November 26, 2020

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Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis
Author : Xian Liu
Publisher : Elsevier
Release Date : 2015-09-11
Category : Mathematics
Total pages :530
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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.

Longitudinal Data Analysis

Longitudinal Data Analysis
Author : Mark D. Uncles
Publisher : Pion Limited
Release Date : 1988
Category : Analyse de données
Total pages :152
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Longitudinal Data Analysis

Longitudinal Data Analysis
Author : Jason Newsom,Richard N. Jones,Scott M. Hofer
Publisher : Routledge
Release Date : 2013-06-19
Category : Psychology
Total pages :405
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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.

Longitudinal Data Analysis

Longitudinal Data Analysis
Author : Donald Hedeker,Robert D. Gibbons
Publisher : John Wiley & Sons
Release Date : 2006-05-12
Category : Mathematics
Total pages :360
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Longitudinal data analysis for biomedical and behavioral sciences This innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in the biomedical and behavioral sciences. Reflecting the growing importance and use of longitudinal data across many areas of research, the text is designed to help users of statistics better analyze and understand this type of data. Much of the material from the book grew out of a course taught by Dr. Hedeker on longitudinal data analysis. The material is, therefore, thoroughly classroom tested and includes a number of features designed to help readers better understand and apply the material. Statistical procedures featured within the text include: * Repeated measures analysis of variance * Multivariate analysis of variance for repeated measures * Random-effects regression models (RRM) * Covariance-pattern models * Generalized-estimating equations (GEE) models * Generalizations of RRM and GEE for categorical outcomes Practical in their approach, the authors emphasize the applications of the methods, using real-world examples for illustration. Some syntax examples are provided, although the authors do not generally focus on software in this book. Several datasets and computer syntax examples are posted on this title's companion Web site. The authors intend to keep the syntax examples current as new versions of the software programs emerge. This text is designed for both undergraduate and graduate courses in longitudinal data analysis. Instructors can take advantage of overheads and additional course materials available online for adopters. Applied statisticians in biomedicine and the social sciences can also use the book as a convenient reference.

Applied Longitudinal Analysis

Applied Longitudinal Analysis
Author : Garrett M. Fitzmaurice,Nan M. Laird,James H. Ware
Publisher : John Wiley & Sons
Release Date : 2012-10-23
Category : Mathematics
Total pages :740
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Praise for the First Edition ". . . [this book] should be on the shelf of everyone interestedin . . . longitudinal data analysis." —Journal of the American Statistical Association Features newly developed topics and applications of theanalysis of longitudinal data Applied Longitudinal Analysis, Second Edition presentsmodern methods for analyzing data from longitudinal studies and nowfeatures the latest state-of-the-art techniques. The bookemphasizes practical, rather than theoretical, aspects of methodsfor the analysis of diverse types of longitudinal data that can beapplied across various fields of study, from the health and medicalsciences to the social and behavioral sciences. The authors incorporate their extensive academic and researchexperience along with various updates that have been made inresponse to reader feedback. The Second Edition features six newlyadded 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 effectsmodels Multiple imputation and inverse probability weightedmethods Smoothing methods for longitudinal data Sample size and power Each chapter presents methods in the setting of applications todata sets drawn from the health sciences. New problem sets havebeen added to many chapters, and a related website features sampleprograms and computer output using SAS, Stata, and R, as well asdata sets and supplemental slides to facilitate a completeunderstanding of the material. With its strong emphasis on multidisciplinary applications andthe interpretation of results, Applied LongitudinalAnalysis, Second Edition is an excellent book for courses onstatistics in the health and medical sciences at theupper-undergraduate and graduate levels. The book also serves as avaluable reference for researchers and professionals in themedical, public health, and pharmaceutical fields as well as thosein social and behavioral sciences who would like to learn moreabout analyzing longitudinal data.

Analysis of Longitudinal Data

Analysis of Longitudinal Data
Author : Peter Diggle,Patrick Heagerty,Kung-Yee Liang,Scott Zeger
Publisher : OUP Oxford
Release Date : 2013-03-14
Category : Mathematics
Total pages :400
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The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models for discrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This second edition, published for the first time in paperback, provides a thorough and expanded revision of this important text. It includes two new chapters; the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.

Longitudinal Data Analysis

Longitudinal Data Analysis
Author : Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs
Publisher : CRC Press
Release Date : 2008-08-11
Category : Mathematics
Total pages :632
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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 and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines. Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.

Longitudinal Data Analysis for the Behavioral Sciences Using R

Longitudinal Data Analysis for the Behavioral Sciences Using R
Author : Jeffrey D. Long
Publisher : SAGE
Release Date : 2011-10-31
Category : Social Science
Total pages :542
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This book is unique in its focus on showing students in the behavioral sciences how to analyze longitudinal data using R software. The book focuses on application, making it practical and accessible to students in psychology, education, and related fields, who have a basic foundation in statistics. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted.

Practical Longitudinal Data Analysis

Practical Longitudinal Data Analysis
Author : David J. Hand,Martin J. Crowder
Publisher : CRC Press
Release Date : 1996-03-01
Category : Mathematics
Total pages :232
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This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.

Longitudinal and Panel Data

Longitudinal and Panel Data
Author : Edward W. Frees,Frees
Publisher : Cambridge University Press
Release Date : 2004-08-16
Category : Business & Economics
Total pages :467
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An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.

Nonparametric Regression Methods for Longitudinal Data Analysis

Nonparametric Regression Methods for Longitudinal Data Analysis
Author : Hulin Wu,Jin-Ting Zhang
Publisher : John Wiley & Sons
Release Date : 2006-05-12
Category : Mathematics
Total pages :384
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Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems.

Applied Longitudinal Data Analysis for Epidemiology

Applied Longitudinal Data Analysis for Epidemiology
Author : Jos W. R. Twisk
Publisher : Cambridge University Press
Release Date : 2013-05-09
Category : Medical
Total pages :321
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A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.

Correlated Data Analysis: Modeling, Analytics, and Applications

Correlated Data Analysis: Modeling, Analytics, and Applications
Author : Peter X. -K. Song
Publisher : Springer Science & Business Media
Release Date : 2007-06-30
Category : Mathematics
Total pages :352
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This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

Analysis of Mixed Data

Analysis of Mixed Data
Author : Alexander R. de Leon,Keumhee Carriere Chough
Publisher : CRC Press
Release Date : 2013-01-16
Category : Mathematics
Total pages :262
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A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. Carefully edited for smooth readability and

Bayesian Biostatistics

Bayesian Biostatistics
Author : Emmanuel Lesaffre,Andrew B. Lawson
Publisher : John Wiley & Sons
Release Date : 2012-08-13
Category : Mathematics
Total pages :516
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This book provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementations, with an emphasis on healthcare techniques. Contains introductory explanations of Bayesian principles common to all areas.