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Author: Grace Y. Yi Publisher: Springer ISBN: 1493966405 Category : Mathematics Languages : en Pages : 497
Book Description
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.
Author: Grace Y. Yi Publisher: Springer ISBN: 1493966405 Category : Mathematics Languages : en Pages : 497
Book Description
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.
Author: Graham Dunn Publisher: Wiley ISBN: 9780470682159 Category : Mathematics Languages : en Pages : 0
Book Description
The statistical methods used to evaluate and compare different methods of measurement are a vital common component of all methods of scientific research. This book provides a practically orientated guide to the statistical models used in the evaluation of measurement errors with a wide variety of illustrative examples taken from across the sciences. After introducing basic concepts, such as precision, reproducibility and reliability, a detailed discussion of the sources of variability of measurements and associated variance components models is provided. The central chapters deal with the design and analysis of method comparison studies (concentrating primarily on quantitative measurements) ranging from simple paired comparisons to more complex studies involving three or more methods. This leads on to a review of methods for categorical measures.
Author: Graham Dunn Publisher: Halsted Press ISBN: 9780470220658 Category : Mathematics Languages : en Pages : 198
Book Description
Concerned with statistical problems of assessing the dependability, precision and bias of measurements. Using a practical approach, it features enough theoretical material enabling users of relevant techniques to understand why and how the vast array of concepts and methods can be applied. Coverage includes analysis of variance, linear regression and chi-square tests for two-way contingency tables.
Author: John P. Buonaccorsi Publisher: CRC Press ISBN: 1420066587 Category : Mathematics Languages : en Pages : 465
Book Description
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
Author: Philip J. Brown Publisher: American Mathematical Soc. ISBN: 0821851179 Category : Mathematics Languages : en Pages : 262
Book Description
Measurement error models describe functional relationships among variables observed, subject to random errors of measurement. This book treats general aspects of the measurement problem and features a discussion of the history of measurement error models.
Author: Madhu Viswanathan Publisher: SAGE ISBN: 9781412906425 Category : Psychology Languages : en Pages : 460
Book Description
"Measurement Error and Research Design is an ideal text for research methods courses across the social sciences, especially those in which a primer on measurement is needed. For the novice researcher, this book facilitates understanding of the basic principles required to design measures and methods for empirical research. For the experienced researcher, this book provides an in-depth analysis and discussion of the essence of measurement error and the procedures to minimize it. Most important, the book's unique approach bridges measurement and methodology through clear illustrations of the intangibles of scientific research."--BOOK JACKET.
Author: Grace Y. Yi Publisher: CRC Press ISBN: 1351588591 Category : Mathematics Languages : en Pages : 648
Book Description
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 Models 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
Author: Paul P. Biemer Publisher: John Wiley & Sons ISBN: 1118150376 Category : Mathematics Languages : en Pages : 804
Book Description
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.
Author: Chi-Lun Cheng Publisher: Wiley ISBN: 9780470711064 Category : Mathematics Languages : en Pages : 0
Book Description
Providing a general survey of the theory of measurement error models, including the functional, structural, and ultrastructural models, this book is written in the of the Kendall and Stuart Advanced Theory of Statistics set and, like that series, includes exercises at the end of the chapters. The goal is to emphasize the ideas and practical implications of the theory in a style that does not concentrate on the theorem-proof format.
Author: Grace Y. Yi
Author: Grace Y. Yi
Author: Graham Dunn
Author: Graham Dunn
Author: John P. Buonaccorsi
Author: Philip J. Brown
Author: Madhu Viswanathan
Author: Grace Y. Yi
Author: John Robert Taylor
Author: Paul P. Biemer
Author: Chi-Lun Cheng