Overview
- 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
Part of the book series: Springer Series in Statistics (SSS)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Reviews
“This book successfully collects, compiles, organizes, and presents the literature on the newly developed and earlier existing topics of measurement error models and misclassification in a crisp and concise way without losing the clarity in understanding. … I am sure it will stimulate researchers in and newcomers to this area.” (Shalabh, Mathematical Reviews, June, 2018)
“This book covers a wide range of topics in a unified framework where measurement error and misclassification problems receive careful treatments, from both practical and theoretical points of view. … This book can serve well as a textbook for a graduate-level course on measurement error in a (bio)statistics department … . Besides ample real life applications presented in the book, from which students can appreciate practical relevance of measurement error problems … .” (Xianzheng Huang, Journal of the American Statistical Association JASA, Vol. 113 (522), 2018)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Statistical Analysis with Measurement Error or Misclassification
Book Subtitle: Strategy, Method and Application
Authors: Grace Y. Yi
Series Title: Springer Series in Statistics
DOI: https://doi.org/10.1007/978-1-4939-6640-0
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2017
Hardcover ISBN: 978-1-4939-6638-7Published: 03 August 2017
Softcover ISBN: 978-1-4939-8257-8Published: 03 August 2018
eBook ISBN: 978-1-4939-6640-0Published: 02 August 2017
Series ISSN: 0172-7397
Series E-ISSN: 2197-568X
Edition Number: 1
Number of Pages: XXVII, 479
Number of Illustrations: 15 b/w illustrations, 1 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Life Sciences, Medicine, Health Sciences, Biostatistics, Epidemiology