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.

Measuring Agreement: Models, Methods, and Applications

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£99.95

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Hardback by Pankaj K. Choudhary , Haikady N. Nagaraja

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Short Description:

Presents statistical methodologies for analyzing common types of data from method comparison experiments and illustrates their applications through detailed case... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 02/01/2018
    ISBN13: 9781118078587, 978-1118078587
    ISBN10: 1118078586

    Number of Pages: 360

    Non Fiction , Mathematics & Science , Education

    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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