Modeling Longitudinal Data
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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.
Longitudinal data are ubiquitous across Medicine, Public Health, Public Policy, Psychology, Political Science, Biology, Sociology and Education, yet many longitudinal data sets remain improperly analyzed. This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, understanding, and interpreting longitudinal data models. He inspects the longitudinal data graphically, analyzes the time trend and covariates, models the covariance matrix, and then draws conclusions. Covariance models covered include random effects, autoregressive, autoregressive moving average, antedependence, factor analytic, and completely unstructured models among others. Longer expositions explore: an introduction to and critique of simple non-longitudinal analyses of longitudinal data, missing data concepts, diagnostics, and simultaneous modeling of two longitudinal variables. Applications and issues for random effects models cover estimation, shrinkage, clustered data, models for binary and count data and residuals and residual plots. Shorter sections include a general discussion of how computational algorithms work, handling transformed data, and basic design issues. This book requires a solid regression course as background and is particularly intended for the final year of a Biostatistics or Statistics Masters degree curriculum. The mathematical prerequisite is generally low, mainly assuming familiarity with regression analysis in matrix form. Doctoral students in Biostatistics or Statistics, applied researchers and quantitative doctoral students in disciplines such as Medicine, Public Health, Public Policy, Psychology, Political Science, Biology, Sociology and Education will find this book invaluable. The book has 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 thematerial. From the reviews: "...This book is extremely well presented and it has been written in a style that makes its reading really pleasant and enjoyable...I highly recommend Modeling Longitudinal Data as a good reference book for anyone interested in looking into the art and statistical science of modern longitudinal data analysis." Journal of Applied Statistics, December 2005 "The book is clearly written and well presented. The author's accumulated experience in presenting the material comes over. On balance, this is one of the books which anyone about to teach a practical course in longitudinal data analysis should consider adopting as the course text." Short Book Reviews of the ISI, June 2006 "...Modeling Longitudinal Data is a welcome addition to the vast literature on longitudinal data analysis. The book requires little in terms of prerequisites but offers a great deal." Zhigang Zhang for the Journal of the American Statistical Association, December 2006 "Overall, Robert Weiss's book can be used as an excellent textbook for a first master-level course in longitudinal data analysis in a statistics or biostatistics program, or as a self-study book for applied researchers interested in this area...The style is very clear, concepts are explained in an engaging way and amply illustrated, and the chapters on covariate selection and modeling the variance-covariance matrix are definite assets." Ralitza Gueorgueiva for Biostatistics, September 2006
Methods And Applications Of Longitudinal Data Analysis
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Author : Xian Liu
language : en
Publisher: Elsevier
Release Date : 2015-09-01
Methods And Applications Of Longitudinal Data Analysis written by Xian Liu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-01 with Mathematics categories.
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 Analysis
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Author : Lesa Hoffman
language : en
Publisher: Routledge
Release Date : 2015-01-30
Longitudinal Analysis written by Lesa Hoffman and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-30 with Psychology categories.
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 equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. Written for non-mathematically-oriented readers, this text features: A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data An emphasis on how the terminology, interpretation, and estimation of familiar general linear models relates to those of more complex models for longitudinal data Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers’ understanding of the overall model-building process Sample results sections for each example to provide useful templates for published reports Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and Mplus at www.PilesOfVariance.com to help readers apply the models to their own data The book opens with the building blocks of longitudinal analysis—general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces unconditional longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. Conditional longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data. Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book’s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text.
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
Linear Mixed Models For Longitudinal Data
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Author : Geert Verbeke
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-05-12
Linear Mixed Models For Longitudinal Data written by Geert Verbeke 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 2009-05-12 with Mathematics categories.
This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.
Longitudinal Data Analysis
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Author : Ikuko Funatogawa
language : en
Publisher: Springer
Release Date : 2019-02-04
Longitudinal Data Analysis written by Ikuko Funatogawa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-04 with Mathematics categories.
This book provides a new analytical approach for dynamic data repeatedly measured from multiple subjects over time. Random effects account for differences across subjects. Auto-regression in response itself is often used in time series analysis. In longitudinal data analysis, a static mixed effects model is changed into a dynamic one by the introduction of the auto-regression term. Response levels in this model gradually move toward an asymptote or equilibrium which depends on covariates and random effects. The book provides relationships of the autoregressive linear mixed effects models with linear mixed effects models, marginal models, transition models, nonlinear mixed effects models, growth curves, differential equations, and state space representation. State space representation with a modified Kalman filter provides log likelihoods for maximum likelihood estimation, and this representation is suitable for unequally spaced longitudinal data. The extension to multivariate longitudinal data analysis is also provided. Topics in medical fields, such as response-dependent dose modifications, response-dependent dropouts, and randomized controlled trials are discussed. The text is written in plain terms understandable for researchers in other disciplines such as econometrics, sociology, and ecology for the progress of interdisciplinary research.
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
Applied Longitudinal Data Analysis
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Author : Judith D. Singer
language : en
Publisher: Oxford University Press
Release Date : 2003-03-27
Applied Longitudinal Data Analysis written by Judith D. Singer 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 2003-03-27 with Mathematics categories.
By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives.
Longitudinal Data Analysis
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Author : Professor Catrien C J H C J H Bijleveld
language : en
Publisher: SAGE
Release Date : 1998-10-26
Longitudinal Data Analysis written by Professor Catrien C J H C J H Bijleveld and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-26 with Social Science categories.
By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.
Models For Discrete Longitudinal Data
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Author : Geert Molenberghs
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-08-30
Models For Discrete Longitudinal Data written by Geert Molenberghs 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 2006-08-30 with Mathematics categories.
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.