Measuring Agreement: Models, Methods, and Applications (Wiley Series in Probability and Statistics)

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Measuring Agreement: Models, Methods, and Applications (Wiley Series in Probability and Statistics) image
ISBN-10:

1118078586

ISBN-13:

9781118078587

Edition: 1
Released: Nov 13, 2017
Publisher: wiley
Format: Hardcover, 360 pages

Description:

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.

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