# Methods 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 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.

Produk Detail:

• Author : Xian Liu
• Publisher : Elsevier
• Pages : 530 pages
• ISBN : 0128014822
• Rating : 4/5 from 21 reviews

## Methods and Applications of Longitudinal Data Analysis

• Author : Xian Liu
• Publisher : Elsevier
• Release : 11 September 2015

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

## Longitudinal Data Analysis

• Author : Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs
• Publisher : CRC Press
• Release : 11 August 2008

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.

## Longitudinal Data Analysis

• Author : Jason Newsom,Richard N. Jones,Scott M. Hofer
• Publisher : Routledge
• Release : 22 May 2012

First Published in 2012. Routledge is an imprint of Taylor & Francis, an informa company.

## Applied Longitudinal Analysis

• Author : Garrett M. Fitzmaurice,Nan M. Laird,James H. Ware
• Publisher : John Wiley & Sons
• Release : 23 October 2012

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

## Longitudinal Data Analysis

• Author : Donald Hedeker,Robert D. Gibbons
• Publisher : John Wiley & Sons
• Release : 12 May 2006

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

## Longitudinal and Panel Data

• Author : Edward W. Frees,Frees
• Publisher : Cambridge University Press
• Release : 16 August 2004

An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.

## Analysis of Longitudinal Data

• Author : Peter Diggle,Patrick Heagerty,Kung-Yee Liang,Scott Zeger
• Publisher : Oxford University Press
• Release : 14 March 2013

This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.

## Analysis of Longitudinal Data with Example

• Author : You-Gan Wang,Liya Fu,Sudhir Paul
• Publisher : CRC Press
• Release : 28 January 2022

Development in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the modern approaches to inference, including the links between the theories of estimators and various types of efficient statistical models including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case-studies from a

## Methods and Applications of Statistics in the Life and Health Sciences

• Author : N. Balakrishnan
• Publisher : John Wiley & Sons
• Release : 01 January 2010

"Data collection holds an essential part in dictating the future of health sciences and public health, as the compilation of statistics allows researchers and medical practitioners to monitor trends in health status, identify health problems, and evaluate the impact of health policies and programs. Methods and Applications of Statistics in the Life and Health Sciences serves as a single, one-of-a-kind resource on the wide range of statistical methods, techniques, and applications that are applied in modern life and health sciences

## Advances in Longitudinal Data Methods in Applied Economic Research

• Author : Nicholas Tsounis,Aspasia Vlachvei
• Publisher : Springer Nature
• Release : 02 May 2021

This volume presents new methods and applications in longitudinal data estimation methodology in applied economic. Featuring selected papers from the 2020 the International Conference on Applied Economics (ICOAE 2020) held virtually due to the corona virus pandemic, this book examines interdisciplinary topics such as financial economics, international economics, agricultural economics, marketing and management. Country specific case studies are also featured.

## Nonparametric Regression Methods for Longitudinal Data Analysis

• Author : Hulin Wu,Jin-Ting Zhang
• Publisher : John Wiley & Sons
• Release : 12 May 2006

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.

## Methods and Applications of Statistics in Clinical Trials, Volume 1

• Author : N. Balakrishnan
• Publisher : John Wiley & Sons
• Release : 05 March 2014

A complete guide to the key statistical concepts essential for the design and construction of clinical trials As the newest major resource in the field of medical research, Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs presents a timely and authoritative reviewof the central statistical concepts used to build clinical trials that obtain the best results. The referenceunveils modern approaches vital to understanding, creating, and evaluating data obtained throughoutthe various stages of clinical trial

## Longitudinal Analysis

• Author : Lesa Hoffman
• Publisher : Routledge
• Release : 30 January 2015

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

## Joint Modeling of Longitudinal and Time-to-Event Data

• Author : Robert Elashoff,Gang li,Ning Li
• Publisher : CRC Press
• Release : 04 October 2016

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

## Applied Longitudinal Data Analysis

• Author : Judith D. Singer,John B. Willett,Charles William Eliot Professor John B Willett,John B.. Willett
• Publisher : Oxford University Press
• Release : 27 March 2003

By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives.