Handbook of measurement error /
"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 a...
Saved in:
Group Author: | ; ; |
---|---|
Published: |
CRC Press,
|
Publisher Address: | Boca Raton, FL : |
Publication Dates: | 2021. |
Literature type: | Book |
Language: | English |
Edition: | First edition. |
Subjects: | |
Summary: |
"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 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. 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)"-- |
Carrier Form: | xiv, 577 pages : illustrations ; 26 cm |
Bibliography: | Includes bibliographical references and index. |
ISBN: |
9781138106406 1138106402 |
Index Number: | QA275 |
CLC: | O241.1-62 |
Call Number: | O241.1-62/H236 |
Contents: | Measurement error models -- a brief account of past developments and modern advancements / Grace Y. Yi/Jeffrey S Buzas -- The impact of unacknowledged measurement error / Paul Gustafson -- Identifiability in measurement error / Liqun Wang -- Partial learning of misclassification parameters / Paul Gustafson -- Using instrumental variables to estimate models with mismeasured regressors / Arthur Lewbel -- Likelihood methods for measurement error and misclassification / Grace Y. Yi -- Regression calibration for covariate measurement error / Pamela A. Shaw -- Conditional and corrected score methods / David M. Zucker -- Semiparametric methods for measurement error and misclassification / Yanyuan Ma -- Deconvolution kernel density estimation / Aurore Delaigle -- Nonparametric deconvolution by Fourier transformation and other related approaches / Yicheng Kang/Peihua Qiu -- Deconvolution with unknown error distribution / Aurore Delaigle, Ingrid Van Keilegom -- Nonparametric inference methods for Berkson errors / Weixing Song -- Nonparametric measurement errors models for regression / Tatiyana Apanasovich/Hua Liang -- Covariate measurement error in survival data / Jeffrey S. Buzas -- Mixed effects models with measurement errors in time-dependent covariates / Lang Wu/Wei Liu/Hongbin Zhang -- Estimation in mixed-effects models with measurement error -- Liqun Wang -- Measurement error in dynamic models -- John P. Buonaccorsi -- Spatial exposure measurement error in environmental epidemiology -- Howard H. Chang, Joshua P. Keller -- Measurement error as a missing data problem -- Ruth H. Keogh, Jonathan W. Bartlett -- Measurement error in causal inference -- Linda Valeri -- Measurement error and misclassification in meta-analysis -- Annamaria Guolo -- Bayesian adjustment for misclassification -- James D. Stamey and John W. Seaman Jr. -- Bayesian approaches for handling covariate measurement error -- Samiran Sinha. |