I1.3.1 North Carolina Design I (NCI)1.3.2 North Carolina Design II (NCII)1.3.3 Sets of North Carolina Design II1.3.4 North Carolina Design III (NCIII)1.3.5 Line x Tester Approach 1.3.6 A Modified Line x Tester Approach1.4 DIALLEL CROSSES: TYPE II DESIGNS1.4.1 Hayman Approach for Diallel Analysis1.4.2 Griffing's Method1.5 PARTIAL DIALLEL CROSSES: NO BLOCKING OR COMPLETE BLOCKS1.6 PARTIAL DIALLEL CROSSES IN INCOMPLETE BLOCKS1.6.1 Construction of Mating-Environment Designs1.6.2 Analysis of M-E Design1.6.3 An Example of PDC in Incomplete Blocks1.6.4 Other M-E Designs1.7 OPTIMALITY1.7.1 Optimal CDC Designs for Estimation of gca1.7.2 Optimal Partial Diallel Crosses1.7.3 Estimation of Heritability1.8 ROBUSTNESS1.9 THREE- OR HIGHER-WAY CROSSES 1.9.1 Triallel or Three-Way Crosses1.9.2 Double- or Four-Way Crosses1.10 COMPUTATIONACKNOWLEDGMENTSREFERENCESCHAPTER 2: Design of Gene Expression Microarray Experiments2.1 INTRODUCTION2.2 GENE EXPRESSION MICROARRAY TECHNOLOGY2.2.1 Introduction2.2.2 Definition of a Microarray2.2.3 Using Microarrays to Measure Gene Expression2.2.4 Types of Gene Expression in Microarrays2.3 PREPROCESSING OF MICROARRAY FLUORESCENCE INTENSITIES2.3.1 Introduction2.3.2 Background Correction2.3.3 Normalization2.3.4 Summarization 2.4 INTRODUCTION TO GENE EXPRESSION MICROARRAY EXPERIMENTAL DESIGN2.5 TWO-TREATMENT EXPERIMENTS USING TWO-COLOR MICROARRAYS2.6 TWO-COLOR MICROARRAY EXPERIMENTS INVOLVING MORE THAN TWO TREATMENTS2.7 MULTIFACTOR TWO-COLOR MICROARRAY EXPERIMENTS2.7.1 Introduction2.7.2 Admissible Designs2.7.3 w-Optimal Designs2.7.4 e-Efficiency2.8 PHASE 2 DESIGNS FOR COMPLEX PHASE 1 DESIGNSREFERENCESCHAPTER 3: Spatial Analysis of Agricultural Field Experiments3.1 INTRODUCTION3.2 METHODS TO ACCOUNT FOR SPATIAL VARIATION3.2.1 Design of Experiments3.2.2 Spatial Analysis Methods 3.3 A SPATIAL LINEAR MIXED MODEL3.3.1 Estimation, Prediction and Testing3.3.2 The Spatial Modeling Process3.4 ANALYSIS OF EXAMPLES3.4.1 Herbicide Tolerance Trial3.4.2 Variety TrialREFERENCESCHAPTER 4: Optimal Designs for Generalized Linear Models4.1 INTRODUCTION4.2 NOTATION AND BASIC CONCEPTS4.2.1 Binary Data4.2.2 Count Data4.2.3 Optimality Criteria4.3 TOOLS FOR FINDING LOCALLY OPTIMAL DESIGNS4.3.1 Traditional Approaches4.3.2 An Analytical Approach4.4 GLMs WITH TWO PARAMETERS4.5 GLMs WITH MULTIPLE PARAMETERS4.5.1 GLMs with Multiple Covariates 4.5.2 GLMs with Group Effects

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.

• PrefaceContributorsCHAPTER 1: Genetic Crosses Experiments1.1 INTRODUCTION1.2 BASIC OBJECTIVES AND MODELS1.2.1 Generation Mean Analysis1.2.2 Generation Variance Analysis1.2.3 Covariance between Relatives1.2.4 Mating (M) and Environmental (E) Designs1.2.5 Fixed Effects and Random Effects Models1.3 DIALLEL MATING DESIGN OF TYPE I1.3.1 North Carolina Design I (NCI)1.3.2 North Carolina Design II (NCII)1.3.3 Sets of North Carolina Design II1.3.4 North Carolina Design III (NCIII)1.3.5 Line x Tester Approach 1.3.6 A Modified Line x Tester Approach1.4 DIALLEL CROSSES: TYPE II DESIGNS1.4.1 Hayman Approach for Diallel Analysis1.4.2 Griffing's Method1.5 PARTIAL DIALLEL CROSSES: NO BLOCKING OR COMPLETE BLOCKS1.6 PARTIAL DIALLEL CROSSES IN INCOMPLETE BLOCKS1.6.1 Construction of Mating-Environment Designs1.6.2 Analysis of M-E Design1.6.3 An Example of PDC in Incomplete Blocks1.6.4 Other M-E Designs1.7 OPTIMALITY1.7.1 Optimal CDC Designs for Estimation of gca1.7.2 Optimal Partial Diallel Crosses1.7.3 Estimation of Heritability1.8 ROBUSTNESS1.9 THREE- OR HIGHER-WAY CROSSES 1.9.1 Triallel or Three-Way Crosses1.9.2 Double- or Four-Way Crosses1.10 COMPUTATIONACKNOWLEDGMENTSREFERENCESCHAPTER 2: Design of Gene Expression Microarray Experiments2.1 INTRODUCTION2.2 GENE EXPRESSION MICROARRAY TECHNOLOGY2.2.1 Introduction2.2.2 Definition of a Microarray2.2.3 Using Microarrays to Measure Gene Expression2.2.4 Types of Gene Expression in Microarrays2.3 PREPROCESSING OF MICROARRAY FLUORESCENCE INTENSITIES2.3.1 Introduction2.3.2 Background Correction2.3.3 Normalization2.3.4 Summarization 2.4 INTRODUCTION TO GENE EXPRESSION MICROARRAY EXPERIMENTAL DESIGN2.5 TWO-TREATMENT EXPERIMENTS USING TWO-COLOR MICROARRAYS2.6 TWO-COLOR MICROARRAY EXPERIMENTS INVOLVING MORE THAN TWO TREATMENTS2.7 MULTIFACTOR TWO-COLOR MICROARRAY EXPERIMENTS2.7.1 Introduction2.7.2 Admissible Designs2.7.3 w-Optimal Designs2.7.4 e-Efficiency2.8 PHASE 2 DESIGNS FOR COMPLEX PHASE 1 DESIGNSREFERENCESCHAPTER 3: Spatial Analysis of Agricultural Field Experiments3.1 INTRODUCTION3.2 METHODS TO ACCOUNT FOR SPATIAL VARIATION3.2.1 Design of Experiments3.2.2 Spatial Analysis Methods 3.3 A SPATIAL LINEAR MIXED MODEL3.3.1 Estimation, Prediction and Testing3.3.2 The Spatial Modeling Process3.4 ANALYSIS OF EXAMPLES3.4.1 Herbicide Tolerance Trial3.4.2 Variety TrialREFERENCESCHAPTER 4: Optimal Designs for Generalized Linear Models4.1 INTRODUCTION4.2 NOTATION AND BASIC CONCEPTS4.2.1 Binary Data4.2.2 Count Data4.2.3 Optimality Criteria4.3 TOOLS FOR FINDING LOCALLY OPTIMAL DESIGNS4.3.1 Traditional Approaches4.3.2 An Analytical Approach4.4 GLMs WITH TWO PARAMETERS4.5 GLMs WITH MULTIPLE PARAMETERS4.5.1 GLMs with Multiple Covariates 4.5.2 GLMs with Group Effects