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Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis
  • Author : Xian Liu
  • Publsiher : Elsevier
  • Release : 11 September 2015
  • ISBN : 0128014822
  • Pages : 530 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKMethods and Applications of Longitudinal Data Analysis

Summary:
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.


Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis
  • Author : Xian Liu
  • Publisher : Elsevier
  • Release : 11 September 2015
GET THIS BOOKMethods and Applications of Longitudinal Data Analysis

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

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Longitudinal Data Analysis

Longitudinal Data Analysis
  • Author : Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs
  • Publisher : CRC Press
  • Release : 11 August 2008
GET THIS BOOKLongitudinal Data Analysis

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.

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Longitudinal Data Analysis

Longitudinal Data Analysis
  • Author : Donald Hedeker,Robert D. Gibbons
  • Publisher : John Wiley & Sons
  • Release : 12 May 2006
GET THIS BOOKLongitudinal Data Analysis

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

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Joint Modeling of Longitudinal and Time-to-Event Data

Joint Modeling of Longitudinal and Time-to-Event Data
  • Author : Robert Elashoff,Gang li,Ning Li
  • Publisher : CRC Press
  • Release : 04 October 2016
GET THIS BOOKJoint Modeling of Longitudinal and Time-to-Event Data

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

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Longitudinal Analysis

Longitudinal Analysis
  • Author : Lesa Hoffman
  • Publisher : Routledge
  • Release : 30 January 2015
GET THIS BOOKLongitudinal Analysis

Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model

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Nonparametric Regression Analysis of Longitudinal Data

Nonparametric Regression Analysis of Longitudinal Data
  • Author : Hans-Georg Müller
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKNonparametric Regression Analysis of Longitudinal Data

This monograph reviews some of the work that has been done for longitudi nal data in the rapidly expanding field of nonparametric regression. The aim is to give the reader an impression of the basic mathematical tools that have been applied, and also to provide intuition about the methods and applications. Applications to the analysis of longitudinal studies are emphasized to encourage the non-specialist and applied statistician to try these methods out. To facilitate this, FORTRAN programs are provided which

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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 : 12 May 2006
GET THIS BOOKNonparametric Regression Methods for Longitudinal Data Analysis

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.

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Sequence Analysis and Related Approaches

Sequence Analysis and Related Approaches
  • Author : Gilbert Ritschard,Matthias Studer
  • Publisher : Springer
  • Release : 17 October 2018
GET THIS BOOKSequence Analysis and Related Approaches

This open access book provides innovative methods and original applications of sequence analysis (SA) and related methods for analysing longitudinal data describing life trajectories such as professional careers, family paths, the succession of health statuses, or the time use. The applications as well as the methodological contributions proposed in this book pay special attention to the combined use of SA and other methods for longitudinal data such as event history analysis, Markov modelling, and sequence network. The methodological contributions in

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Practical Longitudinal Data Analysis

Practical Longitudinal Data Analysis
  • Author : David J. Hand
  • Publisher : Routledge
  • Release : 06 October 2017
GET THIS BOOKPractical Longitudinal Data Analysis

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.

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Longitudinal Data Analysis

Longitudinal Data Analysis
  • Author : Jason Newsom,Richard N. Jones,Scott M. Hofer
  • Publisher : Routledge
  • Release : 19 June 2013
GET THIS BOOKLongitudinal Data Analysis

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

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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 : 31 October 2011
GET THIS BOOKLongitudinal Data Analysis for the Behavioral Sciences Using R

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.

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Intensive Longitudinal Methods

Intensive Longitudinal Methods
  • Author : Niall Bolger,Jean-Philippe Laurenceau
  • Publisher : Guilford Press
  • Release : 22 January 2013
GET THIS BOOKIntensive Longitudinal Methods

This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical

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