Measurement Error And Misclassification
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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
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.
Correcting For Measurement Error And Misclassification Using General Location Models
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Author : Muhire Honorine Kwizera
language : en
Publisher:
Release Date : 2023
Correcting For Measurement Error And Misclassification Using General Location Models written by Muhire Honorine Kwizera and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
The proposed method uses observed data from both the calibration and main study samples and incorporates relationships among all variables in measurement error adjustment, unlike existing methods that only use the calibration data for model estimation. We assume by strong nondifferential measurement error (sNDME) that the measurement error is independent of all the error-free variables given the true value of the error-prone variable. The sNDME assumption allows us to identify our model parameters. We show through simulations that the proposed method yields reduced bias, smaller mean squared error, and interval coverage closer to the nominal level compared to existing methods in regression settings. Furthermore, this improvement is pronounced with increased measurement error, higher correlation between covariates, and stronger covariate effects. We apply the new method to the New York City Neighborhood Asthma and Allergy Study to examine the association between indoor allergen concentrations and asthma morbidity among urban asthmatic children.
Measurement Error And Misclassification
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Author : Arie Kapteyn
language : en
Publisher:
Release Date : 2008
Measurement Error And Misclassification written by Arie Kapteyn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
The authors provide both a theoretical and empirical analysis of the relation between register and survey data. By distinguishing between different sources of deviations between survey and register data the authors are able to reproduce several stylized facts in the literature. In doing so, they deviate from the almost universal assumption that the register data represent the truth. They illustrate the implications of different error sources for estimation in (simple) econometric models. The analysis is applied to Swedish data that have been collected for a validation study as part of a larger European health and retirement study (SHARE: Survey of Health, Ageing, and Retirement in Europe). Thus this paper makes two contributions: (1) it adds to the limited number of empirical validation studies of earnings measurement in surveys and (2) it shows the sensitivity of some findings in the literature for the assumption that register data represent the truth. They find in particular that the common finding of substantial mean reversion in survey data largely goes away once we allow for a richer error structure.
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.
Mind The Gap
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Author : Mochen Yang
language : en
Publisher:
Release Date : 2017
Mind The Gap written by Mochen Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
The application of predictive data mining techniques in Information Systems research has grown in recent years, likely due to their effectiveness and scalability in extracting information from large amounts of data. A number of scholars have sought to combine data mining with traditional econometric analyses. Typically, data mining methods are first used to generate new variables (e.g., text sentiment), which are added into subsequent econometric models as independent regressors. However, because prediction is almost always imperfect, variables generated from the first stage data mining models inevitably contain measurement error or misclassification. These errors, if ignored, can introduce systematic biases into the second stage econometric estimations and threaten the validity of statistical inference. In this commentary, we examine the nature of this bias, both analytically and empirically, and show that it can be severe even when data mining models exhibit relatively high performance. We then show that this bias becomes increasingly difficult to anticipate as the functional form of the measurement error grows more complex, or as the number of covariates in the econometric model increases. We review several methods for error correction and focus on two simulation-based methods, SIMEX and MC-SIMEX, which can be easily parameterized using standard performance metrics from data mining models, such as error variance or the confusion matrix, and can be applied under a wide range of econometric specifications. Finally, we demonstrate the effectiveness of SIMEX and MC-SIMEX by simulations and subsequent application of the methods to econometric estimations employing variables mined from three real world datasets related to travel, social networking, and crowdfunding campaign websites.
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)"--
Linear And Logistic Regression With Measurement Erro And Misclassification In Covariates
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Author : Hok Laam Cheng
language : en
Publisher:
Release Date : 2020
Linear And Logistic Regression With Measurement Erro And Misclassification In Covariates written by Hok Laam Cheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
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
Measurement Error And Misclassification In Interval Censored Life History Data
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Author : Bethany Joy Giddings White
language : en
Publisher:
Release Date : 2007
Measurement Error And Misclassification In Interval Censored Life History Data written by Bethany Joy Giddings White and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.