HANDBOOK OF MEASUREMENT ERROR MODELS (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

Yi, Gracy Y. [Editor] Delaigle, Aurore [Editor] Gustafson, Paul [Editor]

ISBN 10: 1138106402 / ISBN 13: 9781138106406

Published by CRC Press, Boca Raton, Florida, 2021

About this Item

Large Octavo, xiv, 577 pages. In Good condition. Grey and dark blue spine with white and dark blue lettering. Boards have mild shelving wear, mild finger-staining, scratches along front board joint, a small tear along rear board joint along tail, mild wear along rear board edges, mild wear along spine head and tail, and boards are shaken. Textblock has mild wear along head and tail edges of pages 151-205, mild staining along rear end-page and pastedown, mild wear along front and rear pastedowns, moderate wear along head and tail edges, and mild staining along edges. Shelved in ND-C. 1379688. FP New Rockville Stock.

Seller Inventory # 1379688

Bibliographic Details

• Title: HANDBOOK OF MEASUREMENT ERROR MODELS (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
• Publisher: CRC Press, Boca Raton, Florida
• Publication Date: 2021
• Language: English
• ISBN 10: 1138106402
• ISBN 13: 9781138106406
• Binding: Hardcover
• Edition: First Edition.
• Seller catalogs:
  • Sciences, Math, Medicine, & Natural History

About this title

Synopsis

Measurement error arises ubiquitously in applications and has been of long-standing concern in a variety of fields, including medical research, epidemiological studies, economics, environmental studies, and survey research. While several research monographs are available to summarize methods and strategies of handling different measurement error problems, research in this area continues to attract extensive attention.

The Handbook of Measurement Error Models provides overviews of various topics on measurement error problems. It collects carefully edited chapters concerning issues of measurement error and evolving statistical methods, with a good balance of methodology and applications. It is prepared for readers who wish to start research and gain insights into challenges, methods, and applications related to error-prone data. It also serves as a reference text on statistical methods and applications pertinent to measurement error models, for researchers and data analysts alike.

Features:

• Provides an account of past development and modern advancement concerning measurement error problems
• Highlights the challenges induced by error-contaminated data
• Introduces off-the-shelf methods for mitigating deleterious impacts of measurement error
• Describes state-of-the-art strategies for conducting in-depth research

About the Author

Grace Y. Yi is Professor of Statistics at the University of Western Ontario where she holds a Tier I Canada Research Chair in Data Science. She is a Fellow of the Institute of Mathematical Statistics (IMS), a Fellow of the American Statistical Association (ASA), and an Elected Member of the International Statistical Institute (ISI). She authored the monograph Statistical Analysis with Measurement Error or Misclassification (2017, Springer).

Aurore Delaigle is Professor at the School of Mathematics and Statistics at the University of Melbourne. She is a Fellow of the Australian Academy of Science, a Fellow of the Institute of Mathematical Statistics (IMS), a Fellow of the American Statistical Association (ASA), and an Elected Member of the International Statistical Institute (ISI). She is a past recipient of the George W. Snedecor Award from the Committee of Presidents of Statistical Societies (COPSS) and of the Moran Medal from the Australian Academy of Science.

Paul Gustafson is Professor and Head of the Department of Statistics at the University of British Columbia. He is a Fellow of the American Statistical Association, the 2020 Gold Medalist of the Statistical Society of Canada, and the author of the monograph Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments (2004, Chapman and Hall, CRC Press).