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The theory and practice of longitudinal studies; Sampling and design; The choice of measurement scales over time; The analysis of models for time related measurement; The analysis of models for relating measurements at differene occasions; Population standards or norms; Data processing.
By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. 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 appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.
This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose the techniques that best fit their research. The analyses are illustrated with examples from major longitudinal data sets including practical information about their content and design. Illustrations from popular software packages offer tips on how to interpret the results. Each chapter features suggested readings for additional study and a list of articles that further illustrate how to implement the analysis and report the results. Syntax examples for several software packages for each of the chapter examples are provided at www.psypress.com/longitudinal-data-analysis. Although many of the examples address health or social science questions related to aging, readers from other disciplines will find the analyses relevant to their work. In addition to demonstrating statistical analysis of longitudinal data, the book shows how to interpret and analyze the results within the context of the research design. The methods covered in this book are applicable to a range of applied problems including short- to long-term longitudinal studies using a range of sample sizes. The book provides non-technical, practical introductions to the concepts and issues relevant to longitudinal analysis. Topics include use of publicly available data sets, weighting and adjusting for complex sampling designs with longitudinal studies, missing data and attrition, measurement issues related to longitudinal research, the use of ANOVA and regression for average change over time, mediation analysis, growth curve models, basic and advanced structural equation models, and survival analysis. An ideal supplement for graduate level courses on data analysis and/or longitudinal modeling taught in psychology, gerontology, public health, human development, family studies, medicine, sociology, social work, and other behavioral, social, and health sciences, this multidisciplinary book will also appeal to researchers in these fields.
Longitudinal research is a broad field in which substantial advances have been made over the past decade. Unlike many of the existing books that only address the analysis of information. The Handbook of Longitudinal Research covers design and measurement as well as the data analysis. Designed for use by a wide-ranging audience, this Handbook not only includes perspective on the methodological and data analysis problems in longitudinal research but it also includes contributors' data sets that enable readers who lack sophisticated statistics skills to move from theories about longitudinal data into practice. As the comprehensive reference, this Handbook has no direct competition as most books in this subject area are more narrowly specialized and are pitched at a high mathematical level. Contributors and subject areas are interdisciplinary to reach the broadest possible audience (i.e., psychology, epidemiology, and economics research fields) Summary material will be included for less sohisticated readers Extensive coverage is provided of traditional advanced topics
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
This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinical psychological scientists.
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.
The present book project on Research Design, which is planned in English, is intended to create an innovative textbook that can be used at university undergraduate and graduate levels in internationally oriented education in the German-speaking countries. This textbook shall provide comprehensive guidance for students when tackling their (applied) research papers. Instead of reiterating qualitative and quantitative methods it focuses on how to come up with an appropriate research design that allows the student to make the intended intellectual contribution. Starting from the desired (hypothetical) conclusion or statement the student will be guided through the process of finding the appropriate Research Question that will be answered by such a statement and the required Research Design consisting of data collection and data analysis, that allows for such a statement as the conclusion of the study. Common Research Designs in Business and Management, i.e. well beyond the standard Research Designs of Social Sciences and curtailed to the focus area, will be described with regard to their suitability to answer specific kinds of questions as well as the idiosyncrasies of the these Designs and their impact on the written research reports. Examples for each Research Design will be provided as well as guidance about how to write about such research.
This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website (www.intensivelongitudinal.com).
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.