Measuring Agreement: Models, Methods, and Applications

<p><b>Presents statistical methodologies for analyzing common types of data from method comparison experiments and illustrates their applications through detailed case studies</b></p> <p><i>Measuring Agreement: Models, Methods, and Applications </i>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:</p> <p>• Strikes a balance between theory and applications</p> <p>• Presents parametric as well as nonparametric methodologies</p> <p>• Provides a concise introduction to Cohen’s kappa coefficient and other measures of agreement for binary and categorical data</p> <p>• Discusses sample size determination for trials on measuring agreement</p> <p>• Contains real-world case studies and exercises throughout</p> <p>• Provides a supplemental website containing the related datasets and R code</p> <p><i>Measuring Agreement: Models, Methods, and Applications </i>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.</p>