Product Description: 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...read more

Product Description: When determining the most appropriate method for analyzing longitudinal data, you must first consider what research question you want to answer. In this book, McArdle and Nesselroade identify five basic purposes of longitudinal structural equation modeling...read more

Product Description: This volume brings together a sample of the best of the studies that illustrate two recent trends in research on deviant behavior. The first of these trends is the investigation of deviant behavior in longitudinal perspective. Panels of subjects are followed over long periods of time to establish temporal relationships be­ tween deviant behavior and the antecedents and consequences of deviant behav­ ior...read more

This paperback edition is a reprint of the 2000 edition. It provides comprehensive coverage of linear mixed models for continuous longitudinal data. Next to model formulation, it puts major emphasis on exploratory data analysis for all aspects of the model.

Product Description: The importance that practitioners are placing on longitudinal designs and analyses signals a critical shift toward methods that enable a better understanding of developmental processes thought to underlie many human attributes and behaviors...read more

Product Description: 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...read more

A rigorous, systematic presentation of modern longitudinal analysis Longitudinal studies, employing repeated measurement of subjects over time, play a prominent role in the health and medical sciences as well as in pharmaceutical studies. An important strategy in modern clinical research, they provide valuable insights into both the development and persistence of disease and those factors that can alter the course of disease development. Written at a technical level suitable for researchers and graduate students, Applied Longitudinal Analysis provides a rigorous and comprehensive description of modern methods for analyzing longitudinal data. Focusing on General Linear and Mixed Effects Models for continuous responses, and extensions of Generalized Linear Models for discrete responses, the authors discuss in detail the relationships among these different models, including their underlying assumptions and relative merits. The book features: * A focus on practical applications, utilizing a wide range of examples drawn from real-world studies * Coverage of modern methods of regression analysis for correlated data * Analyses utilizing SAS(r) * Multiple exercises and "homework" problems for review An accompanying Web site features twenty-five real data sets used throughout the text, in addition to programming statements and selected computer output for the examples.

Presenting a thorough and accessible treatment of generalized linear mixed models, also known as multilevel or hierarchical models, Multilevel and Longitudinal Modeling Using Stata explains the models and their assumptions, applies methods to real data using Stata, and shows how to interpret the results. Beginning with the comparatively simple random-intercept linear model without covariates, the text develops the mixed model from first principles, familiarizing the reader with terminology, summarizing and relating the widely used estimating strategies, and providing historical perspective. Once this mixed-model foundation has been established, the text smoothly transitions to random-intercept models with covariates and then to random-coefficient models. The middle chapters apply the concepts defined earlier for Gaussian models to models for binary responses (e.g., logit and probit), ordinal responses (e.g., ordered logit and ordered probit), and count responses (e.g., Poisson). Models with multiple levels of random variation are then considered, as well as models with crossed (nonnested) random effects. The most complete and up-to-date depiction of Stata’s capacity for fitting generalized linear mixed models, Multilevel and Longitudinal Modeling Using Stata serves as an ideal introduction for Stata users wishing to learn about this powerful data-analysis tool.

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Product Description: Taking the Long View is a study of documentary series such as Michael Apted's world-famous Seven Up films that set out to trace the life-journeys of individuals from their earliest schooldays till they are fully grown adults, often with children of their own...read more

Product Description: Latent growth curve modeling (LGM)―a special case of confirmatory factor analysis designed to model change over time―is an indispensable and increasingly ubiquitous approach for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modeling approaches, and highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit...read more

Product Description: 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...read more

Product Description: The book features 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 the material...read more

Product Description: This book provides a systematic exposition of a group-based statistical method for analyzing longitudinal data in the social and behavioral sciences and in medicine. The methods can be applied to a wide range of data, such as that describing the progression of delinquency and criminality over the life course, changes in income over time, the course of a disease or physiological condition, or the evolution of the socioeconomic status of communities...read more

Product Description: Focusing on an analysis of models and data that arise from repeated observations of a cross-section of individuals, households or firms, this book also covers important applications within business, economics, education, political science and other social science disciplines...read more (view table of contents, read Amazon.com's description)