Measuring Agreement Models, Methods, and Applications
Measuring Agreement Models, Methods, and Applications
- ISBN 13:
9781118078587
- ISBN 10:
1118078586
- Edition: 1st
- Format: Hardcover
- Copyright: 11/13/2017
- Publisher: Wiley
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Summary
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.