Springer Series in Statistics

Statistical Analysis with Measurement Error or Misclassification

Strategy, Method and Application

Authors: Yi, Grace Y.

  • Brings together assorted methods concerning measurement error or misclassification in a single text, including updates of recent developments for a variety of settings
  • Presents both statistical theory and applications in a coherent and systematic manner
  • Highlights the essence of commonly used modeling and inference strategies 
  • Includes self-contained material of an individual topic in each chapter
  • Provides exercises, discussion questions, and bibliographic notes at the end of each chapter to supplement the development in the text
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eBook $99.00
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  • ISBN 978-1-4939-6640-0
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Hardcover $129.00
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  • ISBN 978-1-4939-6638-7
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About this book

This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification:  Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems.
Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods—such as likelihood and estimating function theory—or modeling schemes in varying settings—such as survival analysis and longitudinal data analysis—can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material.  The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods.
This text can serve as a reference book for researchers  interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data.
Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute. 

About the authors

Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. Her broad research interests include measurement error models, missing data problems, high dimensional data analysis, survival data and longitudinal data analysis, estimating function and likelihood methods, and medical applications. Prof. Yi received her Ph.D. in Statistics from the University of Toronto in 2000.  She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She was a recipient of the prestigious University Faculty Award granted by the Natural Sciences and Engineering Research Council of Canada (NSERC). She serves as an associate editor for several statistical journals, and is the editor of the Canadian Journal of Statistics (2016-2018). She is a Fellow of the American Statistical Association, and an Elected Member of the International Statistical Institute. She is President of the Biostatistics Section of the Statistical Society of Canada in 2016, and the Founder and Chair of the first chapter (Canada Chapter) of the  International Chinese Statistical Association. 

Table of contents (9 chapters)

  • Inference Framework and Method

    Yi, Grace Y.

    Pages 1-41

  • Measurement Error and Misclassification: Introduction

    Yi, Grace Y.

    Pages 43-85

  • Survival Data with Measurement Error

    Yi, Grace Y.

    Pages 87-150

  • Recurrent Event Data with Measurement Error

    Yi, Grace Y.

    Pages 151-191

  • Longitudinal Data with Covariate Measurement Error

    Yi, Grace Y.

    Pages 193-256

Buy this book

eBook $99.00
price for USA (gross)
  • ISBN 978-1-4939-6640-0
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $129.00
price for USA
  • ISBN 978-1-4939-6638-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Statistical Analysis with Measurement Error or Misclassification
Book Subtitle
Strategy, Method and Application
Authors
Series Title
Springer Series in Statistics
Copyright
2017
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC
eBook ISBN
978-1-4939-6640-0
DOI
10.1007/978-1-4939-6640-0
Hardcover ISBN
978-1-4939-6638-7
Series ISSN
0172-7397
Edition Number
1
Number of Pages
XXVII, 479
Number of Illustrations and Tables
15 b/w illustrations, 1 illustrations in colour
Topics