This is a practically oriented introduction to the realiability of measurements. One of the implicit themes is that the measurement models and the statistical methods used in the assessment of accuracy are common to virtually all fields of scientific endeavor. For this latest edition, Dunn has integrated the design and analysis of this type of study to make it easier and included new data sets and examples. Also, he has included the hot new topics of Monte Carlo simulations and the bootstrap, making this an essential guide for all students and scholars of applied statistics.
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The statistical methods used to evaluate and compare different methods of measurement are a vital common component of all methods of scientific research. This book provides a practically orientated guide to the statistical models used in the evaluation of measurement errors with a wide variety of illustrative examples taken from across the sciences. After introducing basic concepts, such as precision, reproducibility and reliability, a detailed discussion of the sources of variability of measurements and associated variance components models is provided. The central chapters deal with the design and analysis of method comparison studies (concentrating primarily on quantitative measurements) ranging from simple paired comparisons to more complex studies involving three or more methods. This leads on to a review of methods for categorical measures.
Graham Dunn is Professor of Biomedical Statistics at the University of Manchester.
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Descripción Hodder Education Publishers, 2004. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería M0340760702