Regression Models for the Comparison of Measurement Methods

Beschreibung

This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others – a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine. Methods comparison involves a non-standard regression problem; when a method is to be tested in a laboratory, it may be used on samples of suitable reference material, but frequently it is used with other methods on a range of suitable materials whose concentration levels are not known precisely. By presenting a sound statistical background not found in other books for the type of problem addressed, this book complements and extends topics discussed in the current literature. It highlights the applications of the presented techniques with the support of computer routines implemented using the R language, with examples worked out step-by-step. This book is a valuable resource for applied statisticians, practitioners, laboratoryscientists, geostatisticians, process engineers, geologists and graduate students.

Offers a sound statistical background not found in other books for the type of problems addressed, like an explicit formulation of the regression model and the proposal of the statistical test for detection of bias Includes comparisons of more than two methods, and analyses of model adequacy and sensitivity, topics not commonly found in the current literature Features R package with implementing techniques and examples to help practitioners analyze their own data sets

Autor*in

Heleno Bolfarine

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“This book is a successful compilation of such developments in the last two decades and presents them concisely to help researchers and practitioners. … The book requires the reader to have a solid background in mathematical statistics and detailed knowledge of areas such as measurement error models. It also provides a platform for new entrants in this area to begin their research with complete references and updated developments in one place.” (Shalabh, Mathematical Reviews, April, 2022)
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