Statistical Analysis With Measurement Error Or Misclassification
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Statistical Analysis With Measurement Error Or Misclassification
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Author : Grace Y. Yi
language : en
Publisher:
Release Date : 2017
Statistical Analysis With Measurement Error Or Misclassification written by Grace Y. Yi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Epidemiology categories.
Measurement Error And Misclassification In Statistics And Epidemiology
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Author : Paul Gustafson
language : en
Publisher: CRC Press
Release Date : 2003-09-25
Measurement Error And Misclassification In Statistics And Epidemiology written by Paul Gustafson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-25 with Mathematics categories.
Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassi
Handbook Of Measurement Error Models
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Author : Grace Y. Yi
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2021-10-17
Handbook Of Measurement Error Models written by Grace Y. Yi and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-17 with Mathematics categories.
"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)"--
Statistical Analysis With Measurement Error Or Misclassification
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Author : Grace Y. Yi
language : en
Publisher: Springer
Release Date : 2017-08-02
Statistical Analysis With Measurement Error Or Misclassification written by Grace Y. Yi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-02 with Mathematics categories.
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.
Measurement Errors In Surveys
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Author : Paul P. Biemer
language : en
Publisher: John Wiley & Sons
Release Date : 2013-08-12
Measurement Errors In Surveys written by Paul P. Biemer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-12 with Mathematics categories.
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book will be an aid to survey statisticians and to research workers who must work with survey data." –Short Book Reviews, International Statistical Institute Measurement Errors in Surveys documents the current state of the field, reports new research findings, and promotes interdisciplinary exchanges in modeling, assessing, and reducing measurement errors in surveys. Providing a fundamental approach to measurement errors, the book features sections on the questionnaire, respondents and responses, interviewers and other means of data collection, the respondent-interviewer relationship, and the effects of measurement errors on estimation and data analysis.
Measurement Error
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Author : John P. Buonaccorsi
language : en
Publisher: CRC Press
Release Date : 2010-03-02
Measurement Error written by John P. Buonaccorsi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-02 with Mathematics categories.
Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu
Applying Quantitative Bias Analysis To Epidemiologic Data
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Author : Timothy L. Lash
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-14
Applying Quantitative Bias Analysis To Epidemiologic Data written by Timothy L. Lash and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-14 with Medical categories.
Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.
Measurement Error In Nonlinear Models
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Author : Raymond J. Carroll
language : en
Publisher: CRC Press
Release Date : 2006-06-21
Measurement Error In Nonlinear Models written by Raymond J. Carroll and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-21 with Mathematics categories.
It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex
Statistical Analysis Of Measurement Errors
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Author : John L. Jaech
language : en
Publisher:
Release Date : 1985-09-03
Statistical Analysis Of Measurement Errors written by John L. Jaech and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-09-03 with Mathematics categories.
In this book the author has developed a general model of statistical inference based on maximum likelihood for experimental situations in which a multiple number of items are each measured by several different measurement methods.
Measurement Error In Nonlinear Models
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Author : Raymond J. Carroll
language : en
Publisher: CRC Press
Release Date : 1995-07-06
Measurement Error In Nonlinear Models written by Raymond J. Carroll and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-07-06 with Mathematics categories.
This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.