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.
Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
"This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies.
Longitudinal Data Analysis: Methods and Applications
Furthermore, as noted by Allison [1982], the regression coeflicients of the model are invariant to interval length. ... In the ordinal treatment, survival time is represented by the ordered outcome Y,-j, which is designated as being ...
This volume presents new methods and applications in longitudinal data estimation methodology in applied economic.
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 ...
An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.
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 ...
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.
This book is a practical guide for the analysis of longitudinal behavioural data. Longitudinal data consist of repeated measures collected on the same subjects over time.