Applied Linear Regression For Longitudinal Data
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Applied Linear Regression For Longitudinal Data
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Author : Frans E.S. Tan
language : en
Publisher: CRC Press
Release Date : 2022-12-09
Applied Linear Regression For Longitudinal Data written by Frans E.S. Tan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-09 with Mathematics categories.
This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions such as multiple imputation are explained conceptually and consequences of missing observations are clarified using visualization techniques. Key features include the following: Provides datasets and examples online Gives state-of-the-art methods of dealing with missing observations in a non-technical way with a special focus on sensitivity analysis Conceptualises the analysis of comparative (experimental and observational) studies It is the ideal companion for researchers and students in epidemiological, health, and social and behavioral sciences working with longitudinal studies without a mathematical background.
Applied Linear Regression For Longitudinal Data
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Author : Frans E.S. Tan
language : en
Publisher: CRC Press
Release Date : 2022-12-09
Applied Linear Regression For Longitudinal Data written by Frans E.S. Tan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-09 with Mathematics categories.
This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions such as multiple imputation are explained conceptually and consequences of missing observations are clarified using visualization techniques. Key features include the following: Provides datasets and examples online Gives state-of-the-art methods of dealing with missing observations in a non-technical way with a special focus on sensitivity analysis Conceptualises the analysis of comparative (experimental and observational) studies It is the ideal companion for researchers and students in epidemiological, health, and social and behavioral sciences working with longitudinal studies without a mathematical background.
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.
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.
Applied Longitudinal Data Analysis For Epidemiology
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Author : Jos W. R. Twisk
language : en
Publisher: Cambridge University Press
Release Date : 2013-05-09
Applied Longitudinal Data Analysis For Epidemiology written by Jos W. R. Twisk and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-09 with Medical categories.
A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.
Beyond Multiple Linear Regression
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Author : Paul Roback
language : en
Publisher: CRC Press
Release Date : 2021-01-14
Beyond Multiple Linear Regression written by Paul Roback and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Mathematics categories.
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling. A solutions manual for all exercises is available to qualified instructors at the book’s website at www.routledge.com, and data sets and Rmd files for all case studies and exercises are available at the authors’ GitHub repo (https://github.com/proback/BeyondMLR)
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
Nonparametric Regression Methods For Longitudinal Data Analysis
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Author : Hulin Wu
language : en
Publisher: John Wiley & Sons
Release Date : 2006-05-12
Nonparametric Regression Methods For Longitudinal Data Analysis written by Hulin Wu 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 2006-05-12 with Mathematics categories.
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 Linear Regression For Longitudinal Data
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Author : Frans Tan
language : en
Publisher: CRC Press
Release Date : 2023
Applied Linear Regression For Longitudinal Data written by Frans Tan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Mathematics categories.
"This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths, while at the same time not requiring much prior knowledge about regression analysis. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions such as multiple imputation are explained conceptually and consequences of missing observations (in the outcome and/or independent variables) are clarified using visualization techniques. Key Features: Provides datasets and example online; Gives state-of-the-art methods of dealing with missing observations in a non-technical way with a special focus on sensitivity analysis; Conceptualize the analysis of comparative (experimental and observational) studies. It is the ideal companion for researcher and students in epidemiological, health, and social and behavioural sciences working with longitudinal studies without a mathematical background"--
Applied Regression Analysis And Generalized Linear Models
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Author : John Fox
language : en
Publisher: SAGE Publications
Release Date : 2015-03-18
Applied Regression Analysis And Generalized Linear Models written by John Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-18 with Social Science categories.
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.