Comparing Clinical Measurement Methods - (Statistics in Practice) by Bendix Carstensen (Hardcover)

Book Synopsis

This book provides a practical guide to analysis of simple and complex method comparison data, using Stata, SAS and R. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty.

• Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods.
• Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software.
• Illustrated throughout with computer examples in R.
• Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area.
• Examples in SAS and Stata for the most common situations are also provided.
• Written by an acknowledged expert on the subject, with a long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject.

Biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations will benefit from this book. Students of statistics, biostatistics, and the chemical sciences will also find this book useful.

From the Back Cover

This book provides a practical guide to analysis of simple and complex method comparison data. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty.

Key features:

• Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods.
• Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software.
• Illustrated throughout with computer examples in R.
• Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area.
• Includes examples in SAS and Stata for the most common situations.

Written by an acknowledged expert on the subject, with long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject, this book will benefit biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations. Students of statistics, biostatistics, and the chemical sciences will also find it useful.

Review Quotes

"This book presents useful information about the complexities of method comparison studies specific to clinical/biomedical research. . . I would consider using it in a course intended for students seeking advanced degrees in biostatistics and epidemiology." (Doody's, 16 September 2011)

"In conclusion, this book provides a statistical modeling approach to the comparison of clinical measurements. The modeling aspects will be particularly appreciated by researchers and others mathematically sophisticated, while the computer code at the end of the book will be useful for practitioners wishing to implement the methods." (Journal of Biopharmaceutical Statistics, January 2011)

About the Author

Bendix Carstensen, Senior Statistician at Steno Diabetes Center, Denmark; also of Department of Biostatistics, Copenhagen, Denmark
Bendix Carstensen has been working as a biostatistician in research institutions since 1983. During the last 10 years he has taught courses for medical PhD-students at the Department of Biostatistics at the University of Copenhagen and has been involved in the delivery of overseas courses in epidemiology and the comparison of measurement methods.