
Statistical Evaluation of Measurement Errors
Graham Dunn(Author)
Wiley (Publisher)
1st Edition
Published on 26. March 2004
Book
Hardback
226 pages
978-0-470-68215-9 (ISBN)
Description
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.
More details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 17 mm
Weight
510 gr
ISBN-13
978-0-470-68215-9 (9780470682159)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Book
03/2004
2nd Edition
Hodder Arnold
€93.10
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Person
Graham Dunn is the author of Statistical Evaluation of Measurement Errors, published by Wiley.
Content
Setting the Scene Sources of Variation
Method Comparison 1: Paired Observations
Method Comparison 2: More Informative Designs
Methods for Categorical (binary) data
Appendix 1. EQS Programs (chapter 3)
Appendix 2. Selected EQS Programs (chapter 4)
Appendix 3. Selected Gllamm Programs
Appendix 4. Selected Mplus Programs
Appendix 5. Selected Mplus Runs to Fit latent Class Models
Appendix 6. Web-based Resources and Software Packages
Method Comparison 1: Paired Observations
Method Comparison 2: More Informative Designs
Methods for Categorical (binary) data
Appendix 1. EQS Programs (chapter 3)
Appendix 2. Selected EQS Programs (chapter 4)
Appendix 3. Selected Gllamm Programs
Appendix 4. Selected Mplus Programs
Appendix 5. Selected Mplus Runs to Fit latent Class Models
Appendix 6. Web-based Resources and Software Packages