Title: Regression Models for the Comparison of Measurement Methods (SpringerBriefs in Statistics)
Publisher: Springer
Publication Date: 2020
Language: English
ISBN 10: 3030579344
ISBN 13: 9783030579340
Binding: Soft cover
Condition: New

About this title

Synopsis

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.

About the Author

Heleno Bolfarine is a Full Professor at the Instituto de Matem�tica e Estat�stica of the Universidade de S�o Paulo, SP, Brazil. He received his PhD in Probability and Statistics from the University of California at Berkeley, USA. Prof. Bolfarine has published more than 190 articles in respected ,international, peer-reviewed journals, and co-authored the book “Prediction Theory for Finite Populations”, published by Springer. His research focuses on statistical inference, more specifically on mixed models and finite populations.

M�rio de Castro is an Associate Professor at the Instituto de Ci�ncias Matem�ticas e de Computa��o of the Universidade de S�o Paulo at S�o Carlos, SP, Brazil. He completed his PhD studies in Statistics at the Instituto de Matem�tica e Estat�stica, Universidade de S�o Paulo, Brazil, and postdoctoral studies at the University of Connecticut, USA. His research interests include measurement errors, survival analysis and data modelingfor counting. He has authored or co-authored more than 60 papers.

Manuel Galea is an Associate Professor at the Pontificia Universidad Cat�lica de Chile. He received his PhD in Statistics from the Instituto de Matem�tica e Estat�stica, Universidade de S�o Paulo, Brazil. His fields of research include inference and influence diagnosis in measurement error models under elliptical distributions. Dr. Galea has published more than 70 papers, as author or co-author.

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