Statistical Analysis with Measurement Error or Misclassification

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Publisher : Springer
ISBN 13 : 1493966405
Total Pages : 497 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Statistical Analysis with Measurement Error or Misclassification by : Grace Y. Yi

Download or read book Statistical Analysis with Measurement Error or Misclassification written by Grace Y. Yi and published by Springer. This book was released on 2017-08-02 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Biometrika

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Publisher :
ISBN 13 :
Total Pages : 980 pages
Book Rating : 4.3/5 (117 download)

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Book Synopsis Biometrika by :

Download or read book Biometrika written by and published by . This book was released on 1991 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Interpretable Machine Learning

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Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Measurement Error Models

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Publisher : John Wiley & Sons
ISBN 13 : 0470317337
Total Pages : 474 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Measurement Error Models by : Wayne A. Fuller

Download or read book Measurement Error Models written by Wayne A. Fuller and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. "The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries." -Biometrics "Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book." -Journal of the American Statistical Association "The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection." -Technometrics " . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work." -Journal of Applied Econometrics Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.

Improving Diagnosis in Health Care

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Publisher : National Academies Press
ISBN 13 : 0309377722
Total Pages : 473 pages
Book Rating : 4.3/5 (93 download)

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Book Synopsis Improving Diagnosis in Health Care by : National Academies of Sciences, Engineering, and Medicine

Download or read book Improving Diagnosis in Health Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2015-12-29 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

On Estimation and Local Influence Analysis for Measurement Errors Models Under Heavy-tailed Distributions

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Publisher :
ISBN 13 :
Total Pages : 40 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis On Estimation and Local Influence Analysis for Measurement Errors Models Under Heavy-tailed Distributions by : V. H. Lachos

Download or read book On Estimation and Local Influence Analysis for Measurement Errors Models Under Heavy-tailed Distributions written by V. H. Lachos and published by . This book was released on 2008 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Mixed Effects Models for Complex Data

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Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Measurement Error in Nonlinear Models

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Publisher : CRC Press
ISBN 13 : 1420010131
Total Pages : 484 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Measurement Error in Nonlinear Models by : Raymond J. Carroll

Download or read book Measurement Error in Nonlinear Models written by Raymond J. Carroll and published by CRC Press. This book was released on 2006-06-21 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Linear Mixed Models

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Publisher : CRC Press
ISBN 13 : 1420010433
Total Pages : 376 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Linear Mixed Models by : Brady T. West

Download or read book Linear Mixed Models written by Brady T. West and published by CRC Press. This book was released on 2006-11-22 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-nav

Measurement Error and Research Design

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Publisher : SAGE
ISBN 13 : 9781412906425
Total Pages : 460 pages
Book Rating : 4.9/5 (64 download)

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Book Synopsis Measurement Error and Research Design by : Madhu Viswanathan

Download or read book Measurement Error and Research Design written by Madhu Viswanathan and published by SAGE. This book was released on 2005-02-10 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Mixed Models

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Publisher : John Wiley & Sons
ISBN 13 : 0471726133
Total Pages : 732 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rigorous, self-contained examination of mixed model theory and application Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. Paying special attention to algorithms and their implementations, the book discusses: Modeling of complex clustered or longitudinal data Modeling data with multiple sources of variation Modeling biological variety and heterogeneity Mixed model as a compromise between the frequentist and Bayesian approaches Mixed model for the penalized log-likelihood Healthy Akaike Information Criterion (HAIC) How to cope with parameter multidimensionality How to solve ill-posed problems including image reconstruction problems Modeling of ensemble shapes and images Statistics of image processing Major results and points of discussion at the end of each chapter along with "Summary Points" sections make this reference not only comprehensive but also highly accessible for professionals and students alike in a broad range of fields such as cancer research, computer science, engineering, and industry.

Skew-normal Distribution in Multivariate Null Intercept Measurement Error Model

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Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Skew-normal Distribution in Multivariate Null Intercept Measurement Error Model by :

Download or read book Skew-normal Distribution in Multivariate Null Intercept Measurement Error Model written by and published by . This book was released on 2007 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Regression Models for the Comparison of Measurement Methods

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Publisher : Springer Nature
ISBN 13 : 3030579352
Total Pages : 70 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Regression Models for the Comparison of Measurement Methods by : Heleno Bolfarine

Download or read book Regression Models for the Comparison of Measurement Methods written by Heleno Bolfarine and published by Springer Nature. This book was released on 2020-10-27 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Methods comparison involves a non-standard regression problem; when a method is to be tested in a laboratory, it may be used on samples of suitable reference material, but frequently it is used with other methods on a range of suitable materials whose concentration levels are not known precisely. By presenting a sound statistical background not found in other books for the type of problem addressed, this book complements and extends topics discussed in the current literature. It highlights the applications of the presented techniques with the support of computer routines implemented using the R language, with examples worked out step-by-step. This book is a valuable resource for applied statisticians, practitioners, laboratory scientists, geostatisticians, process engineers, geologists and graduate students.

Spatial Analysis Methods and Practice

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Publisher : Cambridge University Press
ISBN 13 : 1108498981
Total Pages : 535 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Spatial Analysis Methods and Practice by : George Grekousis

Download or read book Spatial Analysis Methods and Practice written by George Grekousis and published by Cambridge University Press. This book was released on 2020-06-11 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.

Handbook of Measurement Error Models

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Publisher : CRC Press
ISBN 13 : 1351588591
Total Pages : 648 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Handbook of Measurement Error Models by : Grace Y. Yi

Download or read book Handbook of Measurement Error Models written by Grace Y. Yi and published by CRC Press. This book was released on 2021-09-28 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Applied Linear Statistical Models

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Publisher : McGraw-Hill/Irwin
ISBN 13 : 9780072386882
Total Pages : 1396 pages
Book Rating : 4.3/5 (868 download)

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Book Synopsis Applied Linear Statistical Models by : Michael H. Kutner

Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.

Dissertation Abstracts International

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Publisher :
ISBN 13 :
Total Pages : 924 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Dissertation Abstracts International by :

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2007 with total page 924 pages. Available in PDF, EPUB and Kindle. Book excerpt: