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First published Open Access under a Creative Commons license as What is Quantitative Longitudinal Data Analysis?, this title is now also available as part of the Bloomsbury Research Methods series.Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data resources. But, to date, many texts on analysing longitudinal social analysis surveys have been written from a statistical, rather than a social science data analysis perspective and they lack adequate coverage of common practical challenges associated with social science data analyses. This book provides a practical and up-to-date introduction to influential approaches to quantitative longitudinal data analysis in the social sciences. The book introduces definitions and terms, explains the relative attractions of such a longitudinal design, and offers an introduction to the main techniques of analysis, explaining their requirements, statistical properties and their substantive contribution.

An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state–trait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Following a standard format, chapters review the theoretical underpinnings, strengths, and limitations of the various models; present data examples; and demonstrate each model's application and interpretation in Mplus, with numerous screen shots and output excerpts. Coverage encompasses both traditional models (autoregressive, change score, and growth curve models) and LST models for analyzing single- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data handling, and provides strategies for model selection and reporting of results. User-friendly features include special-topic boxes, chapter summaries, and suggestions for further reading. The companion website features data sets, annotated syntax files, and output for all of the examples.

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. This volume offers a new introduction to an evolving research method in the social sciences. Qualitative Longitudinal (QL) research is conducted through time. In its qualitative dimensions it opens up the potential to'think dynamically'in creative, flexible and innovative ways. QL enquiry is rooted in a long-established tradition of qualitative temporal research, spanning the fields of social anthropology, sociological re-studies and biographical research. But over the past two decades, a growing body of scholarship has begun to document this approach and explore its theoretical underpinnings. This in turn has fuelled a growing interest in and rapid uptake of QL methodology across the disciplines and in international context. This practical volume will be a first port of call for students and researchers wishing to use QL research in their own projects. The chapters follow a logical development, from conceptual and methodological foundations, to research practice and ethics, to the generation and analysis of data. Each chapter offers practical examples drawn from the research field to illustrate key themes and the rich possibilities for new applications.

Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features •Real, worked-through longitudinal data examples serving as illustrations in each chapter. •Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. •'Important Considerations'sections offering caveats, warnings, and recommendations for the use of specific models. •Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling. Winner--Barbara Byrne Book Award from the Society of Multivariate Experimental Psychology

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. A simple scan of one's own applied literature reveals evidence of this trend through the increasing number of articles adopting longitudinal methods as their primary analytic tools. Advances in Longitudinal Methods in the Social and Behavioral Sciences is a resource intended for advanced graduate students, faculty, and applied researchers interested in longitudinal data analysis, especially in the social and behavioral sciences. The chapters are written by established methodological researchers from diverse research domains such as psychology, biostatistics, educational statistics, psychometrics, and family sciences. Each chapter exposes the reader to some of the latest methodological developments and perspectives in the analysis of longitudinal data, and is written in a didactic tone that makes the content accessible to the broader research community. This volume will be particularly appealing to researchers in domains including, but not limited to: human development, clinical psychology, educational psychology, school psychology, special education, epidemiology, family science, kinesiology, communication disorders, and education policy and administration. The book will also be attractive to members of several professional organizations such as the American Educational Research Association (AERA), the American Psychological Association (APA), the American Psychological Society (APS), the Society for Research on Adolescence (SRA), the Society of Research in Child Development (SRCD), Society for Research in Adult Development (SRAD), British Psychological Society (BPS), Canadian Psychological Association (CPA), and other related organizations.

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. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted.'This text excels in the explanation of models with the side-by-side use of R, so the audience can see the models in action. There is a gentle coverage of the mathematics driving the models, which does not seem intimidating to a non technical audience.'—William Anderson, Cornell University

The study of social dynamics using quantitative methodology is complex and calls for cutting-edge technical and methodological approaches in social science research. This book presents the existing statistical models and methods available for understanding social change over time. It provides step-by-step instructions for designing and conducting longitudinal research, with special focus on the longitudinal analysis of both quantitative outcomes (for the modeling of change in continuous variables) and qualitative outcomes (for the modeling of events occurring over time). Readers will learn how to study change in variables over time and how to formulate and estimate multivariate longitudinal models to predict such change, mainly using cross-sectional, cross-time and event history analyzes. This text also teaches how to design and implement a study using longitudinal data from the selection and collection of appropriate variables to the most effective ways to analyze and present data for publication in top social science journals.

This focuses on models and data that arise from repeated observations of a cross-section of individuals, households or companies. These models have found important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented graduate social science students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also describes substantive applications from across the social sciences, showing the breadth and scope that these models enjoy. The applications are enhanced by real-world data sets and software programs in SAS and Stata.

One of the major changes in the social science research landscape in recent years has been the introduction of computerised panel surveys in Europe and the US which make longitudinal data widely available to graduate students for the first time. Elisabetta Ruspini here provides a concise yet comprehensive introduction to the issues involved in this kind of research. This book:• Defines the concept of longitudinal research• Gives guidance on sources of longitudinal data in Europe and the US and their strengths and weaknesses• Discusses the choices that need to be made in this kind of research - for instance the advantages and disadvantages of certain types of research data and of different types of analysis• Highlights some of the problems involved, e.g. the issue of comparability within longitudinal research

`The author has done a remarkable job of writing a very accessible introduction to a broad literature. As such, he should be congratulated on achieving his objective to provide the'ideal primer for this growing area of social research'′ - Kwantitatieve Methoden This accessible introduction to the theory and practice of longitudinal research takes the reader through the strengths and weaknesses of this kind of research, making clear: how to design a longitudinal study; how to collect data most effectively; how to make the best use of statistical techniques; and how to interpret results. Although the book provides a broad overview of the field, the focus is always on the practical issues arising out of longitudinal research. This book supplies the student with all that they need to get started and acts as a manual for dealing with opportunities and pitfalls. It is the ideal primer for this growing area of social research.