Presents statistical methodologies for analyzing common types of data from method comparison experiments and illustrates their applications through detailed case studies Measuring Agreement: Models, Methods, and Applications features statistical evaluation of agreement between two or more methods of measurement of a variable with a primary focus on continuous data. The authors view the analysis of method comparison data as a two-step procedure where an adequate model for the data is found, and then inferential techniques are applied for appropriate functions of parameters of the model. The…mehr
Presents statistical methodologies for analyzing common types of data from method comparison experiments and illustrates their applications through detailed case studies Measuring Agreement: Models, Methods, and Applications features statistical evaluation of agreement between two or more methods of measurement of a variable with a primary focus on continuous data. The authors view the analysis of method comparison data as a two-step procedure where an adequate model for the data is found, and then inferential techniques are applied for appropriate functions of parameters of the model. The presentation is accessible to a wide audience and provides the necessary technical details and references. In addition, the authors present chapter-length explorations of data from paired measurements designs, repeated measurements designs, and multiple methods; data with covariates; and heteroscedastic, longitudinal, and categorical data. The book also: * Strikes a balance between theory and applications * Presents parametric as well as nonparametric methodologies * Provides a concise introduction to Cohen's kappa coefficient and other measures of agreement for binary and categorical data * Discusses sample size determination for trials on measuring agreement * Contains real-world case studies and exercises throughout * Provides a supplemental website containing the related datasets and R code Measuring Agreement: Models, Methods, and Applications is a resource for statisticians and biostatisticians engaged in data analysis, consultancy, and methodological research. It is a reference for clinical chemists, ecologists, and biomedical and other scientists who deal with development and validation of measurement methods. This book can also serve as a graduate-level text for students in statistics and biostatistics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
P. K. CHOUDHARY, PhD, is Professor in the Department of Mathematical Sciences at the University of Texas at Dallas. Currently, he is also the Associate Head of the department. His research interests include development of statistical methodology for biostatistical applications, and he has published extensively in the field of method comparison studies. H. N. NAGARAJA, PhD, is Professor Emeritus at The Ohio State University where he has served in the Departments of Statistics and Internal Medicine and the Division of Biostatistics. He is a fellow of the American Statistical Association and the American Association for the Advancement of Science, and an elected member of the International Statistical Institute. His published works include Order Statistics, Third Edition (with H. A. David) and Records (with B. C. Arnold and N. Balakrishnan), both published by Wiley.
Inhaltsangabe
Preface Chapter 1: Introduction 1.1 Preview 1.2 Notational conventions 1.3 Basic characteristics of a measurement method 1.4 Method comparison studies 1.5 Meaning of agreement 1.6 A measurement error model 1.7 Similarity versus agreement 1.8 A toy example 1.9 Controversies and our view 1.10 Concepts related to agreement 1.11 Role of confidence intervals and hypotheses testing 1.12 Common models for paired measurements data 1.13 The Bland Altman plot 1.14 Common regression approaches 1.15 Inappropriate use of common tests in method comparison studies 1.16 Key steps in the analysis of method comparison data 1.17 Chapter summary 1.18 Bibliographic note Exercises Chapter 2: Common Approaches for Measuring Agreement 2.1 Preview 2.2 Introduction 2.3 Mean squared deviation 2.4 Concordance correlation coefficient 2.5 A digression: Tolerance and prediction intervals 2.6 Lin's probability criterion and Bland Altman criterion 2.7 Limits of agreement 2.8 Total deviation index and coverage probability 2.9 Inference on agreement measures 2.10 Chapter summary 2.11 Bibliographic note Exercises Chapter 3: A General Approach for Modeling and Inference 3.1 Preview 3.2 Mixed effects models 3.3 A large-sample approach for inference 3.4 Modeling and analysis of method comparison data 3.5 Chapter summary 3.6 Bibliographic note Exercises Chapter 4: Paired Measurements Data 4.1 Preview 4.2 Modeling of data 4.3 Evaluation of similarity and agreement 4.4 Case studies 4.5 Chapter summary 4.6 Technical details 4.7 Bibliographic note Exercises Chapter 5: Repeated Measurements Data 5.1 Preview 5.2 Introduction 5.3 Displaying data 5.4 Modeling of data 5.5 Evaluation of similarity and agreement 5.6 Evaluation of repeatability 5.7 Case studies 5.8 Chapter summary 5.9 Technical details 5.10 Bibliographic note Exercises Chapter 6: Heteroscedastic Data 6.1 Preview 6.2 Introduction 6.3 Variance function models 6.4 Repeated measurements data 6.5 Paired measurements data 6.6 Chapter summary 6.7 Technical details 6.8 Bibliographic note Exercises Chapter 7: Data from Multiple Methods 7.1 Preview 7.2 Introduction 7.3 Displaying data 7.4 Example datasets 7.5 Modeling unreplicated data 7.6 Modeling repeated measurements data 7.7 Model fitting and evaluation 7.8 Evaluation of similarity and agreement 7.9 Evaluation of repeatability 7.10 Case studies 7.11 Chapter summary 7.12 Technical details 7.13 Bibliographic note Exercises Chapter 8: Data with Covariates 8.1 Preview 8.2 Introduction 8.3 Modeling of data 8.4 Evaluation of similarity, agreement and repeatability 8.5 Case study 8.6 Chapter summary 8.7 Technical details 8.8 Bibliographic note Exercises Chapter 9: Longitudinal Data 9.1 Preview 9.2 Introduction 9.3 Modeling of data 9.4 Evaluation of similarity and agreement 9.5 Case study 9.6 Chapter summary 9.7 Technical details 9.8 Bibliographic note Exercises Chapter 10: A Nonparametric Approach 10.1 Preview 10.2 Introduction 10.3 The statistical functional approach 10.4 Evaluation of similarity and agreement 10.5 Case studies 10.6 Chapter summary 10.7 Technical details 10.8 Bibliographic note Exercises Chapter 11: Sample Size Determination 11.1 Preview 11.2 Introduction 11.3 The sample size methodology 11.4 Case study 11.5 Chapter summary 11.6 Bibliographic note Exercises Chapter 12: Categorical Data 12.1 Preview 12.2 Introduction 12.3 Experimental setups and examples 12.4 Cohen's kappa coefficient for dichotomous data 12.5 Kappa type measures for more than two categories 12.6 Case studies 12.7 Models for exploring agreement 12.8 Discussion 12.9 Chapter summary 12.10 Bibliographic note Exercises References Dataset List Index
Preface Chapter 1: Introduction 1.1 Preview 1.2 Notational conventions 1.3 Basic characteristics of a measurement method 1.4 Method comparison studies 1.5 Meaning of agreement 1.6 A measurement error model 1.7 Similarity versus agreement 1.8 A toy example 1.9 Controversies and our view 1.10 Concepts related to agreement 1.11 Role of confidence intervals and hypotheses testing 1.12 Common models for paired measurements data 1.13 The Bland Altman plot 1.14 Common regression approaches 1.15 Inappropriate use of common tests in method comparison studies 1.16 Key steps in the analysis of method comparison data 1.17 Chapter summary 1.18 Bibliographic note Exercises Chapter 2: Common Approaches for Measuring Agreement 2.1 Preview 2.2 Introduction 2.3 Mean squared deviation 2.4 Concordance correlation coefficient 2.5 A digression: Tolerance and prediction intervals 2.6 Lin's probability criterion and Bland Altman criterion 2.7 Limits of agreement 2.8 Total deviation index and coverage probability 2.9 Inference on agreement measures 2.10 Chapter summary 2.11 Bibliographic note Exercises Chapter 3: A General Approach for Modeling and Inference 3.1 Preview 3.2 Mixed effects models 3.3 A large-sample approach for inference 3.4 Modeling and analysis of method comparison data 3.5 Chapter summary 3.6 Bibliographic note Exercises Chapter 4: Paired Measurements Data 4.1 Preview 4.2 Modeling of data 4.3 Evaluation of similarity and agreement 4.4 Case studies 4.5 Chapter summary 4.6 Technical details 4.7 Bibliographic note Exercises Chapter 5: Repeated Measurements Data 5.1 Preview 5.2 Introduction 5.3 Displaying data 5.4 Modeling of data 5.5 Evaluation of similarity and agreement 5.6 Evaluation of repeatability 5.7 Case studies 5.8 Chapter summary 5.9 Technical details 5.10 Bibliographic note Exercises Chapter 6: Heteroscedastic Data 6.1 Preview 6.2 Introduction 6.3 Variance function models 6.4 Repeated measurements data 6.5 Paired measurements data 6.6 Chapter summary 6.7 Technical details 6.8 Bibliographic note Exercises Chapter 7: Data from Multiple Methods 7.1 Preview 7.2 Introduction 7.3 Displaying data 7.4 Example datasets 7.5 Modeling unreplicated data 7.6 Modeling repeated measurements data 7.7 Model fitting and evaluation 7.8 Evaluation of similarity and agreement 7.9 Evaluation of repeatability 7.10 Case studies 7.11 Chapter summary 7.12 Technical details 7.13 Bibliographic note Exercises Chapter 8: Data with Covariates 8.1 Preview 8.2 Introduction 8.3 Modeling of data 8.4 Evaluation of similarity, agreement and repeatability 8.5 Case study 8.6 Chapter summary 8.7 Technical details 8.8 Bibliographic note Exercises Chapter 9: Longitudinal Data 9.1 Preview 9.2 Introduction 9.3 Modeling of data 9.4 Evaluation of similarity and agreement 9.5 Case study 9.6 Chapter summary 9.7 Technical details 9.8 Bibliographic note Exercises Chapter 10: A Nonparametric Approach 10.1 Preview 10.2 Introduction 10.3 The statistical functional approach 10.4 Evaluation of similarity and agreement 10.5 Case studies 10.6 Chapter summary 10.7 Technical details 10.8 Bibliographic note Exercises Chapter 11: Sample Size Determination 11.1 Preview 11.2 Introduction 11.3 The sample size methodology 11.4 Case study 11.5 Chapter summary 11.6 Bibliographic note Exercises Chapter 12: Categorical Data 12.1 Preview 12.2 Introduction 12.3 Experimental setups and examples 12.4 Cohen's kappa coefficient for dichotomous data 12.5 Kappa type measures for more than two categories 12.6 Case studies 12.7 Models for exploring agreement 12.8 Discussion 12.9 Chapter summary 12.10 Bibliographic note Exercises References Dataset List Index
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