Statistical Models For Longitudinal Studies Of Health
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Statistical Models For Longitudinal Studies Of Health
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Author : James H. Dwyer
language : en
Publisher: Oxford University Press, USA
Release Date : 1992-01
Statistical Models For Longitudinal Studies Of Health written by James H. Dwyer and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-01 with Epidemiology categories.
Longitudinal studies of health outcomes and their risk factors are increasingly important source of knowledge in epidemiology,, public health and clinical medicine. However, many of the statistical procedures suited to the analysis of findings from these studies have emerged only recently. This book brings together the mopst important of these developments.
Longitudinal Data Analysis
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Author : Jason Newsom
language : en
Publisher: Routledge
Release Date : 2013-06-19
Longitudinal Data Analysis written by Jason Newsom and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-19 with Psychology categories.
This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose the techniques that best fit their research. The analyses are illustrated with examples from major longitudinal data sets including practical information about their content and design. Illustrations from popular software packages offer tips on how to interpret the results. Each chapter features suggested readings for additional study and a list of articles that further illustrate how to implement the analysis and report the results. Syntax examples for several software packages for each of the chapter examples are provided at www.psypress.com/longitudinal-data-analysis. Although many of the examples address health or social science questions related to aging, readers from other disciplines will find the analyses relevant to their work. In addition to demonstrating statistical analysis of longitudinal data, the book shows how to interpret and analyze the results within the context of the research design. The methods covered in this book are applicable to a range of applied problems including short- to long-term longitudinal studies using a range of sample sizes. The book provides non-technical, practical introductions to the concepts and issues relevant to longitudinal analysis. Topics include use of publicly available data sets, weighting and adjusting for complex sampling designs with longitudinal studies, missing data and attrition, measurement issues related to longitudinal research, the use of ANOVA and regression for average change over time, mediation analysis, growth curve models, basic and advanced structural equation models, and survival analysis. An ideal supplement for graduate level courses on data analysis and/or longitudinal modeling taught in psychology, gerontology, public health, human development, family studies, medicine, sociology, social work, and other behavioral, social, and health sciences, this multidisciplinary book will also appeal to researchers in these fields.
Modeling Longitudinal Data
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Author : Robert E. Weiss
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-12-06
Modeling Longitudinal Data written by Robert E. Weiss and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-06 with Medical categories.
The book features many figures and tables illustrating longitudinal data and numerous homework problems. The associated web site contains many longitudinal data sets, examples of computer code, and labs to re-enforce the material. Weiss emphasizes continuous data rather than discrete data, graphical and covariance methods, and generalizations of regression rather than generalizations of analysis of variance.
Joint Modeling Of Longitudinal And Time To Event Data
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Author : Robert Elashoff
language : en
Publisher: CRC Press
Release Date : 2016-10-04
Joint Modeling Of Longitudinal And Time To Event Data written by Robert Elashoff and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-04 with Mathematics categories.
Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.
Analysis Of Longitudinal Data
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Author : Peter Diggle
language : en
Publisher: Oxford University Press, USA
Release Date : 1994
Analysis Of Longitudinal Data written by Peter Diggle and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Mathematics categories.
Describes statistical models and methods for the analysis of longitudinal data, with a strong emphasis on applications in the biological and health sciences. Addressed to advanced undergraduates or first-year graduates in statistics, and may also be accessible to readers with less technical knowledge but more experience in longitudinal studies. Annotation copyright by Book News, Inc., Portland, OR
Statistical Methods For Quality Of Life Studies
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Author : Mounir Mesbah
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Statistical Methods For Quality Of Life Studies written by Mounir Mesbah and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Medical categories.
On October 16 and 17, 2000, we hosted an international workshop entitled "Statistical Design, Measurement, and Analysis of Health Related Quality of Life." The workshop was held in the beautiful city of Arradon, South Brittany, France with the main goal of fostering an interdisciplinary forum for discussion of theoretical and applied statistical issues arising in studies of health-related quality of life (HRQoL). Included were biostatisticians, psychometricians and public health professionals (e.g., physicians, sociologists, psychologists) active in the study ofHRQoL. In assembling this volume, we invited each conference participant to contribute a paper based on his or her presentation and the ensuing and very interesting discussions that took place in Arradon. All papers were peer-reviewed, by anonymous reviewers, and revised before final editing and acceptance. Although this process was quite time consuming, we believe that it greatly improved the volume as a whole, making this book a valuable contribution to the field ofHRQoL research. The volume presents a broad spectrum of papers presented at the Workshop, and thus illustrates the range of current research related to the theory, methods and applications of HRQoL, as well as the interdisciplinary nature ofthis work. Following an introduction written by Sir David Cox, it includes 27 articles organized into the following chapters.
Longitudinal Data Analysis
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Author : Garrett Fitzmaurice
language : en
Publisher: CRC Press
Release Date : 2008-08-11
Longitudinal Data Analysis written by Garrett Fitzmaurice and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-11 with Mathematics categories.
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
Models For Intensive Longitudinal Data
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Author : Theodore A. Walls
language : en
Publisher: Oxford University Press
Release Date : 2006-01-19
Models For Intensive Longitudinal Data written by Theodore A. Walls and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-19 with Medical categories.
Rapid technological advances in devices used for data collection have led to the emergence of a new class of longitudinal data: intensive longitudinal data (ILD). Behavioral scientific studies now frequently utilize handheld computers, beepers, web interfaces, and other technological tools for collecting many more data points over time than previously possible. Other protocols, such as those used in fMRI and monitoring of public safety, also produce ILD, hence the statistical models in this volume are applicable to a range of data. The volume features state-of-the-art statistical modeling strategies developed by leading statisticians and methodologists working on ILD in conjunction with behavioral scientists. Chapters present applications from across the behavioral and health sciences, including coverage of substantive topics such as stress, smoking cessation, alcohol use, traffic patterns, educational performance and intimacy. Models for Intensive Longitudinal Data (MILD) is designed for those who want to learn about advanced statistical models for intensive longitudinal data and for those with an interest in selecting and applying a given model. The chapters highlight issues of general concern in modeling these kinds of data, such as a focus on regulatory systems, issues of curve registration, variable frequency and spacing of measurements, complex multivariate patterns of change, and multiple independent series. The extraordinary breadth of coverage makes this an indispensable reference for principal investigators designing new studies that will introduce ILD, applied statisticians working on related models, and methodologists, graduate students, and applied analysts working in a range of fields. A companion Web site at www.oup.com/us/MILD contains program examples and documentation.
Applied Longitudinal Analysis
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Author : Garrett M. Fitzmaurice
language : en
Publisher: John Wiley & Sons
Release Date : 2012-10-23
Applied Longitudinal Analysis written by Garrett M. Fitzmaurice and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-23 with Mathematics categories.
Praise for the First Edition ". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis." —Journal of the American Statistical Association Features newly developed topics and applications of the analysis of longitudinal data Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of longitudinal data that can be applied across various fields of study, from the health and medical sciences to the social and behavioral sciences. The authors incorporate their extensive academic and research experience along with various updates that have been made in response to reader feedback. The Second Edition features six newly added chapters that explore topics currently evolving in the field, including: Fixed effects and mixed effects models Marginal models and generalized estimating equations Approximate methods for generalized linear mixed effects models Multiple imputation and inverse probability weighted methods Smoothing methods for longitudinal data Sample size and power Each chapter presents methods in the setting of applications to data sets drawn from the health sciences. New problem sets have been added to many chapters, and a related website features sample programs and computer output using SAS, Stata, and R, as well as data sets and supplemental slides to facilitate a complete understanding of the material. With its strong emphasis on multidisciplinary applications and the interpretation of results, Applied Longitudinal Analysis, Second Edition is an excellent book for courses on statistics in the health and medical sciences at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields as well as those in social and behavioral sciences who would like to learn more about analyzing longitudinal data.
Missing Data In Longitudinal Studies
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Author : Michael J. Daniels
language : en
Publisher: CRC Press
Release Date : 2008-03-11
Missing Data In Longitudinal Studies written by Michael J. Daniels and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-11 with Mathematics categories.
Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies. To illustrate these methods, the authors employ