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Author: Wenqin Pan
Publisher:
ISBN:
Category :
Languages : en
Pages : 244
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Book Description
Author: Wenqin Pan
Publisher:
ISBN:
Category :
Languages : en
Pages : 244
Get Book Here
Book Description
Author: Alexandru Cernat
Publisher: Oxford University Press
ISBN: 0198859988
Category : Mathematics
Languages : en
Pages : 461
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Book Description
Measurement Error in Longitudinal Data tackles the important issue of how to understand and estimate change in the context of imperfect data.
Author: Grace Y. Yi
Publisher: CRC Press
ISBN: 1351588591
Category : Mathematics
Languages : en
Pages : 648
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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: Garrett Fitzmaurice
Publisher: CRC Press
ISBN: 142001157X
Category : Mathematics
Languages : en
Pages : 633
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Book Description
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Author: Johannes Eggs
Publisher: wbv Media GmbH & Company KG
ISBN: 3763941126
Category : Social Science
Languages : en
Pages : 138
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Book Description
Diese Arbeit beschäftigt sich mit Messfehlern in Längsschnittdaten. Messfehler können in besonderem Maße die Messung von Übergängen und Veränderungen über die Zeit beeinflussen. Die Messung von Veränderungen ist jedoch einer der Hauptgründe für das Erheben von Längsschnittdaten. Allerdings werden Messfehler in Längsschnittdaten selten analysiert. Durch die Verknüpfung von Paneldaten mit Registerdaten auf der individuellen Ebene werden in dieser Arbeit Messfehler für den Bezug von Arbeitslosengeld II für fünf aufeinanderfolgende Panelwellen untersucht. Dabei zeigt sich, dass die Messfehler für den Bezug nicht zufällig verteilt sind, sondern mit der Zeit und persönlichen Charakteristiken korrelieren.
Author: Geert Molenberghs
Publisher: Springer Science & Business Media
ISBN: 9780387251448
Category : Mathematics
Languages : en
Pages : 720
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Book Description
The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed in their 2000 book. Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The authors received the American Statistical Association's Excellence in Continuing Education Award based on short courses on longitudinal and incomplete data at the Joint Statistical Meetings of 2002 and 2004.
Author: Francesco Bartolucci
Publisher: CRC Press
ISBN: 1466583711
Category : Mathematics
Languages : en
Pages : 253
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Book Description
Drawing on the authors' extensive research in the analysis of categorical longitudinal data, this book focuses on the formulation of latent Markov models and the practical use of these models. It demonstrates how to use the models in three types of analysis, with numerous examples illustrating how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB routines used for the examples are available on the authors' website.
Author: Grace Y. Yi
Publisher: Springer
ISBN: 1493966405
Category : Mathematics
Languages : en
Pages : 497
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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: Xian Liu
Publisher: Elsevier
ISBN: 0128014822
Category : Mathematics
Languages : en
Pages : 531
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Book Description
Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: - descriptive methods for delineating trends over time - linear mixed regression models with both fixed and random effects - covariance pattern models on correlated errors - generalized estimating equations - nonlinear regression models for categorical repeated measurements - techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. - From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis - Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection - Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.
Author: Peter Diggle
Publisher: Oxford University Press, USA
ISBN: 0199676755
Category : Language Arts & Disciplines
Languages : en
Pages : 397
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Book Description
This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.
