Handbook of Measurement Error Models, Grace Y. Yi, Aurore Delaigle, Paul Gustafson
Автор: Peacock, Janet L. Название: Oxford handbook of medical statistics 2e ISBN: 0198743580 ISBN-13(EAN): 9780198743583 Издательство: Oxford Academ Рейтинг: Цена: 5384.00 р. Наличие на складе: Есть (2 шт.) Описание: This new edition of the Oxford Handbook of Medical Statistics provides doctors and medical students with a clear and concise explanation of statistical methods. It is an accessible and thorough account of a complex subject, and the previous edition has been described by readers as a `statistical Bible`.
Автор: Kawachi I. Название: Oxford handbook of public health practice 4e ISBN: 0198800126 ISBN-13(EAN): 9780198800125 Издательство: Oxford Academ Рейтинг: Цена: 5701.00 р. Наличие на складе: Есть (1 шт.) Описание: This is the quick, go-to-reference book for public health trainees and practitioners. It distils information from the core disciplines of public health into one concise volume. It is also packed with practical tips on professional competencies and skills development, as well as new emerging topics.
Автор: Ward Helen, Toledano Mireille, Elliott Paul Название: Oxford Handbook of Epidemiology for Clinicians ISBN: 0198529880 ISBN-13(EAN): 9780198529880 Издательство: Oxford Academ Рейтинг: Цена: 5384.00 р. Наличие на складе: Поставка под заказ.
Описание: The Oxford Handbook of Epidemiology for Clinicians is the essential reference for all clinicians and junior doctors who need to apply clinical evidence in everyday practice.
Автор: Sergii Masiuk, Alexander Kukush, Sergiy Shklyar, M Название: Radiation Risk Estimation: Based on Measurement Error Models ISBN: 3110441802 ISBN-13(EAN): 9783110441802 Издательство: Walter de Gruyter Рейтинг: Цена: 22305.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.
Contents:
Part I - Estimation in regression models with errors in covariates
Measurement error models
Linear models with classical error
Polynomial regression with known variance of classical error
Nonlinear and generalized linear models
Part II Radiation risk estimation under uncertainty in exposure doses
Overview of risk models realized in program package EPICURE
Estimation of radiation risk under classical or Berkson multiplicative error in exposure doses
Radiation risk estimation for persons exposed by radioiodine as a result of the Chornobyl accident
Elements of estimating equations theory
Consistency of efficient methods
Efficient SIMEX method as a combination of the SIMEX method and the corrected score method
Application of regression calibration in the model with additive error in exposure doses
Описание: Inference Framework and Method.- Measurement Error and Misclassification: Introduction.- Survival Data with Measurement Error.- Recurrent Event Data with Measurement Error.- Longitudinal Data with Covariate Measurement Error.- Multi-State Models with Error-Prone Data.- Case-Control Studies with Measurement Error or Misclassification.- Analysis with Error in Responses.- Miscellaneous Topics.- Appendix.- References.
Описание: Addresses statistical challenges posed by inaccurately measuring explanatory variables, a common problem in biostatistics and epidemiology. This book explores both measurement error in continuous variables and misclassification in categorical variables. It is suitable for biostatisticians, epidemiologists, and students.
Автор: Bolfarine Heleno, de Castro Mбrio, Galea Manuel Название: Regression Models for the Comparison of Measurement Methods ISBN: 3030579344 ISBN-13(EAN): 9783030579340 Издательство: Springer Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others - a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine.
Описание: 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.
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